Search

IEEE Indonesia Section;National Research and Innovation Agency (BRIN);Research Center for Electronics, 2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2023 -- 15 November 2023 through 16 November 2023 -- 195877, Integration of radar and communication systems on the same platform reveals the interference problems of these systems, as well as the installation problems on small scale platforms. Joint radar and communication systems have significant potential in solving these problems, as they reduce congestion both in the spectrum and on the platform. In this article, the integration of communication symbols into the radar signal is studied and a new technique for mono-static pulsed radar receiver is proposed to obtain a better range and velocity estimation performance. The effects of the integration methods on the performance of the radar receiver are analysed. © 2023 IEEE.

IEEE Indonesia Section;National Research and Innovation Agency (BRIN);Research Center for Electronics, 2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2023 -- 15 November 2023 through 16 November 2023 -- 195877, Integration of radar and communication systems on the same platform reveals the interference problems of these systems, as well as the installation problems on small scale platforms. Joint radar and communication systems have significant potential in solving these problems, as they reduce congestion both in the spectrum and on the platform. In this article, the integration of communication symbols into the radar signal is studied and a new technique for mono-static pulsed radar receiver is proposed to obtain a better range and velocity estimation performance. The effects of the integration methods on the performance of the radar receiver are analysed. © 2023 IEEE.

Secure and agile wireless technologies enable spectrum assignment through Dynamic Spectrum Access (DSA), a technique for improving the efficiency of spectrum usage. DSA has attracted much attention, with many national administrations keen to promote its development and uptake, but little research has been undertaken to date to simulate, analyse and demonstrate the potential economic benefit of investment in shared networks in general, and DSA in particular, by Mobile Network Operators (MNOs). This study addresses two distinct areas of shared spectrum and DSA economics: the simulation and optimisation of potential shared spectrum usage opportunities, and the modelling of economic benefits with an associated cost-benefit analysis. Both of these aspects need to be considered in order that stakeholders can decide whether to invest or not. This research study focuses on an assessment of the potential economic benefits from an MNO’s perspective. The optimisation of spectrum use is considered from a bit rate perspective, and the study illustrates that stakeholders should seek to increase C-Band carrier aggregation bandwidths from the present 300 MHz to 800 MHz. Monte Carlo simulations have been undertaken relating to the 3.8 – 4.2 GHz band in a target market, Exclusion Zones (EZs – where a shared network cannot be deployed without creating excessive interference to incumbent users) plotted, and the excluded population estimated. When enabling spectrum sharing, with or without DSA, the study has found that there is a need to maximise the allowable Secondary User (SU) bandwidths in order to optimise the spectrum sharing opportunity. It has also shown that, due to the sensitivity of results to variations in Primary User (PU) antenna characteristics, extant PU antenna data should be used when assessing the impact of EZs on the spectrum sharing opportunity. It is shown that one of the biggest positive impacts on the size of potential economic benefit to MNOs can be

In 2015, Federal Communications Commission (FCC) enabled shared commercial use of the 3.550-3.700 GHz band. A framework was developed to enable this spectrum-sharing capa- bility which included an automated frequency coordinator called Spectrum Access System (SAS). This work extends the open source SAS based on the aforementioned FCC SAS framework developed by researchers at Virginia Tech Wireless group, with real-time envi- ronment sensing capability along with intelligent incumbent detection using Software-defined Radios (SDRs) and a real-time graphical user interface. This extended version is called the OpenSAS. Furthermore, the SAS client and OpenSAS are extended to be compliant with the Wireless Innovation Forum (WINNF) specifications by testing the SAS-CBRS Base Station Device (CBSD) interface with the Google SAS Test Environment. The Environment Sensing Capability (ESC) functionality is evaluated and tested in our xG Testbed to verify its ability to detect the presence of users in the CBRS band. An ML-based feedforward neural net- work model is employed and trained using simulated radar waveforms as incumbent signals and captured 5G New Radio (NR) signals as a non-incumbent signal to predict whether the detected user is a radar incumbent or an unknown user. If the presence of incumbent radar is detected with an 85% or above certainty, incumbent protection is activated, terminating CBSD grants causing damaging interference to the detected incumbent. A 5G NR signal is used as a non-incumbent user and added to the training dataset to better the ability of the model to reject non-incumbent signals. The model achieves a maximum validation accuracy of 95.83% for signals in the 40-50 dB Signal-to-Noise Ratio (SNR) range. It achieves an 85.35% accuracy for Over the air (OTA) real-time tests. The non-incumbent 5G NR signal rejection accuracy is 91.30% for a calculated SNR range of 10-20 dB. In conclusion, this work advances state of the art in spectrum sharing systems

The mobile edge computing (MEC) technology can simultaneously provide high-speed computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) networks. Nevertheless, due to the open feature of the wireless offloading channels and the high mobility of the vehicles, the security and stability of the offloading process would be seriously degraded. In this paper, by utilizing the physical layer security (PLS) technique and spectrum sharing architecture, we propose a deep reinforcement learning based joint secure offloading and resource allocation (SORA) scheme to improve the secrecy performance and resource efficiency of the multi-user VEC networks, where the VU offloading links share the frequency spectrum preoccupied with the vehicle-to-vehicle (V2V) communication links. We use Wyner's wiretap coding scheme to obtain the achievable secrecy rate and guarantee that confidential information cannot be decoded by multiple mobile eavesdroppers. We aim at minimizing the system processing delay while securing the wireless offloading process, by jointly optimizing the transmit power, the frequency spectrum selection and the computation resource allocation. We formulate the optimization problem as a multi-agent collaborative optimal decision problem and solve it with a double deep Q-learning algorithm. Besides, we set a punishment mechanism for the rate degradation to guarantee the communication quality of each V2V link. Simulation results demonstrate that multiple VU agents adopting the SORA scheme can rapidly adapt to the highly dynamic VEC networks and cooperate to improve the system delay performance while increasing the secrecy probability., QC 20230707

The upcoming sixth generation (6G) mobile communication system is expected to operate across a wide range of spectrum that includes not only the bands used by previous generations but also higher frequency bands such as millimeter wave (mmWave), which are currently assigned to fifth generation (5G) networks, terahertz (THz), and optical spectrum. By utilizing a broader range of frequencies, it will be possible to support 6G applications with faster data rates, higher capacity, and lower latency. However, the higher frequency bands pose unique challenges such as higher path loss, absorption loss, and engineering difficulties for antennas and radio frequency (RF) circuitry design, which require advanced technologies and innovative solutions. Given that the spectrum is a scarce resource, efficient management is crucial to ensure the most effective exploitation of frequency bands. The spectrum management has evolved over the years, with different approaches being used to assign and utilize frequency bands. In this paper, we provide a review of spectrum management approaches, including their use in awarding 5G spectrum, and explore their expected use in 6G. We then offer a brief overview of spectrum sharing and its role in enabling the efficient use of spectrum resources. The regulations, standardization, features, limitations, and potential use cases of higher frequency bands such as, mmWave, THz, and visible light (VL) are analyzed to provide a comprehensive understanding of the spectrum options available for the upcoming 6G technology.

The integrated terrestrial satellite networks (ITSNs) have been deemed as a promising solution to ubiquitous Internet access anytime and anywhere. In this paper, we investigate the spectrum sharing problem in ITSN, in particular focusing on the downlink transmission of the satellite network, which adopts the framing structure for the satellite users (SUs). We model the interference from both terrestrial downlink and uplink transmissions to SUs according to the beamforming techniques. For the terrestrial downlink transmission, we assume that terrestrial users (TUs) are served cooperatively by multiple small base stations (SBSs) via joint beamforming, while the virtual multiple access channel (VMAC) scheme is adopted for the terrestrial uplink transmission. We propose the optimization framework by jointly considering the terrestrial beamformer design and satellite user scheduling to maximize the sum rate of all users. The optimization problems are decomposed into three sub-problems: satellite user scheduling, terrestrial beamformer design, and time slot allocation, which are solved by deep clustering, second-order cone programming (SOCP) (or fractional programming (FP)), and linear programming, respectively. Then, an alternating iterative algorithm is designed to obtain the optimal solution. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm in multiple cases.

This paper proposes a radio-protected area (RPA) estimation model that achieves full protection and avoids overprotection by adding an appropriate margin to the extended-Hata (EH) model, for realizing efficient spectrum sharing in the V-High-band. This additional margin, called location gain, is a location-dependent value that accounts for knife-edge losses calculated from topographic information. This study experimentally obtains the location gain by conducting VHF-band-based propagation experiments in urban and suburban areas. Subsequently, we developed an estimation formula for the location gain using topographic data, which include correction terms based on the experimental data. As a result, RPA can be estimated using only the topographic data, excluding the need for propagation experiments. The proposed model resolved the problems of the EH model (incomplete protection) and free-space (FS) model (overprotection). In urban and suburban areas, the proposed model achieved full protection and over 99.7% reduction in the RPA size of the FS model when the threshold of the received power for determining the RPA was set to –80 dBm.

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 paper, we consider Internet of Things (IoT) based mobile edge computing (MEC) system. IoT devices are controlled by access points (APs), which do not have access to any licensed spectrum. This puts limitations on IoT devices’ offloading capability and hence effectively reduces the number of computed bits. Under such scenario, we consider spectrum sharing, where IoT networks get access to licensed spectrum by helping a primary network (owns licensed spectrum) in cooperative relaying. We aim to maximize sum of the primary network’s communication rate and IoT networks’ total number of computed bits by jointly optimizing relay selection, licensed spectrum allocation, local computation, and offloading sequence selection. Moreover, we consider important constraints, e.g., the guaranteed rate for the primary network, IoT devices’ available energy, and available licensed spectrum resource blocks (RBs). We observe that the optimization problem is combinatoric in nature, which becomes more complicated when IoT devices’ scheduling order comes into the formulation. From our analysis, we devise an optimal and computationally efficient algorithm. In the result section, we compare with relevant benchmark systems and show the efficacy of our proposed model. Moreover, we also show how IoT and primary networks benefit from spectrum sharing.

Wireless communication research has recently expanded to address the use of 5G in enterprise application, which has led to the introduction of local private industrial networks. At the same time, the use of wireless communication services offshore has increased both in improving the productivity of the incumbent oil and gas segment, and particularly in enabling sustainable windmill park implementations. These developments call for novel, flexible and scalable spectrum management models to meet the operational requirements of these critical infrastructure verticals. This paper investigates spectrum management approaches and regulatory decisions for private mobile industrial communication networks for the offshore applications. The findings indicate that in offshore areas where significant natural resources, such as oil have been utilized, the regulators have defined mechanisms to make spectrum available while the regulation varies between countries. Traditionally, the regulators have been oriented towards public mobile networks and their service areas have been land oriented. The basis for the jurisdiction for offshore deployments is very different, and also the radio environment at sea differs significantly from that on land which calls for new authorization mechanisms and coordination approaches, and different technical requirements.

The prediction of wireless network parameters can help to facilitate proactive resource allocation solutions not only in cellular networks but also in enterprise networks. In this thesis, temporal and spatial analysis of network traffic using real traffic data of an enterprise network are presented, where we use three different machine learning (ML-based) methods and two different classical methods for temporal forecasting traffic usage. The results show that no universal best forecasting method can predict the traffic usage of every AP in an enterprise wireless network. The ML-based combined models are also used for spatio-temporal forecasting, improving the forecasting performance of single AP traffic usage. However, analyzing and predicting only network layer traffic data is not enough to execute decisions for resource allocation since the channels utilized in enterprise networks are shared unlicensed channels. Therefore, analyzing and forecasting the physical layer data of a channel are also investigated. In this thesis, we also improved the performance of conventional ML-based methods for time series forecasting by proposing a features-like grid training data structure which uses historical data as features. After proving that physical layer data has more predictive power in the time series forecasting aspect with all forecasting models, physical layer data transmit power (TP) and interference prediction are applied in spectrum sharing with a radar system to improve the secure radar protection and efficient transmission of APs. In particular, weather radar operating in the 5.6 GHz band is considered a primary system and the secondary system is an enterprise network consisting of APs in a university campus. First, the transmit power time series of APs in the campus are modeled with multinomial distribution based on real collected data. Then, the aggregated interference due to the transmissions from the APs at the radar is predicted using LSTM with Monte, Tiivistelmä Langattoman verkon parametrien ennustaminen voi auttaa edistämään ennakoivia resurssien allokointiratkaisuja myös yritysverkoissa. Työssä esitetään verkkoliikenteen ajallinen ja spatiaalinen analyysi yritysverkon todellisen liikennedatan avulla. Käytämme kolmea koneoppimismenetelmää (ML) ja kahta klassista menetelmää liikenteen käytön ajalliseen ennustamiseen. Tulokset osoittavat, että ei ole olemassa yhtä yleismaailmallista parasta ennustemenetelmää, jolla voidaan ennustaa jokaisen tukiaseman liikenteen käyttöä yrityksen langattomassa verkossa. ML-pohjaisia yhdistettyjä malleja käytetään myös ajallispaikalliseen ennustamiseen, mikä paransi yhden tukiaseman liikenteen käytön ennustamista. Pelkän verkkokerroksen liikennetietojen analysointi ja ennustaminen ei kuitenkaan riitä resurssien allokointipäätösten suorittamiseen, koska yritysverkoissa käytettävät kanavat ovat jaettuja lisensoimattomia kanavia. Siksi tutkitaan myös kanavan fyysisen kerroksen datan analysointia ja ennustamista. Paransimme myös perinteisten ML-pohjaisten menetelmien suorituskykyä aikasarjaennusteissa ehdottamalla uutta tietorakennetta oppimiseen, joka käyttää ominaisuuksina historiallisia tietoja. Sen jälkeen, kun on todistettu, että fyysisen kerroksen tiedoilla on enemmän ennustusvoimaa aikasarjan ennustamisessa kaikissa ennustemalleissa, fyysisen kerroksen datan lähetystehoa (TP) ja häiriöennustetta käytetään spektrin jakamisessa tutkan kanssa tutkasuojauksen ja tukiasemien tehokkaan tiedonsiirron parantamiseksi. Erityisesti 5,6 GHz:n kaistalla toimivaa säätutkaa tutkitaan ensisijaisena järjestelmänä ja toissijainen järjestelmä on yliopistokampuksen tukiasemista koostuva yritysverkko. Ensin kampuksen tukiasemien lähetystehon aikasarjat mallinnetaan multinomijakaumalla todellisen kerätyn datan perusteella. Tutkalle tukiasemien lähetyksistä johtuvat häiriöt ennustetaan käyttämällä LSTM:ää Monte Carlo (MC) -pudotuksen kanssa ottaen huomioon mallin epävarmuus. Lopuksi ehdotetaan kahte

Spectrum sharing in radar bands with interference forecasting for enhanced radar protection can help design proactive resource allocation solutions which can achieve high data rates for wireless communication networks on one hand and help protect the incumbent radar systems. We consider radar spectrum sharing in 5.6GHz where a weather radar operates as a primary system and the dominant secondary system is an enterprise network consisting of access points (APs) in a university campus. Our work models transmit the power of the APs as a time series with multinomial distribution based on real collected data. The aggregated interference due to the transmissions from the APs at the radar is forecasted using a long short-term memory (LSTM) based neural network. Monte Carlo dropout is utilized to generate prediction intervals that capture the uncertainties in the interference from the APs. Finally, by using both average and upper limits of predicted interference time series a cloud-assisted efficient sharing and radar protection algorithm is proposed. Tracking the rotating radar is not required in the proposed system. The results show that the proposed efficient sharing and radar protection system ensures better radar protection and increased throughput for wireless communication users.

Owing to its ability to improve both spectral and energy efficiency of wireless networks, massive multiple-input multiple-output (mMIMO) has become one of the key enablers of the fifth-generation (5G) and beyond communication systems. For successful integration of this promising physical layer technique in the upcoming cellular standards, it is essential to have a comprehensive understanding of its network-level performance. Over the last decade, stochastic geometry has been instrumental in obtaining useful system design insights of wireless networks through accurate and tractable theoretical analysis. Hence, it is only natural to consider modeling and analyzing the mMIMO systems using appropriate statistical constructs from the stochastic geometry literature and gain insights for its future implementation. With this broader objective in mind, we first focus on modeling a cellular mMIMO network that uses fractional pilot reuse to mitigate the sole performance-limiting factor of mMIMO networks, namely, pilot contamination. Leveraging constructs from the stochastic geometry literature, such as Johnson-Mehl cells, we derive analytical expressions for the uplink (UL) signal-to-interference-and-noise ratio (SINR) coverage probability and average spectral efficiency for a random user. From our system analysis, we present a partitioning rule for the number of pilot sequences to be reserved for the cell-center and cell-edge users that improves the average cell-edge user spectral efficiency while achieving similar cell-center user spectral efficiency with respect to unity pilot reuse. In addition, using the analytical approach developed for the cell-center user performance evaluation, we study the performance of a small cell system where user and base station (BS) locations are coupled. The impact of distance-dependent UL power control on the performance of an mMIMO network with unity pilot reuse is analyzed and subsequent system design guidelines are also presented. Next, w

Adaptive capacity with cost-efficient resource provisioning is a crucial capability for future 6G networks. In this work, we conceptualize "expansive networks" which refers to a networking paradigm where networks should be able to extend their resource base by opportunistic but self-controlled expansive actions. To this end, we elaborate on a key aspect of an expansive network as a concrete example: Spectrum resource at the PHY layer. Evidently, future wireless networks need to provide efficient mechanisms to coexist in the licensed and unlicensed bands and operate in expansive mode. In this work, we first describe spectrum sharing issues and possibilities in 6G networks for expansive networks. We then present security implications of expansive networks, an important concern due to more open and coupled systems in expansive networks. We also discuss two key enablers, namely distributed ledger technology (DLT) and network intelligence via machine learning, which are promising to realize expansive networks for the spectrum sharing aspect.

Increasingly more unlicensed bands accommodate multiple broadband technologies, e.g. Wi-Fi and LTE in the 5 GHz band and Wi-Fi 6E and 5G NR-U in the new 6 GHz unlicensed band. In these bands, the technologies coexist primarily via distributed MAC spectrum sharing mechanisms, so it is crucial to evaluate their performance using the right tools that reliably and accurately model the coexisting schemes. CSMA and duty cycle are representative schemes in this context, but the few modelling tools that capture their coexistence performance are yet to be properly evaluated in terms of accuracy and computational efficiency. This paper is the first to compare three such modelling tools - stochastic geometry modelling (SGM), ns-3, and our hybrid model - which comprise different time granularities and abstraction levels for the MAC mechanisms. We compare both the accuracy of their estimated SINR and throughput versus ns-3 and their computational efficiency, for CSMA and duty cycle coexistence. Furthermore, we make recommendations pertinent to future broadband coexistence cases. Our results show that ns-3 captures important effects of the CSMA sensing time on the SINR, but its computation time may be prohibitive for modelling coexisting dense networks. This tool is thus useful primarily for studying dynamic MAC features in small to medium-sized coexisting deployments. SGM is the least accurate and also requires a long computation time, so we argue it is the least attractive approach to model coexisting CSMA and duty cycle technologies. Finally, our hybrid model yields the time-average per-link SINR with reasonable accuracy and the throughput with good accuracy and is at least two orders of magnitude faster to compute than SGM and ns-3, making it very well suited for extensive Monte Carlo simulations and large networks., QC 20221012

In this paper, we consider a system model in conjunction with two major technologies in 5G communications, i.e., mobile edge computing and spectrum sharing. An IoT network, which does not have access to any licensed spectrum, carries its computational task offloading activities with help of spectrum sharing. The IoT network cooperates with a licensed spectrum holding network by relaying its data and in return gets access to the licensed spectrum. The licensed spectrum holding network focuses on throughput maximization, whereas, the IoT network tries to maximize task computation rate. We formulate an optimization problem giving importance to both networks’ interests. Typical IoT nodes may be energy-constrained, which is considered along with task computation time constraints. Parallel computation is considered while computing IoT nodes’ computational tasks at the mobile edge computing server, where the processor is allocated based on IoT nodes’ offloading capabilities. The advantage of such processor allocation is shown in the result section. Moreover, we also show how both IoT and licensed spectrum holding networks benefit from the spectrum sharing by caring for each other requirements, which echoes the fact, i.e., Sharing is Caring.

In this paper, the problem of joint transmit waveform and receive filter design for dual-function radar-communication (DFRC) systems is studied. The considered system model involves a multiple antenna base station (BS) of a cellular system serving multiple single antenna users on the downlink. Furthermore, the BS simultaneously introduces sensing capabilities in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. A novel framework based on constrained optimization problems is proposed for the joint design of the transmit waveform and the radar receive filter such that different constraints related to the power amplifiers and the radar waveform are satisfied. In contrast to the existing approaches in the DFRC systems' literature, the proposed approach does not require the knowledge of a predetermined radar beampattern in order to optimize the performance of the radar part through its approximation. Instead, a beampattern is generated by maximizing the radar receive signal-to-interference ratio (SINR) thus, enabling a more flexible design. Moreover, the radar receive filter processing and its optimization is considered for the first time on DFRC systems, enabling the effective exploitation of the available degrees of freedom in the radar receive array. Efficient algorithmic solutions with guaranteed convergence are developed for the defined constrained nonconvex optimization problems. The effectiveness of the proposed solutions is verified via numerical results., QC 20220523

The ongoing 5G evolution transforming network from connectivity driven to service dominant logic will impact the stakeholder roles, ecosystem and business models. Systemic change will lower the barriers to entry and expand the ecosystem to new roles such as local operators, edge cloud services providers and resource aggregators and agents. Spectrum regulation has traditionally acted as a gate keeper of the mobile service provisioning, and lately national authorities have reacted via allocating new frequency bands and considering novel flexible spectrum administration and management methods and tools. This paper provides a comprehensive overview of the most recent spectrum regulation decisions for mobile communication networks and shows how local licensing, spectrum sharing, and unlicensed commons approaches work as novel business model antecedent. The study analyzes key spectrum antecedents for the open ecosystemic business model value configuration.

New generations of mobile communication are expected to support QoS constraints ranging from low latency (few milliseconds) and extreme reliability (> 99.99%), enabling Ultra-Reliable Low Latency Communication (URLLC). Beside health risks of electromagnetic radiation, URLLC devices usually have limited power resources, which dictates careful planning of throughput maximization with green communication schemes. Hence, it becomes crucial to optimize resource allocation and study the interplay between power, delay, and reliability. Effective Capacity (EC) indicates the maximum communication rate subject to a certain delay constraint while effective energy efficiency (EEE) denotes the ratio between EC and power consumption. We analyze these metrics in ultra-reliable networks and characterize the performance gap resulting from finite blocklength operation. Our analysis determines the upper bounds for EC and delay constraint when varying transmission power. We characterize the power-delay trade-off for fixed EC and propose a power saving scheme which exploits the asymptotic behavior of EC in the high SNR regime. We study different models for energy efficient transmission such as empty buffer probability and adaptive retransmission. We obtain closed form expressions for EC and EEE in fading channels as a function of power, error probability, and delay. Moreover, the optimum power allocation strategy for maximizing EEE is defined for each model. Next, we present an opportunistic spectrum sharing scheme that applies ARQ with successive interference cancellation. The proposed scheme outperforms the open loop and non-opportunistic scenarios in terms of secondary user transmit power and primary user reliability. In the context of retransmissions, we also illustrate a power saving uplink algorithm by optimally allocating time and frequency resources for packets with heterogeneous reliability requirements. Finally, in the context of massive access schemes, we assume disc, Tiivistelmä Uuden sukupolven liikkuvan tietoliikenteen odotetaan tukevan Keskeiset erittäin luotettavan pienen latenssin tiedonsiirron (URLLC) ja palvelun laadun (QoS) vaatimukset vaihtelevat pienestä muutaman millisekunnin luokkaa olevasta viiveestä äärimmäiseen, yli 99,99 % luotettavuuteen. Sähkömagneettisen säteilyn terveysriskien lisäksi, useimmissa tapauksissa URLLC-laitteilla on rajalliset virtalähteet, joka ekologista energiatehokasta viestintäjärjestelmää unohtamatta. Tässä, on ratkaisevan tärkeää optimoida resurssien kohdentamista ja tehon, latenssin ja luotettavuuden välistä vuorovaikutusta. Efektiivinen kapasiteetti (EC) ilmaisee suurimman tiedonsiirtonopeuden tietyllä viivekriteerillä, kun taas efektiivinen energiatehokkuus (EEE) tarkoittaa EC:n ja energiankulutuksen suhdetta. Analysoimme näitä mittareita erittäin luotettavina verkoissa ja luonnehdimme äärellisen lohkon pituudesta johtuvaa suorituskykyä. Analyysi määrittelee myös EC:n ylärajat ja viiverajoitukset lähetystehoa vaihdettaessa. Tehon ja viiveen välistä kaupankäyntiä luonnehditaan kiinteällä EC:llä ja tehonsäästöön ehdotetaan EC:n asymptoottista käyttäytymistä suurilla signaalikohinasuhteilla hyödyntävää. Erilaiset energiatehokkaan siirron mallit vaihtelevat aina täyden puskurin mallista malleihin, jotka pohjautuvat uudelleenlähetyksiin. Tutkittavalle metriikalle johdetaan suljetun muodon lausekkeita häipyvissä kanavissa tehon, virhetodennäköisyyden ja latenssin funktiona. Lisäksi jokaiselle mallille määritetään optimaalinen tehonjakostrategia EEE:n maksimoimiseksi. Seuraavaksi esitetään opportunistinen taajuuksien jakamisjärjestelmä, joka soveltaa automaattista toistopyyntöä (ARQ) ja peräkkäistä häiriönpoistoa. Ehdotettu järjestelmä on parempi kuin avoimeen silmukkaan ja ei-opportunistisiin skenaarioihin perustuvat järjestelmät toissijaisen käyttäjän lähetystehon säästön ja ensisijaisen käyttäjän luotettavuuden kannalta. Uudelleenlähetysten yhteydessä havainnollistetaan myös nousevan siirtot

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., The popularity of mobile broadband connectivity continues to grow and thus, the future wireless networks are expected to serve a very large number of users demanding a huge capacity. Employing larger spectral bandwidth and installing more access points to enhance the capacity is not enough to tackle the stated challenge due to related costs and the interference issues involved. In this way, frequency resources are becoming one of the most valuable assets, which require proper utilization and fair distribution. Traditional frequency resource management strategies are often based on static approaches, and are agnostic to the instantaneous demand of the network. These static approaches tend to cause congestion in a few cells, whereas at the same time, might waste those precious resources on others. Therefore, such static approaches are not efficient enough to deal with the capacity challenge of the future network. Thus, in this paper we present a dynamic access-aware bandwidth allocation approach, which follows the dynamic traffic requirements of each cell and allocates the required bandwidth accordingly from a common spectrum pool, which gathers the entire system bandwidth. We perform the evaluation of our proposal by means of real network traffic traces. Evaluation results presented in this paper depict the performance gain of the proposed dynamic access-aware approach compared to two different traditional approaches in terms of utilization and served traffic. Moreover, to acquire knowledge about access network requirement, we present a machine learning-based approach, which predicts the state of the network, and is utilized to manage the available spectrum accordingly. Our comparative results show that, in terms of spectrum allocation accuracy and utilization efficiency, a well designed machine learning-based bandwidth allocation mechanism not only outperforms common static approaches, but even achieves the performance (with a relative error close to 0.04) of an ide, This work was supported in part by the EU Horizon 2020 Research and Innovation Program (5GAuRA) under Grant 675806, and in part by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement from the Generalitat de Catalunya under Grant 2017 SGR 376., Peer Reviewed, Postprint (published version)

Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference. Unfortunately, traditional model-based spectrum sharing schemes make idealistic assumptions about inter-operator coordination mechanisms in terms of latency and protocol overhead, while being sensitive to missing channel state information. In this paper, we propose hybrid model-based and data-driven multi-operator spectrum sharing mechanisms, which incorporate model-based beamforming and user association complemented by data-driven model refinements. Our solution has the same computational complexity as a model-based approach but has the major advantage of having substantially less signaling overhead. We discuss how limited channel state …, QC 20200630

Long-Term Evolution (LTE) is the fourth generation (4G) wireless communications standard and its evolution is paving the path for the fifth generation (5G) technology. LTE is also considered for supporting public safety networks, Machine-to-Machine (M2M) communications, and many other applications. Hence, it is critical to ensure that the LTE system performs effectively even in harsh signaling environments. Unfortunately, LTE is vulnerable to intentional interference at the physical layer. We define the term LTE control channel spoofing, which refers to the case when an adversary sets a fake LTE-like base station (evolved NodeB or eNodeB) that transmits a partial or full LTE downlink frame to deceive LTE devices and hinder them from attaching to a real cell. Based on analyzing the initial cell selection process in the LTE specifications, we identify three different level of LTE control channel spoofing. We have built a testbed to demonstrate the feasibility of such an attack. The experimental results show that LTE control channel spoofing can cause permanent denial of service for LTE devices during the cell selection process. We propose effective mitigation techniques to enhance the immunity of LTE systems against all the three forms of LTE control channel spoofing, and ensure that it is secure and available when and where needed. Moreover, the commercial success of LTE and the resulting growth in mobile data demand have motivated cellular network operators to strive for new innovations. LTE-Unlicensed has been recently proposed to allow cellular network operators to offload some of their data traffic by accessing the unlicensed 5 GHz frequency band. There are three variants of LTE-Unlicensed that have been proposed in the industry. These variants differ in their operational features, but they enhance the capacity of LTE and represent a big milestone in its evolution toward 5G. However, LTE-Unlicensed faces several challenges when operating in the 5 GHz bands, as th

Society's newfound dependence on wireless transmission systems has driven demand for access to the electromagnetic (EM) spectrum to an all-time high. In particular, wireless applications related to the fifth generation (5G) of cellular technology along with statically allocated radar systems have contributed to the increasing scarcity of the sub 6 GHz frequency bands. As a result, development of Dynamic Spectrum Access (DSA) techniques for sharing these frequencies has become a critical research area for the greater wireless community. Since among incumbent systems, radars are the largest consumers of spectrum in the sub 6 GHz regime, and are being used increasingly for civilian applications such as traffic control, adaptive cruise control, and collision avoidance, the need for radars which can adaptively tune specific transmission parameters in an intelligent manner to promote coexistence with other systems has arisen. Thus, fully-aware, dynamic, cognitive radar has been proposed as target for radars to evolve towards. In this thesis, we extend current research thrusts towards cognitive radar to utilize Reinforcement Learning (RL) techniques which allow a radar system to learn desired behavior using information obtained from past transmissions. Since radar systems inherently interact with their electromagnetic environment, it is natural to view the use of reinforcement learning techniques as a straightforward extension to previous adaptive techniques. However, in designing learning algorithms for radar systems, we must carefully define goal-driven rewards, formalize the learning process, and consider an appropriate amount of environmental information. In this thesis, we apply well-established and emerging reinforcement learning approaches to meet the demands of modern radar coexistence problems. In particular, function estimation using deep neural networks is examined, as Deep RL presents a scalable learning framework which allows many environmental states to be co

Over the last few decades, wireless networks have morphed from traditional cellular/wireless local area networks (WLAN), into a wide range of applications, such as the Internet-of-Things (IoT), vehicular-to-everything (V2X), and smart grid communication networks. This transition has been facilitated by research and development efforts in academia and industry, which has resulted in the standardization of fifth-generation (5G) wireless networks. To meet the performance requirements of these diverse use-cases, 5G networks demand higher performance in terms of data rate, latency, security, and reliability, etc. At the physical layer, these performance enhancements are achieved by (a) optimizing spectrum utilization shared amongst multiple technologies (termed as spectrum sharing), and (b) leveraging advanced spatial signal processing techniques using large antenna arrays (termed as massive MIMO). In this dissertation, we focus on enhancing the performance of next-generation vehicular communication and spectrum sharing systems. In the first contribution, we present a novel pilot configuration design and adaptation mechanism for cellular vehicular-to-everything (C-V2X) networks. Drawing inspiration from 4G and 5G standards, the proposed approach is based on limited feedback of indices from a codebook comprised of quantized channel statistics information. We demonstrate significant rate improvements using our proposed approach in terrestrial and air-to-ground (A2G) vehicular channels. In the second contribution, we demonstrate the occurrence of cellular link adaptation failure due to channel state information (CSI) contamination, because of coexisting pulsed radar signals that act as non-pilot interference. To mitigate this problem, we propose a low-complexity semi-blind SINR estimation scheme that is robust and accurate in a wide range of interference and noise conditions. We also propose a novel dual CSI feedback mechanism for cellular systems and demonstrate significan

5G will extend the mobile technology deployment beyond the communications industry, bringing connectivity to the explosively growing number of devices and services. To be able to respond to 5G sectors’ different requirements, as well as the spectrum scarcity issue, different spectrum access approaches need to be considered. The aim of this article is to identify substantial properties of spectrum access approaches to assess their suitability to 5G vertical use cases. We have defined five optional spectrum access scenarios for 5G vertical network service providers (VNSPs) in acquiring spectrum access to provide a network service to either end users or other companies. The stakeholders involved in the spectrum awarding process are identified, and their roles and targets are examined. Furthermore, the advantages and drawbacks of each scenario are covered. Following the discussion, we were able to highlight some substantive characteristics in terms of suitability assessment, namely reliability, locality and mobility, mobile network operators (MNOs) involvement, costs and time scale. These characteristics were analysed in terms of each scenario to further the scenario’s suitability assessment to VNSPs’ purposes.

In this paper, the throughput and energy efficiency of an unlicensed machine type communications network is studied. If an outage event happens in the network, there is a possibility for packet retransmission in order to obtain a lower error probability. The concept of spectrum sharing is used here for modeling the network, which allows the two types of licensed and unlicensed users to share the same uplink channel allocated to the licensed users. However, it is done in a way that no harm is done to the licensed nodes’ transmission for sharing the same channel with the unlicensed users, while licensed nodes’ transmission causes interference on the unlicensed network. Poisson point process is used here to model the location of the nodes and the effect of interference on the network. We study how different factors such as the number of retransmissions, SIR threshold and outage can affect the throughput and energy efficiency of the network. Throughput and energy efficiency are also both studied in constrained optimization problems where the constraints are the SIR threshold and the number of retransmission attempts. We also show why it is important to use limited transmissions and what are the benefits.

The dramatically development of wireless technologies in the last few decades, leads to the growth of channel resources demand in a limited spectrum with inextensible character. Cognitive radio network (CR) is a promising technology that provides solutions for the spectrum management and optimization problems via dynamic spectrum management. The spectrum resources management and optimization are an important part of the future network performances. In this paper, we propose an efficient algorithm to examine the design specification issues regarding the choice of optimal power, optimal speed, and optimal amount of information in a wireless network along with studying the effect of different parameters on the obtained results. Our objectives are to guarantee the protection on licensed users (Primary users ‘PU’) from harmful interference caused by the unlicensed users (Secondary users ‘SU’), more especially, to optimize the quality of communication link, Transmission levels, and battery life of the wireless devices. Results show that our proposed work leads to an efficient utilization of radio spectrum and strongly contributes to alleviating the spectrum scarcity problem.

The unlicensed spectrum offers tremendous opportunities for mobile network operators (MNOs), whose traffic can be offloaded from licensed bands to unlicensed ones. To realize these opportunities, three new technologies have been proposed: LTE-Unlicensed (LTE-U), 4G LTE Licensed-Assisted Access (LAA), and 5G New Radio Unlicensed (NR-U). Although unlicensed spectrum seems attractive to MNOs, its access is fraught with many challenges that need to be addressed. These include coexistence with legacy unlicensed technologies such as Wi-Fi and Bluetooth, fairness in channel access, and supporting a desired level of quality of service (QoS) in a shared-spectrum environment. Addressing these challenges is critical for achieving harmonious coexistence between various technologies. In this dissertation, we design resource management algorithms and channel access protocols to overcome these challenges. We mainly focus on issues arising in three scenarios: (1) coexistence between Listen-Before-Talk (LBT), e.g., Wi-Fi, and non-LBT systems, e.g., LTE-U, (2) coexistence within LBT systems (e.g., 4G LTE LAA, 5G NR-U, and Wi-Fi), and (3) resource allocation for LBT systems sharing a common network infrastructure (e.g., 5G NR-U and Wi-Fi). For the first scenario, we develop a cross-technology detection scheme that allows LBT devices to concurrently transmit over and sense the channel, a.k.a., full-duplex (FD) sensing. This will reduce the impact of collisions between LBT and non-LBT devices. LBT devices can then detect collisions with non-LBT devices earlier, allowing them to react properly by pausing transmission and preventing interference. We develop a framework based on Partially Observable Markov Decision Process (POMDP) that allows FD-enabled LBT devices to mitigate interference generated by non-LBT devices. By following a POMDP policy, LBT devices can jointly adapt their transmission rates and duplex mode based on their belief about interference caused by non-LBT devices. Altho

This paper presents a stochastic geometry analysis of radio interference and a grid-based design of a primary exclusive region (PER) for spectrum sharing in the 3D unmanned aerial vehicle (UAV) networks. When a UAV network shares frequency bands with a primary system (e.g., a weather radar system), the UAVs must avoid harmful interference with the primary system. To facilitate the design of a complex-shaped PER according to a primary user's antenna pattern, spatial grid models, namely cylindrical and cubic grid models, are introduced. In the cylindrical grid model, to approximate the distribution of the interference at the radar, the cumulants of the interference are expressed by expressions with simple integrals or even closed-form expressions based on the assumption that the distributions of the UAVs in each grid cell follow an inhomogeneous 3D Poisson point process (PPP). In the cubic grid model, the shape of the grid cell is approximated by the cylindrical grid cell to derive the cumulants of the interference because they cannot be calculated in the same manner as in the cylindrical grid model. Using the derived interference cumulants to determine a PER to satisfy the radar's outage probability target, an optimization problem that minimizes the number of the UAVs forbidden from transmitting signals is formulated. The numerical results confirm that the approximated interference distribution using cumulants is in acceptable agreement with the simulation results and the PER obtained from the proposed optimization problem improves the number of the transmitting UAVs by reducing the volume of grid cells.

We consider the performance optimization of multi-cell networks with LTE and Wi-Fi aggregation (LWA) and LTE-unlicensed (LTE-U) with sharing of the unlicensed band. Theoretical results are derived to enable an algorithm to approach the optimum. Numerical results show the algorithm's effectiveness and benefits of joint use of LWA and LTE-U.

Increasing capacity demands in emerging wireless technologies are expected to be met by network densification and spectrum bands open to multiple technologies. These will, in turn, increase the level of interference and also result in more complex inter-technology interactions, which will need to be managed through spectrum sharing mechanisms. Consequently, novel spectrum sharing mechanisms should be designed to allow spectrum access for multiple technologies, while efficiently utilizing the spectrum resources overall. Importantly, it is not trivial to design such efficient mechanisms, not only due to technical aspects, but also due to regulatory and business model constraints. In this survey we address spectrum sharing mechanisms for wireless inter-technology coexistence by means of a technology circle that incorporates in a unified, system-level view the technical and nontechnical aspects. We thus systematically explore the spectrum sharing design space consisting of parameters at different layers. Using this framework, we present a literature review on inter-technology coexistence with a focus on wireless technologies with equal spectrum access rights, i.e., (i) primary/primary, (ii) secondary/secondary, and (iii) technologies operating in a spectrum commons. Moreover, we reflect on our literature review to identify possible spectrum sharing design solutions and performance evaluation approaches useful for future coexistence cases. Finally, we discuss spectrum sharing design challenges and suggest future research directions., QC 20200420

In this paper, an intelligently cooperative communication network with cognitive users is considered, where in a primary system and a secondary system, respectively, a message is communicated to their respective receiver over a packet-based wireless link. The secondary system assists in the transmission of the primary message employing network coding, on the condition of maintaining or improving the primary performance, and is granted limited access to the transmission resources as a reward. The users in both systems exploit their previously received information in encoding and decoding the binary combined packets. Considering the priority of legitimate users, a selective cooperation mechanism is investigated and the system performance based on an optimization problem is analyzed. Both the analytical and numerical results show that the condition for the secondary system accessing the licensed spectrum resource is when the relay link performs better than the direct link of the primary transmission. We also extend the system model into a network with multiple secondary users and propose two relay selection algorithms. Jointly considering the related link qualities, a best relay selection and a best relay group selection algorithm are discussed. Overall, it is found that the throughput performance can be improved with multiple secondary users, especially with more potential users cooperating in the best relay group selection algorithm., QC 20190325

We consider an asynchronous cognitive radio framework, where the primary user (spectrum license holder) and the secondary user are, naturally, not aligned in their timing. We show that applying our optimal receiver design results in improving the performance compared to the case of synchronous cognitive radio. We optimize the rates subject to the constraint to keep interference imposed on the primary user below a certain level. We also derive the constraint for the receiver of the secondary user to perform interference cancellation. Simulation results show that our proposed oversampling secondary user receiver boosts the received signal. As a result, the secondary user's transmission power can be decreased without negatively affecting the quality of the received signal. Not only does our method reduce the interference to the primary user but also it saves power at the secondary user.

The emergence of the massive Internet-of-things (IoT) market, i.e., applications with large-scale deployment of Internet-enabled devices, is transforming many sectors, including cities, logistics, retail, and agriculture. Nevertheless, a large-scale uptake of such applications is intertwined with connectivity challenges due to the unique traffic characteristics of massive IoT and the high density of IoT devices. The main objective of this dissertation is to develop spectrum sharing solutions to enable massive IoT connectivity over the unlicensed and licensed bands. To this end, we unravel the interplay between the intra-network sharing and inter-network sharing, i.e., how a high density of low-cost IoT devices should share the spectrum among themselves while still harmoniously coexist with other wireless networks. We first present a framework to model and analyze ultra-narrowband (UNB) communications, where IoT devices randomly access the unlicensed spectrum using extremely narrowband signals. The framework enables tractable analysis of large-scale networks, identifying fundamental limits and proposing enhancements that help UNB networks support a higher density of low-rate IoT devices. We then present an access scheme that supports applications with higher rates over unlicensed bands with sensing regulations. To this end, we revisit spectrum sensing for massive IoT and propose a sensing-based system, where base stations with narrowband receivers locally share and process sensing reports to scan a wideband spectrum, identifying resources at a fine spectral resolution and aggressively reusing them over space. Next, for applications with strict quality-of-service guarantees, we consider cellular connectivity, where we develop a shared spectrum access protocol, leveraging drones as IoT data aggregators. The proposed protocol maximizes the energy-efficiency of IoT devices while still protecting existing cellular users from interference. Last, we analyze and optimize the

Spectrum sharing and management constitute an important tool for alleviating the problem of spectrum scarcity and underutilization. For 5G networks, a number of spectrum sharing schemes are currently under consideration, which differ significantly from the traditional approaches, namely, exclusive access and unlicensed access. The choice of spectrum sharing scheme has a significant impact on the virtualization aspects of the network. This chapter discusses spectrum sharing and its ramifications on the architecture of virtualized wireless networks. We provide a survey of important spectrum sharing schemes and discuss their pros and cons from a 5G perspective. This is followed by an up-to-date account of regulatory aspects and field trials of the important spectrum sharing schemes. The main challenges pertinent to spectrum sharing in virtualized networks are identified. Furthermore, we discuss an architecture for enabling efficient spectrum management and network virtualization in multi-operator 5G networks., QC 20210914

We propose a novel asynchronous direct-sequence code-division multiple access (DS-CDMA) using feedback-controlled spreading sequences (FCSSs) (FCSS/DS-CDMA). At the receiver of FCSS/DS-CDMA, the code-orthogonalizing filter (COF) produces a spreading sequence, and the receiver returns the spreading sequence to the transmitter. Then the transmitter uses the spreading sequence as its updated version. The performance of FCSS/DS-CDMA is evaluated over time-dispersive channels. The results indicate that FCSS/DS-CDMA greatly suppresses both the intersymbol interference (ISI) and multiple access interference (MAI) over time-invariant channels. FCSS/DS-CDMA is applicable to the decentralized multiple access.

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., This paper elaborates on the design challenges, opportunities, and solutions for New Radio-based access to Unlicensed spectrum (NR-U) by taking into account the beam-based transmissions and the worldwide regulatory requirements. NR-U intends to expand the applicability of 5th generation New Radio access technology to support operation in unlicensed bands by adhering to Listen-Before-Talk (LBT) requirements for accessing the channel. LBT was already adopted by different variants of 4th generation Long Term Evolution (LTE) in unlicensed spectrum, i.e., Licensed-Assisted Access and MulteFire, to guarantee fair coexistence among different radio access technologies. In the case of beam-based transmissions, the NR-U coexistence framework is significantly different as compared to LTE in unlicensed spectrum due to the use of directional antennas, which enhance the spatial reuse but also complicate the interference management. In particular, beam-based transmissions are needed in the unlicensed spectrum at millimeter-wave (mmWave) bands, which is an attractive candidate for NR-U due to its large amount of allocated spectrum. As a consequence, some major design principles need to be revisited to address coexistence for beam-based NR-U. In this paper, different problems and the potential solutions related to channel access procedures, frame structure, initial access procedures, re-transmission procedures, and scheduling schemes are discussed. A simulation evaluation of different LBT-based channel access procedures for NR-U/Wi-Fi indoor mmWave coexistence scenarios is also provided., This work was partially funded by Spanish MINECO grant TEC2017-88373-R (5G-REFINE) and Generalitat de Catalunya grant 2017 SGR 1195. Also, it was supported by InterDigital Communications, Inc., Peer Reviewed, Postprint (author's final draft)

Radio spectrum is a scarce natural resource, whose efficient management calls for a thorough understanding of its value. A number of spectrum valuation approaches has emerged considering different elements, some with potentially high uncertainty as future profits, total cost of ownership and societal benefits. Spectrum valuation is important in regulators’ 5G spectrum decisions and will face a new situation, where location specific services and higher carrier frequencies give rise to local network operator models. This paper analyzes the existing spectrum management and spectrum valuation approaches and identifies key elements to consider, when defining and assessing the value of spectrum especially in the context of future local 5G networks. The growing pressure to open the mobile market for location and vertical specific 5G networks promotes new sharing-based spectrum access models, to allow the emergence of local 5G operators. We characterize the identified spectrum valuation elements in the context of these new local 5G networks from the perspectives of the different stakeholder roles including regulators, mobile network operators (MNOs) and entrant local 5G operators. We further present a spectrum valuation case study of the recent 5G spectrum decisions in the 3.5-GHz band in different countries.

We develop and analyze a new user-centric networking model for ubiquitous spectrum sharing where every user can share and use the spectrum under uncertainty of their traffic models. In this concept, users when connected to the Internet (wired/wireless) can dynamically serve as access points for other users in their vicinity. For this reason, the concept is referred to as user-centric distributed spectrum sharing. Each user in spectrum sharing mode utilizes a part of its available spectrum for its own traffic and remaining part to share with users in spectrum demanding modes. The model is designed as an operator supervised double-Stackelberg game with network operators, access points, and users as main players. We study network reliability and latency of the system under uncertainty of users’ traffic patterns. The numerical results show that the proposed model, depending on different settings, can significantly improve both profit and utility for network operators and users, respectively. Furthermore, network reliability is significantly improved depending on the network parameters for both users and operators.

The aim of this thesis is to devise new paradigms on radio resource sharing including cache-enabled virtualized large cellular networks for mobile network operators (MNOs). Also, self-organizing resource allocation for small cell networks is considered. In such networks, the MNOs rent radio resources from the infrastructure provider (InP) to support their subscribers. In order to reduce the operational costs, while at the same time to significantly increase the usage of the existing network resources, it leads to a paradigm where the MNOs share their infrastructure, i.e., base stations (BSs), antennas, spectrum and edge cache among themselves. In this regard, we integrate the theoretical insights provided by stochastic geometrical approaches to model the spectrum and infrastructure sharing for large cellular networks. In the first part of the thesis, we study the non-orthogonal multi-MNO spectrum allocation problem for small cell networks with the goal of maximizing the overall network throughput, defined as the expected weighted sum rate of the MNOs. Each MNO is assumed to serve multiple small cell BSs (SBSs). We adopt the many-to-one stable matching game framework to tackle this problem. We also investigate the role of power allocation schemes for SBSs using Q-learning. In the second part, we model and analyze the infrastructure sharing system considering a single buyer MNO and multiple seller MNOs. The MNOs are assumed to operate over their own licensed spectrum bands while sharing BSs. We assume that multiple seller MNOs compete with each other to sell their infrastructure to a potential buyer MNO. The optimal strategy for the seller MNOs in terms of the fraction of infrastructure to be shared and the price of the infrastructure, is obtained by computing the equilibrium of a Cournot-Nash oligopoly game. Finally, we develop a game-theoretic framework to model and analyze a cache-enabled virtualized cellular networks where the network infrastructure, e.g., Tiivistelmä Tämän väitöskirjan tavoitteena on tuottaa uusia paradigmoja radioresurssien jakoon, mukaan lukien virtualisoidut välimuisti-kykenevät suuret matkapuhelinverkot matkapuhelinoperaattoreille. Näiden kaltaisissa verkoissa operaattorit vuokraavat radioresursseja infrastruktuuritoimittajalta (InP, infrastructure provider) asiakkaiden tarpeisiin. Toimintakulujen karsiminen ja samanaikainen olemassa olevien verkkoresurssien hyötykäytön huomattava kasvattaminen johtaa paradigmaan, jossa operaattorit jakavat infrastruktuurinsa keskenään. Tämän vuoksi työssä tutkitaan teoreettisia stokastiseen geometriaan perustuvia malleja spektrin ja infrastruktuurin jakamiseksi suurissa soluverkoissa. Työn ensimmäisessä osassa tutkitaan ei-ortogonaalista monioperaattori-allokaatioongelmaa pienissä soluverkoissa tavoitteena maksimoida verkon yleistä läpisyöttöä, joka määritellään operaattoreiden painotettuna summaläpisyötön odotusarvona. Jokaisen operaattorin oletetaan palvelevan useampaa piensolutukiasemaa (SBS, small cell base station). Työssä käytetään monelta yhdelle -vakaata sovituspeli-viitekehystä SBS:lle käyttäen Q-oppimista. Työn toisessa osassa mallinnetaan ja analysoidaan infrastruktuurin jakamista yhden ostaja-operaattorin ja monen myyjä-operaattorin tapauksessa. Operaattorien oletetaan toimivan omilla lisensoiduilla taajuuksillaan jakaen tukiasemat keskenään. Myyjän optimaalinen strategia infrastruktuurin myytävän osan suuruuden ja hinnan suhteen saavutetaan laskemalla Cournot-Nash -olipologipelin tasapainotila. Lopuksi, työssä kehitetään peli-teoreettinen viitekehys virtualisoitujen välimuistikykenevien soluverkkojen mallintamiseen ja analysointiin, missä InP:n omistama verkkoinfrastruktuuri vuokrataan ja jaetaan monen operaattorin kesken. Työssä muodostetaan Stackelberg-pelimalli, jossa InP toimii johtajana ja operaattorit seuraajina. InP pyrkii maksimoimaan voittonsa optimoimalla infrastruktuurin vuokrahintaa. Operaattori pyrkii minimoimaan infrastruktuurin hinnan

Cooperative ambient backscatter system is a novel symbiotic radio paradigm, in which the passive backscatter transmission shares not only the same spectrum but also the same radio-frequency source with the active primary transmission. By considering the unique features of the ambient backscatter system, three practical symbiotic transmission schemes are proposed, in which the relationships between the primary and backscatter transmissions are commensal, parasitic, and competitive, respectively. The achievable rates for both primary and backscatter transmissions are derived for particular fading state. Then, optimal power allocation is obtained for each transmission scheme under the average power constraint. Simulation results are provided to corroborate theoretical studies. © 2012 IEEE.

Ambient backscatter communications (AmBC) enable wireless communications riding on ambient radio frequency (RF) signals instead of self-generated RF signals. Therefore, it has been considered as a promising candidate for the future Internet-of-Things with stringent energy and spectrum constraints. In this paper, we investigate a full-duplex-enabled cognitive backscatter network, in which an AmBC system underlays a primary cellular system, and the primary access point can transmit primary signals and receive backscatter signals simultaneously via full-duplex communications. We aim to maximize the throughput of the AmBC system while guaranteeing the minimum rate requirements of the primary system via joint time scheduling, transmit power allocation, and reflection coefficient (RC) adjustment. To solve the problem, we propose an iterative method utilizing block coordinated decent to partition the variables into the time scheduling variable and the joint transmit power allocation and RC adjustment variable. For the time scheduling problem, we first prove its convexity and then utilize the interior-point method to solve it. For the joint power allocation and RC adjustment problem, we resort to the concave-convex procedure to transform it into a sequence of convex optimization problems, and then adopt Lagrange dual decomposition to tackle these convex optimization problems. The simulation results demonstrate that the proposed method can significantly increase the throughput of the AmBC system with a fast convergence speed. © 2002-2012 IEEE.

In this letter, a novel spectrum sharing system referred to as cognitive backscatter network (CBN) is proposed to support passive Internet of Things (IoT) transmission via backscatter modulation, in which the primary system transmits a sinusoidal carrier in addition to its own signal. In contrast to existing ambient backscatter communications, the proposed CBN does not require perfect symbol synchronization between the IoT and the primary transmissions. We maximize the data rate of the IoT transmission subject to the minimum rate requirement of the primary system by jointly optimizing the time sharing and power allocation parameters. Numerical results have demonstrated the superiority of the proposed CBN over conventional TDMA scheme. © 2012 IEEE.

This paper proposes a chance-constrained stochastic optimization technique that enables effective coexistence between LTE-Unlicensed base stations and radars in a shared spectrum. The optimization problem is formulated to guarantee the minimum performance criteria for radar operation, and at the same time, allows the LTE-Unlicensed base station to control its transmit power to maximize the performance for the serving LTE-Unlicensed device. The proposed power control mechanism results in significant reduction of the required protection distance (3.9% of the one imposed by regulations) between the radar and the LTE-Unlicensed network for the two to effectively coexist in a shared spectrum.

Full-duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth generation (5G) and beyond wireless communication systems due to its advantages, including potential doubling of the capacity and increased spectrum utilization efficiency. However, one of the main challenges of FD technology is the mitigation of strong self-interference (SI). Recent advances in different SI cancellation techniques, such as antenna cancellation, analog cancellation, and digital cancellation methods, have led to the feasibility of using FD technology in different wireless applications. Among potential applications, one important application area is dynamic spectrum sharing (DSS) in wireless systems particularly 5G networks, where FD can provide several benefits and possibilities such as concurrent sensing and transmission (CST), concurrent transmission and reception, improved sensing efficiency and secondary throughput, and the mitigation of the hidden terminal problem. In this direction, first, starting with a detailed overview of FD-enabled DSS, we provide a comprehensive survey of recent advances in this domain. We then highlight several potential techniques for enabling FD operation in DSS wireless systems. Subsequently, we propose a novel communication framework to enable CST in DSS systems by employing a power control-based SI mitigation scheme and carry out the throughput performance analysis of this proposed framework. Finally, we discuss some open research issues and future directions with the objective of stimulating future research efforts in the emerging FD-enabled DSS wireless systems., QC 20191029