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Out-of-system (OoS) interference is a potential limitation for distributed networks that operate in unlicensed spectrum or in a spectrum sharing scenario. The OoS interference differs from the in-system interference in that OoS signals and their associated channels (or even their statistics) are completely unknown. In this letter, we propose a novel distributed algorithm that can mitigate OoS interference in the uplink and suppress the signal transmission in the OoS direction in the downlink. To estimate the OoS interference, each access point (AP), upon receiving an estimate of OoS interference from a previous AP, computes a better estimate of OoS interference by rotate-and-average using Procrustes method and forwards the estimates to the next AP. This process continues until the central processing unit (CPU) receives the final estimate. Our method has comparable performance to that of a fully centralized interference rejection combining algorithm and has much lower fronthaul load requirements., Funding Agencies|REINDEER Project of the European Union's Horizon 2020 Research and Innovation Program [101013425]; ELLIIT

We propose a novel resource efficient analog over-the-air (OTA) computation framework to address the demanding requirements of the uplink (UL) fronthaul between the access points (APs) and the central processing unit (CPU) in cell-free massive multiple-input multiple-output (MIMO) systems. We discuss the drawbacks of the wired and wireless fronthaul solutions, and show that our proposed mechanism is efficient and scalable as the number of APs increases. We present the transmit precoding and two-phase power assignment strategies at the APs to coherently combine the signals OTA in a spectrally efficient manner. We derive the statistics of the APs' locally available signals which enable us to to obtain the analytical expressions for the Bayesian and classical estimators of the OTA combined signals. We empirically evaluate the normalized mean square error (NMSE), symbol error rate (SER), and the coded bit error rate (BER) of our developed solution and benchmark against the state-of-the-art wired fronthaul based system., Part of ISBN 9781728190549QC 20240924

Out-of-system (OoS) interference is a potential limitation for distributed networks that operate in unlicensed spectrum or in a spectrum sharing scenario. The OoS interference differs from the in-system interference in that OoS signals and their associated channels (or even their statistics) are completely unknown. In this letter, we propose a novel distributed algorithm that can mitigate OoS interference in the uplink and suppress the signal transmission in the OoS direction in the downlink. To estimate the OoS interference, each access point (AP), upon receiving an estimate of OoS interference from a previous AP, computes a better estimate of OoS interference by rotate-and-average using Procrustes method and forwards the estimates to the next AP. This process continues until the central processing unit (CPU) receives the final estimate. Our method has comparable performance to that of a fully centralized interference rejection combining algorithm and has much lower fronthaul load requirements., Funding Agencies|REINDEER Project of the European Union's Horizon 2020 Research and Innovation Program [101013425]; ELLIIT

Out-of-system (OoS) interference is a potential limitation for distributed networks that operate in unlicensed spectrum or in a spectrum sharing scenario. The OoS interference differs from the in-system interference in that OoS signals and their associated channels (or even their statistics) are completely unknown. In this letter, we propose a novel distributed algorithm that can mitigate OoS interference in the uplink and suppress the signal transmission in the OoS direction in the downlink. To estimate the OoS interference, each access point (AP), upon receiving an estimate of OoS interference from a previous AP, computes a better estimate of OoS interference by rotate-and-average using Procrustes method and forwards the estimates to the next AP. This process continues until the central processing unit (CPU) receives the final estimate. Our method has comparable performance to that of a fully centralized interference rejection combining algorithm and has much lower fronthaul load requirements., Funding Agencies|REINDEER Project of the European Union's Horizon 2020 Research and Innovation Program [101013425]; ELLIIT

Out-of-system (OoS) interference is a potential limitation for distributed networks that operate in unlicensed spectrum or in a spectrum sharing scenario. The OoS interference differs from the in-system interference in that OoS signals and their associated channels (or even their statistics) are completely unknown. In this letter, we propose a novel distributed algorithm that can mitigate OoS interference in the uplink and suppress the signal transmission in the OoS direction in the downlink. To estimate the OoS interference, each access point (AP), upon receiving an estimate of OoS interference from a previous AP, computes a better estimate of OoS interference by rotate-and-average using Procrustes method and forwards the estimates to the next AP. This process continues until the central processing unit (CPU) receives the final estimate. Our method has comparable performance to that of a fully centralized interference rejection combining algorithm and has much lower fronthaul load requirements., Funding Agencies|REINDEER Project of the European Union's Horizon 2020 Research and Innovation Program [101013425]; ELLIIT

Out-of-system (OoS) interference is a potential limitation for distributed networks that operate in unlicensed spectrum or in a spectrum sharing scenario. The OoS interference differs from the in-system interference in that OoS signals and their associated channels (or even their statistics) are completely unknown. In this paper, we propose a novel distributed algorithm that can mitigate OoS interference in the uplink and suppress the signal transmission in the OoS direction in the downlink. To estimate the OoS interference, each access point (AP), upon receiving an estimate of OoS interference from a previous AP, computes a better estimate of OoS interference by rotate-and-average using Procrustes method and forwards the estimates to the next AP. This process continues until the central processing unit (CPU) receives the final estimate. Our method has comparable performance to that of a fully centralized interference rejection combining algorithm and has much lower fronthaul load requirements., Comment: 5 pages, 2 figures, to be published in IEEE Wireless Communications Letters

The door manufacturing industry still heavily relies on manual technology for its production and quality assurance systems, which poses certain challenges. However, in recent years, the industry has witnessed a growing demand for personalized products, leading to a need for more adaptable production methods and shorter product life cycles. Unfortunately, this reliance on manual technologies has resulted in increased errors and inaccuracies. Moreover, manual technology requires significant time and effort investment, which reduces production efficiency and product quality. To address these issues, the purpose of this thesis is to address the issue of inefficiency at a door manufacturing company by examining its existing production systems and quality assurance system. The thesis aims to provide recommendations for improvement by exploring the integration of automated tracing and tracking technology. Furthermore, it would result in recommendations for feasible methods that may be used in Swedish production systems, as well as further study fields.

The door manufacturing industry still heavily relies on manual technology for its production and quality assurance systems, which poses certain challenges. However, in recent years, the industry has witnessed a growing demand for personalized products, leading to a need for more adaptable production methods and shorter product life cycles. Unfortunately, this reliance on manual technologies has resulted in increased errors and inaccuracies. Moreover, manual technology requires significant time and effort investment, which reduces production efficiency and product quality. To address these issues, the purpose of this thesis is to address the issue of inefficiency at a door manufacturing company by examining its existing production systems and quality assurance system. The thesis aims to provide recommendations for improvement by exploring the integration of automated tracing and tracking technology. Furthermore, it would result in recommendations for feasible methods that may be used in Swedish production systems, as well as further study fields.

We propose a novel resource efficient analog over-the-air (OTA) computation framework to address the demanding requirements of the uplink (UL) fronthaul between the access points (APs) and the central processing unit (CPU) in cell-free massive multiple-input multiple-output (MIMO) systems. We discuss the drawbacks of the wired and wireless fronthaul solutions, and show that our proposed mechanism is efficient and scalable as the number of APs increases. We present the transmit precoding and two-phase power assignment strategies at the APs to coherently combine the signals OTA in a spectrally efficient manner. We derive the statistics of the APs locally available signals which enable us to to obtain the analytical expressions for the Bayesian and classical estimators of the OTA combined signals. We empirically evaluate the normalized mean square error (NMSE), symbol error rate (SER), and the coded bit error rate (BER) of our developed solution and benchmark against the state-of-the-art wired fronthaul based system, Comment: 6 pages, 4 figures, Submitted to IEEE International Conference on Communications (ICC), 2024

Cell-free massive multiple-input-multiple-output (CF-mMIMO) is a next-generation wireless access technology that offers superior coverage and spectral efficiency compared to conventional MIMO. With many future applications in unlicensed spectrum bands, networks will likely experience and may even be limited by out-of-system (OoS) interference. The OoS interference differs from the in-system interference from other serving users in that for OoS interference, the associated pilot signals are unknown or non-existent, which makes estimation of the OoS interferer channel difficult. In this paper, we propose a novel sequential algorithm for the suppression of OoS interference for uplink CF-mMIMO with a stripe (daisy-chain) topology. The proposed method has comparable performance to that of a fully centralized interference rejection combining algorithm but has substantially less fronthaul load requirements., Comment: 5 pages, 1 figure, Submitted to ICASSP 2023

In this era of rapid wireless technological advancements, wireless connectivity between humans, humans with machines, and machines with machines is gradually becoming an absolute necessity. The initial motivation for wireless connectivity was to enable voice communication between humans over a geo-graphical area. Thanks to cellular communications advancements in the past decade, cellular wireless connectivity has become a global success, starting from 1G to the present generation 5G. However, the needs of humans often evolve with time, and now the world is witnessing an ever-growing demand for the internet with high data rates besides reliable voice communication. Current cellular networks suffer from non-uniform data rates across a cell, i.e., users at the cell center and the cell edges experience significant variations in signal-to-noise ratio, making the cellular technology less reliable to meet the future data demands. Moreover, cellular networks operating as cells, i.e., an access point (AP, the term we would use instead of base station) serving the users within its geographical location, cannot leverage the network’s total capacity without cooperation among APs of the neighboring cells. One potential solution is moving away from the cell to cell-free networks wherein all the APs will serve all the users within the geographical coverage area. Thus, there is a need for a paradigm shift in how cellular networks operate. Towards the goal mentioned above to fully leverage the network capacity, the Cell-Free Massive multiple-input-multiple-output (MIMO) technology is expected to be the next potential technology beyond 5G combining the benefits of Massive MIMO and cell-free distributed architectures. Distributed architectures require distributed signal processing algorithms, and also energy consumption of the network is crucial. Keeping in view the practical ease in deployment, we consider a sequentially connected Cell-Free Massive MIMO network called a “radio strip, I denna tid av snabba trådlösa tekniska framsteg blir trådlös anslutning mellan människor, mellan människor och maskiner och mellan maskiner och maskiner gradvis en absolut nödvändighet. Den ursprungliga motivationen för trådlös anslutning var att möjliggöra röstkommunikation mellan människor över ett stort geografiskt område. Tack vare framsteg inom mobilkommunikation under det senaste decenniet har mobil trådlös anslutning blivit en global framgång, från 1G till den nuvarande generationen 5G. Men människors behov utvecklats med tiden, och nu bevittnar världen, förutom pålitlig röstkommunikation, en ständigt växande efterfrågan på internet med höga datahastigheter. Nuvarande cellulära nätverk lider av olikformiga datahastigheter över cellen, d.v.s. användare i cellcentret och cellkanterna upplever betydande variationer i signal-brusförhållande, vilket gör den cellulära tekniken mindre lämplig för att möta framtida databehov. Dessutom kan cellulära nätverk som fungerar som celler, d.v.s. att varje accesspunkt (AP, termen vi använder istället för basstation) betjänar användarna inom dess geografiska område, inte utnyttja nätverkets totala kapacitet utan samarbete mellan AP:er i de angränsande cellerna. En potentiell lösning är att gå från cellulära till cellfria nätverk där alla basstationer betjänar alla användare inom det geografiska täckningsområdet. Det finns alltså ett behov av ett paradigmskifte i hur cellulära nätverk fungerar. För att fullt ut utnyttja nätverkskapaciteten, förväntas Cell-Free Massive MIMO vara nästa potentiella teknik bortom 5G som kombinerar fördelarna med Massive MIMO och cellfria distribuerade arkitekturer. Distribuerade arkitekturer kräver distribuerade signalbehandlingsalgoritmer, och även energiförbrukningen i nätverket är av stor vikt. Vi studerar sekventiellt anslutna Cell-Free Massive MIMO-nätverk som kallas “radio stripe”, eftersom dessa är enkla att placera ut. I den första delen av avhandlingen fokuserar vi på att utveckla en opti

In this era of rapid wireless technological advancements, wireless connectivity between humans, humans with machines, and machines with machines is gradually becoming an absolute necessity. The initial motivation for wireless connectivity was to enable voice communication between humans over a geo-graphical area. Thanks to cellular communications advancements in the past decade, cellular wireless connectivity has become a global success, starting from 1G to the present generation 5G. However, the needs of humans often evolve with time, and now the world is witnessing an ever-growing demand for the internet with high data rates besides reliable voice communication. Current cellular networks suffer from non-uniform data rates across a cell, i.e., users at the cell center and the cell edges experience significant variations in signal-to-noise ratio, making the cellular technology less reliable to meet the future data demands. Moreover, cellular networks operating as cells, i.e., an access point (AP, the term we would use instead of base station) serving the users within its geographical location, cannot leverage the network’s total capacity without cooperation among APs of the neighboring cells. One potential solution is moving away from the cell to cell-free networks wherein all the APs will serve all the users within the geographical coverage area. Thus, there is a need for a paradigm shift in how cellular networks operate. Towards the goal mentioned above to fully leverage the network capacity, the Cell-Free Massive multiple-input-multiple-output (MIMO) technology is expected to be the next potential technology beyond 5G combining the benefits of Massive MIMO and cell-free distributed architectures. Distributed architectures require distributed signal processing algorithms, and also energy consumption of the network is crucial. Keeping in view the practical ease in deployment, we consider a sequentially connected Cell-Free Massive MIMO network called a “radio strip, I denna tid av snabba trådlösa tekniska framsteg blir trådlös anslutning mellan människor, mellan människor och maskiner och mellan maskiner och maskiner gradvis en absolut nödvändighet. Den ursprungliga motivationen för trådlös anslutning var att möjliggöra röstkommunikation mellan människor över ett stort geografiskt område. Tack vare framsteg inom mobilkommunikation under det senaste decenniet har mobil trådlös anslutning blivit en global framgång, från 1G till den nuvarande generationen 5G. Men människors behov utvecklats med tiden, och nu bevittnar världen, förutom pålitlig röstkommunikation, en ständigt växande efterfrågan på internet med höga datahastigheter. Nuvarande cellulära nätverk lider av olikformiga datahastigheter över cellen, d.v.s. användare i cellcentret och cellkanterna upplever betydande variationer i signal-brusförhållande, vilket gör den cellulära tekniken mindre lämplig för att möta framtida databehov. Dessutom kan cellulära nätverk som fungerar som celler, d.v.s. att varje accesspunkt (AP, termen vi använder istället för basstation) betjänar användarna inom dess geografiska område, inte utnyttja nätverkets totala kapacitet utan samarbete mellan AP:er i de angränsande cellerna. En potentiell lösning är att gå från cellulära till cellfria nätverk där alla basstationer betjänar alla användare inom det geografiska täckningsområdet. Det finns alltså ett behov av ett paradigmskifte i hur cellulära nätverk fungerar. För att fullt ut utnyttja nätverkskapaciteten, förväntas Cell-Free Massive MIMO vara nästa potentiella teknik bortom 5G som kombinerar fördelarna med Massive MIMO och cellfria distribuerade arkitekturer. Distribuerade arkitekturer kräver distribuerade signalbehandlingsalgoritmer, och även energiförbrukningen i nätverket är av stor vikt. Vi studerar sekventiellt anslutna Cell-Free Massive MIMO-nätverk som kallas “radio stripe”, eftersom dessa är enkla att placera ut. I den första delen av avhandlingen fokuserar vi på att utveckla en opti

RadioWeaves network operates a large number ofdistributed antennas using cell-free architecture to provide highdata rates and support a large number of users. Operating thisnetwork in an energy-efficient manner in the limited availablespectrum is crucial. Therefore, we consider energy efficiency(EE) maximization of a RadioWeaves network that shares spectrumwith a collocated primary network in underlay mode.To simplify the problem, we lower bound the non-convex EEobjective function to form a convex problem. We then propose adownlink power allocation policy that maximizes the EE of thesecondary RadioWeaves network subject to power constraint ateach access point and interference constraint at each primaryuser. Our numerical results investigate the secondary system’sperformance in interference, power, and EE constrained regimeswith correlated fading channels. Furthermore, they show that theproposed power allocation scheme performs significantly betterthan the simpler equal power allocation scheme., Funding: REINDEER project of the European Unions Horizon 2020 research and innovation program [101013425]; ELLIIT; KAW

RadioWeaves network operates a large number ofdistributed antennas using cell-free architecture to provide highdata rates and support a large number of users. Operating thisnetwork in an energy-efficient manner in the limited availablespectrum is crucial. Therefore, we consider energy efficiency(EE) maximization of a RadioWeaves network that shares spectrumwith a collocated primary network in underlay mode.To simplify the problem, we lower bound the non-convex EEobjective function to form a convex problem. We then propose adownlink power allocation policy that maximizes the EE of thesecondary RadioWeaves network subject to power constraint ateach access point and interference constraint at each primaryuser. Our numerical results investigate the secondary system’sperformance in interference, power, and EE constrained regimeswith correlated fading channels. Furthermore, they show that theproposed power allocation scheme performs significantly betterthan the simpler equal power allocation scheme., Funding: REINDEER project of the European Unions Horizon 2020 research and innovation program [101013425]; ELLIIT; KAW

In this era of rapid wireless technological advancements, wireless connectivity between humans, humans with machines, and machines with machines is gradually becoming an absolute necessity. The initial motivation for wireless connectivity was to enable voice communication between humans over a geo-graphical area. Thanks to cellular communications advancements in the past decade, cellular wireless connectivity has become a global success, starting from 1G to the present generation 5G. However, the needs of humans often evolve with time, and now the world is witnessing an ever-growing demand for the internet with high data rates besides reliable voice communication. Current cellular networks suffer from non-uniform data rates across a cell, i.e., users at the cell center and the cell edges experience significant variations in signal-to-noise ratio, making the cellular technology less reliable to meet the future data demands. Moreover, cellular networks operating as cells, i.e., an access point (AP, the term we would use instead of base station) serving the users within its geographical location, cannot leverage the network’s total capacity without cooperation among APs of the neighboring cells. One potential solution is moving away from the cell to cell-free networks wherein all the APs will serve all the users within the geographical coverage area. Thus, there is a need for a paradigm shift in how cellular networks operate. Towards the goal mentioned above to fully leverage the network capacity, the Cell-Free Massive multiple-input-multiple-output (MIMO) technology is expected to be the next potential technology beyond 5G combining the benefits of Massive MIMO and cell-free distributed architectures. Distributed architectures require distributed signal processing algorithms, and also energy consumption of the network is crucial. Keeping in view the practical ease in deployment, we consider a sequentially connected Cell-Free Massive MIMO network called a “radio strip, I denna tid av snabba trådlösa tekniska framsteg blir trådlös anslutning mellan människor, mellan människor och maskiner och mellan maskiner och maskiner gradvis en absolut nödvändighet. Den ursprungliga motivationen för trådlös anslutning var att möjliggöra röstkommunikation mellan människor över ett stort geografiskt område. Tack vare framsteg inom mobilkommunikation under det senaste decenniet har mobil trådlös anslutning blivit en global framgång, från 1G till den nuvarande generationen 5G. Men människors behov utvecklats med tiden, och nu bevittnar världen, förutom pålitlig röstkommunikation, en ständigt växande efterfrågan på internet med höga datahastigheter. Nuvarande cellulära nätverk lider av olikformiga datahastigheter över cellen, d.v.s. användare i cellcentret och cellkanterna upplever betydande variationer i signal-brusförhållande, vilket gör den cellulära tekniken mindre lämplig för att möta framtida databehov. Dessutom kan cellulära nätverk som fungerar som celler, d.v.s. att varje accesspunkt (AP, termen vi använder istället för basstation) betjänar användarna inom dess geografiska område, inte utnyttja nätverkets totala kapacitet utan samarbete mellan AP:er i de angränsande cellerna. En potentiell lösning är att gå från cellulära till cellfria nätverk där alla basstationer betjänar alla användare inom det geografiska täckningsområdet. Det finns alltså ett behov av ett paradigmskifte i hur cellulära nätverk fungerar. För att fullt ut utnyttja nätverkskapaciteten, förväntas Cell-Free Massive MIMO vara nästa potentiella teknik bortom 5G som kombinerar fördelarna med Massive MIMO och cellfria distribuerade arkitekturer. Distribuerade arkitekturer kräver distribuerade signalbehandlingsalgoritmer, och även energiförbrukningen i nätverket är av stor vikt. Vi studerar sekventiellt anslutna Cell-Free Massive MIMO-nätverk som kallas “radio stripe”, eftersom dessa är enkla att placera ut. I den första delen av avhandlingen fokuserar vi på att utveckla en opti

RadioWeaves, in which distributed antennas with integrated radio and compute resources serve a large number of users, is envisioned to provide high data rates in next-generation wireless systems. In this paper, we develop a physical layer abstraction model to evaluate the performance of different RadioWeaves deployment scenarios. This model helps speed up system-level simulators of the RadioWeaves and is made up of two blocks. The first block generates a vector of signalto-interference-plus-noise ratios (SINRs) corresponding to each coherence block, and the second block predicts the packet error rate corresponding to the SINRs generated. The vector of SINRs generated depends on different parameters such as the number of users, user locations, antenna configurations, and precoders. We have also considered different antenna gain patterns, such as omni-directional and directional microstrip patch antennas. Our model exploits the benefits of exponential effective SINR mapping (EESM). We study the robustness and accuracy of the EESM for RadioWeaves., Funding Agencies|European Union [101013425]

RadioWeaves network operates a large number of distributed antennas using cell-free architecture to provide high data rates and support a large number of users. Operating this network in an energy-efficient manner in the limited available spectrum is crucial. Therefore, we consider energy efficiency (EE) maximization of a RadioWeaves network that shares spectrum with a collocated primary network in underlay mode. To simplify the problem, we lower bound the non-convex EE objective function to form a convex problem. We then propose a downlink power allocation policy that maximizes the EE of the secondary RadioWeaves network subject to power constraint at each access point and interference constraint at each primary user. Our numerical results investigate the secondary system's performance in interference, power, and EE constrained regimes with correlated fading channels. Furthermore, they show that the proposed power allocation scheme performs significantly better than the simpler equal power allocation scheme., Comment: 6 Pages, 4 figures, ICC 2022

RadioWeaves network operates a large number ofdistributed antennas using cell-free architecture to provide highdata rates and support a large number of users. Operating thisnetwork in an energy-efficient manner in the limited availablespectrum is crucial. Therefore, we consider energy efficiency(EE) maximization of a RadioWeaves network that shares spectrumwith a collocated primary network in underlay mode.To simplify the problem, we lower bound the non-convex EEobjective function to form a convex problem. We then propose adownlink power allocation policy that maximizes the EE of thesecondary RadioWeaves network subject to power constraint ateach access point and interference constraint at each primaryuser. Our numerical results investigate the secondary system’sperformance in interference, power, and EE constrained regimeswith correlated fading channels. Furthermore, they show that theproposed power allocation scheme performs significantly betterthan the simpler equal power allocation scheme., Funding: REINDEER project of the European Unions Horizon 2020 research and innovation program [101013425]; ELLIIT; KAW

RadioWeaves network operates a large number ofdistributed antennas using cell-free architecture to provide highdata rates and support a large number of users. Operating thisnetwork in an energy-efficient manner in the limited availablespectrum is crucial. Therefore, we consider energy efficiency(EE) maximization of a RadioWeaves network that shares spectrumwith a collocated primary network in underlay mode.To simplify the problem, we lower bound the non-convex EEobjective function to form a convex problem. We then propose adownlink power allocation policy that maximizes the EE of thesecondary RadioWeaves network subject to power constraint ateach access point and interference constraint at each primaryuser. Our numerical results investigate the secondary system’sperformance in interference, power, and EE constrained regimeswith correlated fading channels. Furthermore, they show that theproposed power allocation scheme performs significantly betterthan the simpler equal power allocation scheme., Funding: REINDEER project of the European Unions Horizon 2020 research and innovation program [101013425]; ELLIIT; KAW

RadioWeaves network operates a large number ofdistributed antennas using cell-free architecture to provide highdata rates and support a large number of users. Operating thisnetwork in an energy-efficient manner in the limited availablespectrum is crucial. Therefore, we consider energy efficiency(EE) maximization of a RadioWeaves network that shares spectrumwith a collocated primary network in underlay mode.To simplify the problem, we lower bound the non-convex EEobjective function to form a convex problem. We then propose adownlink power allocation policy that maximizes the EE of thesecondary RadioWeaves network subject to power constraint ateach access point and interference constraint at each primaryuser. Our numerical results investigate the secondary system’sperformance in interference, power, and EE constrained regimeswith correlated fading channels. Furthermore, they show that theproposed power allocation scheme performs significantly betterthan the simpler equal power allocation scheme., Funding: REINDEER project of the European Unions Horizon 2020 research and innovation program [101013425]; ELLIIT; KAW

In this era of rapid wireless technological advancements, wireless connectivity between humans, humans with machines, and machines with machines is gradually becoming an absolute necessity. The initial motivation for wireless connectivity was to enable voice communication between humans over a geo-graphical area. Thanks to cellular communications advancements in the past decade, cellular wireless connectivity has become a global success, starting from 1G to the present generation 5G. However, the needs of humans often evolve with time, and now the world is witnessing an ever-growing demand for the internet with high data rates besides reliable voice communication. Current cellular networks suffer from non-uniform data rates across a cell, i.e., users at the cell center and the cell edges experience significant variations in signal-to-noise ratio, making the cellular technology less reliable to meet the future data demands. Moreover, cellular networks operating as cells, i.e., an access point (AP, the term we would use instead of base station) serving the users within its geographical location, cannot leverage the network’s total capacity without cooperation among APs of the neighboring cells. One potential solution is moving away from the cell to cell-free networks wherein all the APs will serve all the users within the geographical coverage area. Thus, there is a need for a paradigm shift in how cellular networks operate. Towards the goal mentioned above to fully leverage the network capacity, the Cell-Free Massive multiple-input-multiple-output (MIMO) technology is expected to be the next potential technology beyond 5G combining the benefits of Massive MIMO and cell-free distributed architectures. Distributed architectures require distributed signal processing algorithms, and also energy consumption of the network is crucial. Keeping in view the practical ease in deployment, we consider a sequentially connected Cell-Free Massive MIMO network called a “radio strip, I denna tid av snabba trådlösa tekniska framsteg blir trådlös anslutning mellan människor, mellan människor och maskiner och mellan maskiner och maskiner gradvis en absolut nödvändighet. Den ursprungliga motivationen för trådlös anslutning var att möjliggöra röstkommunikation mellan människor över ett stort geografiskt område. Tack vare framsteg inom mobilkommunikation under det senaste decenniet har mobil trådlös anslutning blivit en global framgång, från 1G till den nuvarande generationen 5G. Men människors behov utvecklats med tiden, och nu bevittnar världen, förutom pålitlig röstkommunikation, en ständigt växande efterfrågan på internet med höga datahastigheter. Nuvarande cellulära nätverk lider av olikformiga datahastigheter över cellen, d.v.s. användare i cellcentret och cellkanterna upplever betydande variationer i signal-brusförhållande, vilket gör den cellulära tekniken mindre lämplig för att möta framtida databehov. Dessutom kan cellulära nätverk som fungerar som celler, d.v.s. att varje accesspunkt (AP, termen vi använder istället för basstation) betjänar användarna inom dess geografiska område, inte utnyttja nätverkets totala kapacitet utan samarbete mellan AP:er i de angränsande cellerna. En potentiell lösning är att gå från cellulära till cellfria nätverk där alla basstationer betjänar alla användare inom det geografiska täckningsområdet. Det finns alltså ett behov av ett paradigmskifte i hur cellulära nätverk fungerar. För att fullt ut utnyttja nätverkskapaciteten, förväntas Cell-Free Massive MIMO vara nästa potentiella teknik bortom 5G som kombinerar fördelarna med Massive MIMO och cellfria distribuerade arkitekturer. Distribuerade arkitekturer kräver distribuerade signalbehandlingsalgoritmer, och även energiförbrukningen i nätverket är av stor vikt. Vi studerar sekventiellt anslutna Cell-Free Massive MIMO-nätverk som kallas “radio stripe”, eftersom dessa är enkla att placera ut. I den första delen av avhandlingen fokuserar vi på att utveckla en opti

RadioWeaves, in which distributed antennas with integrated radio and compute resources serve a large number of users, is envisioned to provide high data rates in next generation wireless systems. In this paper, we develop a physical layer abstraction model to evaluate the performance of different RadioWeaves deployment scenarios. This model helps speed up system-level simulators of the RadioWeaves and is made up of two blocks. The first block generates a vector of signal-to-interference-plus-noise ratios (SINRs) corresponding to each coherence block, and the second block predicts the packet error rate corresponding to the SINRs generated. The vector of SINRs generated depends on different parameters such as the number of users, user locations, antenna configurations, and precoders. We have also considered different antenna gain patterns, such as omni-directional and directional microstrip patch antennas. Our model exploits the benefits of exponential effective SINR mapping (EESM). We study the robustness and accuracy of the EESM for RadioWeaves., Comment: 6 pages, 7 figures. Accepted for publication in 2022 IEEE 95th Vehicular Technology Conference: VTC2022-Spring

In this era of rapid wireless technological advancements, wireless connectivity between humans, humans with machines, and machines with machines is gradually becoming an absolute necessity. The initial motivation for wireless connectivity was to enable voice communication between humans over a geo-graphical area. Thanks to cellular communications advancements in the past decade, cellular wireless connectivity has become a global success, starting from 1G to the present generation 5G. However, the needs of humans often evolve with time, and now the world is witnessing an ever-growing demand for the internet with high data rates besides reliable voice communication. Current cellular networks suffer from non-uniform data rates across a cell, i.e., users at the cell center and the cell edges experience significant variations in signal-to-noise ratio, making the cellular technology less reliable to meet the future data demands. Moreover, cellular networks operating as cells, i.e., an access point (AP, the term we would use instead of base station) serving the users within its geographical location, cannot leverage the network’s total capacity without cooperation among APs of the neighboring cells. One potential solution is moving away from the cell to cell-free networks wherein all the APs will serve all the users within the geographical coverage area. Thus, there is a need for a paradigm shift in how cellular networks operate. Towards the goal mentioned above to fully leverage the network capacity, the Cell-Free Massive multiple-input-multiple-output (MIMO) technology is expected to be the next potential technology beyond 5G combining the benefits of Massive MIMO and cell-free distributed architectures. Distributed architectures require distributed signal processing algorithms, and also energy consumption of the network is crucial. Keeping in view the practical ease in deployment, we consider a sequentially connected Cell-Free Massive MIMO network called a “radio strip, I denna tid av snabba trådlösa tekniska framsteg blir trådlös anslutning mellan människor, mellan människor och maskiner och mellan maskiner och maskiner gradvis en absolut nödvändighet. Den ursprungliga motivationen för trådlös anslutning var att möjliggöra röstkommunikation mellan människor över ett stort geografiskt område. Tack vare framsteg inom mobilkommunikation under det senaste decenniet har mobil trådlös anslutning blivit en global framgång, från 1G till den nuvarande generationen 5G. Men människors behov utvecklats med tiden, och nu bevittnar världen, förutom pålitlig röstkommunikation, en ständigt växande efterfrågan på internet med höga datahastigheter. Nuvarande cellulära nätverk lider av olikformiga datahastigheter över cellen, d.v.s. användare i cellcentret och cellkanterna upplever betydande variationer i signal-brusförhållande, vilket gör den cellulära tekniken mindre lämplig för att möta framtida databehov. Dessutom kan cellulära nätverk som fungerar som celler, d.v.s. att varje accesspunkt (AP, termen vi använder istället för basstation) betjänar användarna inom dess geografiska område, inte utnyttja nätverkets totala kapacitet utan samarbete mellan AP:er i de angränsande cellerna. En potentiell lösning är att gå från cellulära till cellfria nätverk där alla basstationer betjänar alla användare inom det geografiska täckningsområdet. Det finns alltså ett behov av ett paradigmskifte i hur cellulära nätverk fungerar. För att fullt ut utnyttja nätverkskapaciteten, förväntas Cell-Free Massive MIMO vara nästa potentiella teknik bortom 5G som kombinerar fördelarna med Massive MIMO och cellfria distribuerade arkitekturer. Distribuerade arkitekturer kräver distribuerade signalbehandlingsalgoritmer, och även energiförbrukningen i nätverket är av stor vikt. Vi studerar sekventiellt anslutna Cell-Free Massive MIMO-nätverk som kallas “radio stripe”, eftersom dessa är enkla att placera ut. I den första delen av avhandlingen fokuserar vi på att utveckla en opti

In this era of rapid wireless technological advancements, wireless connectivity between humans, humans with machines, and machines with machines is gradually becoming an absolute necessity. The initial motivation for wireless connectivity was to enable voice communication between humans over a geo-graphical area. Thanks to cellular communications advancements in the past decade, cellular wireless connectivity has become a global success, starting from 1G to the present generation 5G. However, the needs of humans often evolve with time, and now the world is witnessing an ever-growing demand for the internet with high data rates besides reliable voice communication. Current cellular networks suffer from non-uniform data rates across a cell, i.e., users at the cell center and the cell edges experience significant variations in signal-to-noise ratio, making the cellular technology less reliable to meet the future data demands. Moreover, cellular networks operating as cells, i.e., an access point (AP, the term we would use instead of base station) serving the users within its geographical location, cannot leverage the network’s total capacity without cooperation among APs of the neighboring cells. One potential solution is moving away from the cell to cell-free networks wherein all the APs will serve all the users within the geographical coverage area. Thus, there is a need for a paradigm shift in how cellular networks operate. Towards the goal mentioned above to fully leverage the network capacity, the Cell-Free Massive multiple-input-multiple-output (MIMO) technology is expected to be the next potential technology beyond 5G combining the benefits of Massive MIMO and cell-free distributed architectures. Distributed architectures require distributed signal processing algorithms, and also energy consumption of the network is crucial. Keeping in view the practical ease in deployment, we consider a sequentially connected Cell-Free Massive MIMO network called a “radio strip, I denna tid av snabba trådlösa tekniska framsteg blir trådlös anslutning mellan människor, mellan människor och maskiner och mellan maskiner och maskiner gradvis en absolut nödvändighet. Den ursprungliga motivationen för trådlös anslutning var att möjliggöra röstkommunikation mellan människor över ett stort geografiskt område. Tack vare framsteg inom mobilkommunikation under det senaste decenniet har mobil trådlös anslutning blivit en global framgång, från 1G till den nuvarande generationen 5G. Men människors behov utvecklats med tiden, och nu bevittnar världen, förutom pålitlig röstkommunikation, en ständigt växande efterfrågan på internet med höga datahastigheter. Nuvarande cellulära nätverk lider av olikformiga datahastigheter över cellen, d.v.s. användare i cellcentret och cellkanterna upplever betydande variationer i signal-brusförhållande, vilket gör den cellulära tekniken mindre lämplig för att möta framtida databehov. Dessutom kan cellulära nätverk som fungerar som celler, d.v.s. att varje accesspunkt (AP, termen vi använder istället för basstation) betjänar användarna inom dess geografiska område, inte utnyttja nätverkets totala kapacitet utan samarbete mellan AP:er i de angränsande cellerna. En potentiell lösning är att gå från cellulära till cellfria nätverk där alla basstationer betjänar alla användare inom det geografiska täckningsområdet. Det finns alltså ett behov av ett paradigmskifte i hur cellulära nätverk fungerar. För att fullt ut utnyttja nätverkskapaciteten, förväntas Cell-Free Massive MIMO vara nästa potentiella teknik bortom 5G som kombinerar fördelarna med Massive MIMO och cellfria distribuerade arkitekturer. Distribuerade arkitekturer kräver distribuerade signalbehandlingsalgoritmer, och även energiförbrukningen i nätverket är av stor vikt. Vi studerar sekventiellt anslutna Cell-Free Massive MIMO-nätverk som kallas “radio stripe”, eftersom dessa är enkla att placera ut. I den första delen av avhandlingen fokuserar vi på att utveckla en opti

In this era of rapid wireless technological advancements, wireless connectivity between humans, humans with machines, and machines with machines is gradually becoming an absolute necessity. The initial motivation for wireless connectivity was to enable voice communication between humans over a geo-graphical area. Thanks to cellular communications advancements in the past decade, cellular wireless connectivity has become a global success, starting from 1G to the present generation 5G. However, the needs of humans often evolve with time, and now the world is witnessing an ever-growing demand for the internet with high data rates besides reliable voice communication. Current cellular networks suffer from non-uniform data rates across a cell, i.e., users at the cell center and the cell edges experience significant variations in signal-to-noise ratio, making the cellular technology less reliable to meet the future data demands. Moreover, cellular networks operating as cells, i.e., an access point (AP, the term we would use instead of base station) serving the users within its geographical location, cannot leverage the network’s total capacity without cooperation among APs of the neighboring cells. One potential solution is moving away from the cell to cell-free networks wherein all the APs will serve all the users within the geographical coverage area. Thus, there is a need for a paradigm shift in how cellular networks operate. Towards the goal mentioned above to fully leverage the network capacity, the Cell-Free Massive multiple-input-multiple-output (MIMO) technology is expected to be the next potential technology beyond 5G combining the benefits of Massive MIMO and cell-free distributed architectures. Distributed architectures require distributed signal processing algorithms, and also energy consumption of the network is crucial. Keeping in view the practical ease in deployment, we consider a sequentially connected Cell-Free Massive MIMO network called a “radio strip, I denna tid av snabba trådlösa tekniska framsteg blir trådlös anslutning mellan människor, mellan människor och maskiner och mellan maskiner och maskiner gradvis en absolut nödvändighet. Den ursprungliga motivationen för trådlös anslutning var att möjliggöra röstkommunikation mellan människor över ett stort geografiskt område. Tack vare framsteg inom mobilkommunikation under det senaste decenniet har mobil trådlös anslutning blivit en global framgång, från 1G till den nuvarande generationen 5G. Men människors behov utvecklats med tiden, och nu bevittnar världen, förutom pålitlig röstkommunikation, en ständigt växande efterfrågan på internet med höga datahastigheter. Nuvarande cellulära nätverk lider av olikformiga datahastigheter över cellen, d.v.s. användare i cellcentret och cellkanterna upplever betydande variationer i signal-brusförhållande, vilket gör den cellulära tekniken mindre lämplig för att möta framtida databehov. Dessutom kan cellulära nätverk som fungerar som celler, d.v.s. att varje accesspunkt (AP, termen vi använder istället för basstation) betjänar användarna inom dess geografiska område, inte utnyttja nätverkets totala kapacitet utan samarbete mellan AP:er i de angränsande cellerna. En potentiell lösning är att gå från cellulära till cellfria nätverk där alla basstationer betjänar alla användare inom det geografiska täckningsområdet. Det finns alltså ett behov av ett paradigmskifte i hur cellulära nätverk fungerar. För att fullt ut utnyttja nätverkskapaciteten, förväntas Cell-Free Massive MIMO vara nästa potentiella teknik bortom 5G som kombinerar fördelarna med Massive MIMO och cellfria distribuerade arkitekturer. Distribuerade arkitekturer kräver distribuerade signalbehandlingsalgoritmer, och även energiförbrukningen i nätverket är av stor vikt. Vi studerar sekventiellt anslutna Cell-Free Massive MIMO-nätverk som kallas “radio stripe”, eftersom dessa är enkla att placera ut. I den första delen av avhandlingen fokuserar vi på att utveckla en opti

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance., Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission [2019-05068]; Swedish Research Council (VR)Swedish Research Council [642-2013-7607]; ELLIIT; Knut and Alice Wallenberg (KAW) FoundationKnut & Alice Wallenberg Foundation

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance., Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission [2019-05068]; Swedish Research Council (VR)Swedish Research Council [642-2013-7607]; ELLIIT; Knut and Alice Wallenberg (KAW) FoundationKnut & Alice Wallenberg Foundation

This paper presents a novel strategy to decentralize the soft detection procedure in an uplink cell-free massive multiple-input-multiple-output network. We propose efficient approaches to compute the a posteriori probability-per-bit, exactly or approximately, when having a sequential fronthaul. More precisely, each access point (AP) in the network computes partial sufficient statistics locally, fuses it with received partial statistics from another AP, and then forward the result to the next AP. Once the sufficient statistics reach the central processing unit, it performs the soft demodulation by computing the log-likelihood ratio (LLR) per bit, and then a channel decoding algorithm (e.g., a Turbo decoder) is utilized to decode the bits. We derive the distributed computation of LLR analytically., QC 20220425Part of proceedings: ISBN 978-9-0827-9706-0

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance., QC 20211206

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance., Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission [2019-05068]; Swedish Research Council (VR)Swedish Research Council [642-2013-7607]; ELLIIT; Knut and Alice Wallenberg (KAW) FoundationKnut & Alice Wallenberg Foundation

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance., Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission [2019-05068]; Swedish Research Council (VR)Swedish Research Council [642-2013-7607]; ELLIIT; Knut and Alice Wallenberg (KAW) FoundationKnut & Alice Wallenberg Foundation

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance., Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission [2019-05068]; Swedish Research Council (VR)Swedish Research Council [642-2013-7607]; ELLIIT; Knut and Alice Wallenberg (KAW) FoundationKnut & Alice Wallenberg Foundation

This paper presents a novel strategy to decentralize the soft detection procedure in an uplink cell-free massive multiple-input-multiple-output network. We propose efficient approaches to compute the a posteriori probability-per-bit, exactly or approximately when having a sequential fronthaul. More precisely, each access point (AP) in the network computes partial sufficient statistics locally, fuses it with received partial statistics from another AP, and then forwards the result to the next AP. Once the sufficient statistics reach the central processing unit, it performs the soft demodulation by computing the log-likelihood ratio (LLR) per bit, and then a channel decoding algorithm (e.g., a Turbo decoder) is utilized to decode the bits. We derive the distributed computation of LLR analytically., Comment: 5 pages, 2 figures, accepted in 2021 29th European Signal Processing Conference (EUSIPCO)

This paper presents a novel strategy to decentralize the soft detection procedure in an uplink cell-free massive multiple-input-multiple-output network. We propose efficient approaches to compute the a posteriori probability-per-bit, exactly or approximately, when having a sequential fronthaul. More precisely, each access point (AP) in the network computes partial sufficient statistics locally, fuses it with received partial statistics from another AP, and then forward the result to the next AP. Once the sufficient statistics reach the central processing unit, it performs the soft demodulation by computing the log-likelihood ratio (LLR) per bit, and then a channel decoding algorithm (e.g., a Turbo decoder) is utilized to decode the bits. We derive the distributed computation of LLR analytically., Funding: Swedish Research Council (VR)Swedish Research Council; ELLIIT

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance., Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission [2019-05068]; Swedish Research Council (VR)Swedish Research Council [642-2013-7607]; ELLIIT; Knut and Alice Wallenberg (KAW) FoundationKnut & Alice Wallenberg Foundation

Climate change is recognized as one of the greatest challenges of 21st century. This study investigated climate and hydrological regimes of the high-altitude Indus basin for the historical period and extreme scenarios of future climate during 21st century. Improved datasets of precipitation and temperature were developed and forced to a fully-distributed physically-based energy-balance Variable Infiltration Capacity (VIC) hydrological model to simulate the water balance at regional and sub-basin scale. Relative to historical baseline, the results revealed highly contrasting signals of climate and hydrological regime changes. Against an increase of 0.6 °C during the last 40 years, the median annual air temperature is projected to increase further between 0.8 and 5.7 °C by the end of 21st century. Similarly, a decline of 11.9% in annual precipitation is recorded, but future projections are highly conflicting and spatially variable. The Karakoram region is anticipated to receive more precipitation, while SW-Hindukush and parts of W-Himalayan region may experience decline in precipitation. The Model for Interdisciplinary Research On Climate version-5 (MIROC5) generally shows increases, while Max Planck Institute Earth System Model at base resolution (MPI-ESM-LR) indicates decreases in precipitation and river inflows under three Representative Concentration Pathways (RCPs) of 2.6, 4.5 and 8.5. Indus-Tarbela inflows are more likely to increase compared to Kabul, Jhelum and Chenab river inflows. Substantial increase in the magnitudes of peak flows and one-month earlier attainment is projected for all river gauges. High flows are anticipated to increase under most scenarios, while low flows may decrease for MPI-ESM-LR in Jhelum, Chenab and Kabul river basins. Hence, hydrological extremes are likely to be intensified. Critical modifications in the strategies and action plans for hydropower generation, construction and operation of storage reservoirs, irrigation withdrawals

The high-altitude Indus basin is one of the most complex and inadequately explored mountain terrains in the World, where reliable observations of precipitation are highly lacking. Therefore, spatially distributed precipitation products developed at global/regional scale are often used in several scientific disciplines. However, large uncertainties in precipitation estimates of such precipitation data sets often lead to suboptimal outcomes. In this study, performance of 27 widely used gridded precipitation products belonging to three different categories of gauge-based, reanalysis and merged products is evaluated with respect to high-quality reference climatologies of mean monthly precipitation. Widely used statistical measures and quantitative analysis techniques are used to analyse the spatial patterns and quantitative distribution of mean monthly, seasonal and annual precipitation at sub-regional scale. Mean annual precipitation estimates of the gridded data sets are cross validated with the corresponding adjusted streamflows using Turc-Budyko non-dimensional analysis. Results reveal poor to moderately good performance of the gridded data sets. Marked differences in spatiotemporal and quantitative distribution of precipitation are found among the data sets. All data sets are consistent in their patterns showing negative or dry bias in wet areas and positive or wet bias in dry areas, although considerable differences in the magnitudes of the biases are noticed at sub-regional scale. None of the data sets is equally good for all sub-regions due to very high spatiotemporal variability in their performance at sub-regional scale. Gauge-based and merged products performed better in dry regions and during monsoon season, while reanalysis products provided better estimates in wet areas and during winter months. GPCC V8, ERA5 and MSWEP2.2 are found better than their counter-grouped data sets. Overall, ERA5 is found most acceptable for all sub-regions, particularly at highe

Technical and Vocational Education and Training (TVET) is the future of tomorrow's workforce in the era of the Industrial Revolution 4.0. The ability of TVET institutions to prepare their graduates for future employment is paramount. Graduates who are adequately prepared to adapt to the workplace scenario is very much sought after. Job descriptions may differ slightly from their education and training, but strong fundamentals greatly improve a TVET graduate's employability. Part of this employability is the ability to commit to safety and health processes and procedures in the workplace. A survey using an instrument with a meritorious confirmatory factorial analysis was conducted. The items of the survey try to obtain feedback on awareness among the TVET population. The survey was disseminated using an online survey form. Feedbacks were analyzed using statistical packages to determine the respondents' replies. Utilizing the Pareto analysis, significant items based on respondents' feedback were identified. From the analysis, two hypotheses were formulated, which were then tested using independent samples test to obtain the significant value of the test. From the Pareto analysis, only 40% of the respondents were knowledgeable to assist if there were any safety and health concerns. Further analysis proved that gender did not influence having the knowledge to assist in any safety and health concerns. Additionally, having an industrial experience did not influence having the knowledge to assist in any safety and health concerns. The study on the awareness of occupational health and safety in TVET institutions is still a scarce research topic. By taking into consideration this research study, practical implications focusing on various stakeholders of educational systems; accreditation agencies and government bodies, TVET institutions, and civil society can be further explored and developed. TVET institutions play a pivotal role in providing a competent workforce to indust

Technical and Vocational Education and Training (TVET) is the future of tomorrow's workforce in the era of the Industrial Revolution 4.0. The ability of TVET institutions to prepare their graduates for future employment is paramount. Graduates who are adequately prepared to adapt to the workplace scenario is very much sought after. Job descriptions may differ slightly from their education and training, but strong fundamentals greatly improve a TVET graduate's employability. Part of this employability is the ability to commit to safety and health processes and procedures in the workplace. A survey using an instrument with a meritorious confirmatory factorial analysis was conducted. The items of the survey try to obtain feedback on awareness among the TVET population. The survey was disseminated using an online survey form. Feedbacks were analyzed using statistical packages to determine the respondents' replies. Utilizing the Pareto analysis, significant items based on respondents' feedback were identified. From the analysis, two hypotheses were formulated, which were then tested using independent samples test to obtain the significant value of the test. From the Pareto analysis, only 40% of the respondents were knowledgeable to assist if there were any safety and health concerns. Further analysis proved that gender did not influence having the knowledge to assist in any safety and health concerns. Additionally, having an industrial experience did not influence having the knowledge to assist in any safety and health concerns. The study on the awareness of occupational health and safety in TVET institutions is still a scarce research topic. By taking into consideration this research study, practical implications focusing on various stakeholders of educational systems; accreditation agencies and government bodies, TVET institutions, and civil society can be further explored and developed. TVET institutions play a pivotal role in providing a competent workforce to indust

Cell-free Massive MIMO (mMIMO) is envisaged to be a next-generation technology beyond 5G with its high spectral efficiency and superior spatial diversity as compared to that of conventional MIMO technology. The main principle is that many distributed access points (APs) cooperate to simultaneously serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture. We propose a novel sequential processing algorithm with normalized linear minimum mean square error (N-LMMSE) combining at every AP. This algorithm enables interference suppression in cell-free mMIMO while keeping the cost and front-haul requirements low. The spectral efficiency of the proposed algorithm is computed and analyzed. We conclude that it provides an attractive trade-off between low front-haul requirements and high spectral efficiency., QC 20220616Part of proceedings: ISBN 978-1-7281-7440-2

The high-altitude Indus basin is one of the most complex and underexplored mountain regions in the World. Scarcity and directional biases of the observed precipitation coupled with measurement errors, high orographic influences and effects of multiple weather systems have prevented a comprehensive and reliable assessment of precipitation distribution in this region. Quantitative and spatiotemporal distributions of precipitation estimated by the previous studies and global/regional scale gridded datasets for this region are highly contrasting and extremely uncertain. Consequently, the studies using these estimates often lead to suboptimal and misleading outcomes regarding hydrometeorological assessments.This PhD research study integrated precipitation observations from multiple sources with the indirect estimates at the accumulation zones of major glaciers, adjusted these observations for measurement errors and derived spatially distributed fields of mean monthly precipitation using the standard and well-recognized techniques. The resultant reference estimates of precipitation distribution are cross-validated by the corresponding observed river inflows, which were adjusted for contribution of net mass balance. The reference climatologies of mean monthly maximum and minimum temperature are derived through elevation and latitude dependent lapse rates at sub-regional scale. Performance of 27 widely used gridded precipitation products is evaluated against the observational based reference dataset at sub-regional scale. The best performing gridded dataset is statistically downscaled and bias-corrected with respect to the reference datasets to develop long-term historical dataset of precipitation and temperature. Similarly, precipitation estimates of 75 CMIP5 GCM outputs for the historical period are evaluated against the bias-corrected historical dataset. Top 24 ranked GCM outputs are further analysed based on the changes in their climatic means between 1971–2000 and 2071

Cell-free Massive MIMO (mMIMO) is envisaged to be a next-generation technology beyond 5G with its high spectral efficiency and superior spatial diversity as compared to that of conventional MIMO technology. The main principle is that many distributed access points (APs) cooperate to simultaneously serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture. We propose a novel sequential processing algorithm with normalized linear minimum mean square error (N-LMMSE) combining at every. This algorithm enables interference suppression in cell-free MMO while keeping the cost and front-haul requirements low. The spectral efficiency of the proposed algorithm is computed and analyzed. We conclude that it provides an attractive trade-off between low front-haul requirements and high spectral efficiency., Comment: 6 pages, 3 figures

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can greatly reduce the fronthaul signaling, without compromising the communication performance.

Cell-free Massive MIMO (mMIMO) is envisaged to be a next-generation technology beyond 5G with its high spectral efficiency and superior spatial diversity as compared to that of conventional MIMO technology. The main principle is that many distributed access points (APs) cooperate to simultaneously serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture. We propose a novel sequential processing algorithm with normalized linear minimum mean square error (N-LMMSE) combining at every AP. This algorithm enables interference suppression in cell-free mMIMO while keeping the cost and front-haul requirements low. The spectral efficiency of the proposed algorithm is computed and analyzed. We conclude that it provides an attractive trade-off between low front-haul requirements and high spectral efficiency., Funding Agencies|Swedish Research Council (VR)Swedish Research Council; ELLIIT

Devastating floods adversely affect human life and infrastructure. Various regions of the Hindukush-Karakoram-Himalayas receive intense monsoon rainfall, which, together with snow and glacier melt, produce intense floods. The Kabul river basin originates from the Hindukush Mountains and is frequently hit by such floods. We analyses flood frequency and intensity in Kabul basin for a contemporary period (1981-2015) and two future periods (i.e., 2031-2050 and 2081-2100) using the RCP4.5 and RCP8.5 scenarios based on four bias-corrected downscaled climate models (INM-CM4, IPSL-CM5A, EC-EARTH, and MIROC5). Future floods are modelled with the SWAT hydrological model. The model results suggest an increasing trend due to an increasing precipitation and higher temperatures (based on all climate models except INM-CM4), which accelerates snow and glacier-melt. All of the scenario results show that the current flow with a 1 in 50 year return period is likely to occur more frequently (i.e., 1 in every 9-10 years and 2-3 years, respectively) during the near and far future periods. Such increases in intensity and frequency are likely to adversely affect downstream population and infrastructures. This, therefore, urges for appropriate early precautionary mitigation measures. This study can assist water managers and policy makers in their preparation to adequately plan for and manage flood protection. Its findings are also relevant for other basins in the Hindukush-Karakoram-Himalayas region.

Precipitation in the high-altitude Indus basin governs its renewable water resources affecting water, energy and food securities. However, reliable estimates of precipitation climatology and associated hydrological implications are seriously constrained by the quality of observed data. As such, quantitative and spatio-temporal distributions of precipitation estimated by previous studies in the study area are highly contrasting and uncertain. Generally, scarcity and biased distribution of observed data at the higher altitudes and measurement errors in precipitation observations are the primary causes of such uncertainties. In this study, we integrated precipitation data of 307 observatories with the net snow accumulations estimated through mass balance studies at 21 major glacier zones. Precipitation observations are adjusted for measurement errors using the guidelines and standard methods developed under the WMO's international precipitation measurement intercomparisons, while net snow accumulations are adjusted for ablation losses using standard ablation gradients. The results showed more significant increases in precipitation of individual stations located at higher altitudes during winter months, which are consistent with previous studies. Spatial interpolation of unadjusted precipitation observations and net snow accumulations at monthly scale indicated significant improvements in the quantitative and spatio-temporal distribution of precipitation over the unadjusted case and previous studies. Adjustment of river flows revealed only a marginal contribution of net glacier mass balance to river flows. The adjusted precipitation estimates are more consistent with the corresponding adjusted river flows. The study recognized that the higher river flows than the corresponding precipitation estimates by the previous studies are mainly due to underestimated precipitation. The results can be useful for water balance studies and bias correction of gridded precipitation pro

Suaeda maritima is a halophyte that has been evolutionary adapted to cope with saline and heavy metal conditions. The aim of the present study was to examine the biochemical response of Suaeda maritima against phytoextracting heavy metals and salts from paper mill effluent. Suaeda maritima  seedlings have been grown for 120 days with an irrigation solution of 250 ml of 75% raw paper mill effluent after four drenching. Analysis of biochemical parameters revealed that maximum synthesis of chlorophyll, protein, phenol, proline and glycinebetaine may be involved in their ability to cope with heavy metal and salt stress. The present study confirms that the accumulation and increase of biochemical constituents can be considered as an efficient ROS scavenger and also maintain cellular homeostasis and metabolic functions in photosynthetically active leaves in Suaeda maritima, during phytoextraction studies. Keywords: phytoextraction, paper mill effluent, Suaeda maritima, biochemical, heavy metal and salts

Suaeda maritima is a halophyte that has been evolutionary adapted to cope with saline and heavy metal conditions. The aim of the present study was to examine the biochemical response of Suaeda maritima against phytoextracting heavy metals and salts from paper mill effluent. Suaeda maritima  seedlings have been grown for 120 days with an irrigation solution of 250 ml of 75% raw paper mill effluent after four drenching. Analysis of biochemical parameters revealed that maximum synthesis of chlorophyll, protein, phenol, proline and glycinebetaine may be involved in their ability to cope with heavy metal and salt stress. The present study confirms that the accumulation and increase of biochemical constituents can be considered as an efficient ROS scavenger and also maintain cellular homeostasis and metabolic functions in photosynthetically active leaves in Suaeda maritima, during phytoextraction studies. Keywords: phytoextraction, paper mill effluent, Suaeda maritima, biochemical, heavy metal and salts

Scarcity of in-situ observations coupled with high orographic influences has prevented a comprehensive assessment of precipitation distribution in the high-altitude catchments of Indus basin. Available data are generally fragmented and scattered with different organizations and mostly cover the valleys. Here, we combine most of the available station data with the indirect precipitation estimates at the accumulation zones of major glaciers to analyse altitudinal dependency of precipitation in the high-altitude Indus basin. The available observations signified the importance of orography in each sub-hydrological basin but could not infer an accurate distribution of precipitation with altitude. We used Kriging with External Drift (KED) interpolation scheme with elevation as a predictor to appraise spatiotemporal distribution of mean monthly, seasonal and annual precipitation for the period of 1998-2012. The KED-based annual precipitation estimates are verified by the corresponding basin-wide observed specific runoffs, which show good agreement. In contrast to earlier studies, our estimates reveal substantially higher precipitation in most of the sub-basins indicating two distinct rainfall maxima; 1st along southern and lower most slopes of Chenab, Jhelum, Indus main and Swat basins, and 2nd around north-west corner of Shyok basin in the central Karakoram. The study demonstrated that the selected gridded precipitation products covering this region are prone to significant errors. In terms of quantitative estimates, ERA-Interim is relatively close to the observations followed by WFDEI and TRMM, while APHRODITE gives highly underestimated precipitation estimates in the study area. Basin-wide seasonal and annual correction factors introduced for each gridded dataset can be useful for lumped hydrological modelling studies, while the estimated precipitation distribution can serve as a basis for bias correction of any gridded precipitation products for the study area.

This paper proposes a new approach of providing ancillary services to AC and DC grids from offshore wind power plants (OWPPs), connected through multi-terminal HVDC network. A coordinated control scheme where OWPP’s AC grid frequency modulated according to DC grid voltage variations is used to detect and provide the ancillary service requirements of both AC and DC grids, is proposed in this paper. In particular, control strategies for onshore frequency control, fault ridethrough support in the onshore grid, and DC grid voltage control are considered. The proposed control scheme involves only local measurements and therefore avoids the need of communication infrastructure otherwise required for communication based control, and thus increases the reliability of the control system. The effectiveness of the proposed control scheme is demonstrated on a MTDC connected wind power system developed in DIgSILIENT PowerFactory.