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In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.

In this paper, we present a two‐stage scalable channel estimator (TSCE), a deep learning (DL)‐based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting‐edge neural network architecture, as a backbone for accurate estimation. For computation‐efficient global feature extractions, we propose using window and window averaging‐based self‐attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL‐based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL‐based estimators. [ABSTRACT FROM AUTHOR]

Abstract Both software-defined networking and big data have gained approval and preferences from both industry and academia. These two important realms have conventionally been addressed independently in wireless cellular networks. The discussion taken into consideration in this study was to analyze the wireless cellular technologies with the contrast of efficient and enhanced spectral densities at a reduced cost. To accomplish the goal of this study, Welch's method has been used as the core subject. With the aid of previous research and classical techniques, this study has identified that the spectral densities can be enhanced at reduced costs with the help of the power spectral estimation methods. The Welch method gives the result on power spectrum estimation. By reducing the effect of noise, the Welch method is used to calculate the power spectral density of a signal. When data length is increased, Welch's method is considered the best as a conclusion to this paper because excellent results are yielded by it in the area of power spectral density estimation.

As one of the most critical elements in the hydrological cycle, real-time and accurate rainfall measurement is of great significance to flood and drought disaster risk assessment and early warning. Using commercial microwave links (CMLs) to conduct rainfall measure is a promising solution due to the advantages of high spatial resolution, low implementation cost, near-surface measurement, and so on. However, because of the temporal and spatial dynamics of rainfall and the atmospheric influence, it is necessary to go through complicated signal processing steps from signal attenuation analysis of a CML to rainfall map. This article first introduces the basic principle and the revolution of CML-based rainfall measurement. Then, the article illustrates different steps of signal process in CML-based rainfall measurement, reviewing the state of the art solutions in each step. In addition, uncertainties and errors involved in each step of signal process as well as their impacts on the accuracy of rainfall measurement are analyzed. Moreover, the article also discusses how machine learning technologies facilitate CML-based rainfall measurement. Additionally, the applications of CML in monitoring phenomena other than rain and the hydrological simulation are summarized. Finally, the challenges and future directions are discussed. [ABSTRACT FROM AUTHOR]

In wireless cellular networks, handoff is a key element in providing quality of service and supporting mobility for users. There is an interaction between wireless cellular networks and handoff calls which strategically act to achieve their own objectives. In order to reasonably control the access of handoff calls and achieve the optimization of social network resources, we present a game-theoretic queueing model to investigate the strategic behavior of handoff calls in wireless cellular networks. The noncooperative joining behavior of handoff calls that maximizes their expected net benefit selfishly is considered. Moreover, the socially optimal joining behavior of handoff calls that maximizes their social total welfare is analyzed. The equilibrium and socially optimal strategies of handoff calls are obtained. Counter-intuitively, we find that the socially optimal joining probability is larger than the equilibrium joining probability. In order to eliminate the difference of joining probabilities, an appropriate incentive-payment is proposed to attract handoff calls to join the system actively. In doing so, it is feasible to induce individuals to behave in a socially best way. [ABSTRACT FROM AUTHOR]

Both software-defined networking and big data have gained approval and preferences from both industry and academia. These two important realms have conventionally been addressed independently in wireless cellular networks. The discussion taken into consideration in this study was to analyze the wireless cellular technologies with the contrast of efficient and enhanced spectral densities at a reduced cost. To accomplish the goal of this study, Welch's method has been used as the core subject. With the aid of previous research and classical techniques, this study has identified that the spectral densities can be enhanced at reduced costs with the help of the power spectral estimation methods. The Welch method gives the result on power spectrum estimation. By reducing the effect of noise, the Welch method is used to calculate the power spectral density of a signal. When data length is increased, Welch's method is considered the best as a conclusion to this paper because excellent results are yielded by it in the area of power spectral density estimation. [ABSTRACT FROM AUTHOR]

Wireless networks constitute a significant attack vector for adversaries due to their wide usage in our everyday life. As the fifth generation of wireless networks reaches maturity, several vulnerabilities affecting earlier generations have been resolved. Nevertheless the coexistence of legacy wireless technologies is giving rise to the risk of allowing adversaries to perform downgrade attacks, thus bypassing the improved security of the state-of-the-art communication networks. Vulnerabilities due to the trade-off between security and usability could also exist in the latest wireless networking technologies; hence mobile network operators need to be aware of the risks related to both protocol vulnerabilities and configuration defects. This paper proposes a methodology for the systematic identification of vulnerabilities associated with wireless access protocols and systems and the quantitative evaluation of the resulting risks for mobile operators using attack trees, while considering the current legislative frameworks. The proposed methodology has been designed to aid both, mobile operators towards planning more effective cybersecurity strategies and adopting efficient defences to minimise the probability of an attack and predict its impact on the operational, market and business aspects of mobile network operators. The proposed risk assessment analysis is evaluated over three distinct vertical scenarios, namely an emergency call, a high-speed train commute and a massive public event, with the most relevant threats and their impact being measured and discussed. The evaluation of the model revealed significant results for mobile network operators that are deploying a mix of legacy and state of the art cellular technologies.

Device-to-Device (D2D) communication is considered to be a promising form of technology to distribute video contents to nearby users and devices at a high data rate and with few delays. In this paper, we propose utilizing the D2D services and cache of mobile devices as a bootstrapping system in a cellular network. The main objective of a bootstrapping-D2D (BD2D) system is to improve the quality of service in terms of achieving the minimum startup-time of popular video files in a cellular network. To achieve our objective, we propose a new caching concept for D2D communication in which each mobile device can cache and share the initial video portion or initial segments of the popular video files to other proximate users via a D2D communication link. We formulate an optimization problem that maximizes the cache-hit ratio of initial segments of the most popular video contents. The basic aim is to move the initial segments as close as possible to the wireless users. We also propose a network-assisted D2D architecture called mobile content delivery network-assisted-BD2D and algorithms that assist the BD2D system in the discovery of devices that have cached the initial segments of the requested video files, in cache placement decisions, and also in the registration of potential D2D devices at the core network. We evaluate the performance of the BD2D system and propose algorithms through extensive simulations under real wireless network conditions, such as interference, fading, and shadowing. Our concluding simulation results demonstrate that bootstrapping the initial segments using the short range BD2D system can significantly reduce the average startup-time of video files in comparison with bootstrapping the initial segments from the traditional cellular system.

During the phase of the Base Station (BS) deployment, the BS placement, as an essential issue in achieving seamless coverage of the existing, even the future version of cellular networks, should be attached extensive attention. The ignorance of the geometric distribution of the candidate sites results in negative impact on the performance of traditional meta-heuristic algorithms related to the base station placement problem. A novel geometry-induced genetic algorithm is proposed as an efficient solution to the problem based on both the local coverage evaluation and the local geometric site pattern reservation. The deployment region is divided into sub-regions and the site assignment in the sub-regions is encoded to geometry-aware chromosome segment, which reflects the geometric correlation among the BSs. In the crossover operation, the segments of the chromosomes, while representing the sites inside a sub-region, are exchanged as a whole. In the mutation operation, the overall coverage performance witnesses improvement with the gradual decoration of the poor sub-regions. The experiments for both the ideal disk coverage model and the real radio signal coverage model are executed. The results prove the validity and the efficiency of the proposed algorithms.

As one of the most critical elements in the hydrological cycle, real-time and accurate rainfall measurement is of great significance to flood and drought disaster risk assessment and early warning. Using commercial microwave links (CMLs) to conduct rainfall measure is a promising solution due to the advantages of high spatial resolution, low implementation cost, near-surface measurement, and so on. However, because of the temporal and spatial dynamics of rainfall and the atmospheric influence, it is necessary to go through complicated signal processing steps from signal attenuation analysis of a CML to rainfall map. This article first introduces the basic principle and the revolution of CML-based rainfall measurement. Then, the article illustrates different steps of signal process in CML-based rainfall measurement, reviewing the state of the art solutions in each step. In addition, uncertainties and errors involved in each step of signal process as well as their impacts on the accuracy of rainfall measurement are analyzed. Moreover, the article also discusses how machine learning technologies facilitate CML-based rainfall measurement. Additionally, the applications of CML in monitoring phenomena other than rain and the hydrological simulation are summarized. Finally, the challenges and future directions are discussed.

To guarantee that all mobile users in a cell can watch video with acceptable quality, conventional multicast IPTV services use the most robust modulation and coding scheme (MCS) for video transmission, resulting in worse spectral efficiency. To enhance the spectral efficiency, the adaptive multicast IPTV using the adaptive MCS based on signal-to-noise ratios (SNRs) or channel quality indicators (CQIs) was proposed in the literature. However, the CQI feedback messages induced by the adaptive multicast IPTV incur additional signaling overhead. Thus, a novel CQI feedback scheme was proposed in this paper to effectively decrease the amount of CQI feedback messages while preserving the system performance. Additionally, the CQI feedback rates of various CQI feedback schemes were theoretically analyzed based on the multi-dimensional Markovian model. Numerical results show that the proposed CQI feedback mechanism significantly reduces the CQI feedback rate without sacrificing the system performance and outperforms other existing CQI feedback schemes. Moreover, the analytical results almost coincide with simulation results, demonstrating that the theoretic analyses are accurate. [ABSTRACT FROM AUTHOR]

The evolution of the global wireless market is accompanied by an increased need in terms of speed and number of users, lower latency, better coverage, better spectral efficiency and quality of service, etc. To meet these needs, 5G has recently been introduced as an effective solution which targets, via the large scale deployment of symmetric antennas, a wide variety of sectors such as energy, health, media, industry, transport and especially wireless cellular networks which are among the most important pillars of modern societies. Multiple Input, Multiple Output (MIMO) systems, which have been extended to “Massive MIMO” mode and which consist of increasing the number of radiating elements involved in the transmission and reception of the radio link, are a very promising solution for improving the spectral efficiency of wireless communication systems (WCSs). Motivated by the aforementioned developments, the present paper investigates the increased capacity of MIMO systems to improve transmission in WCSs using 5G. It carefully focuses on the evaluation of the development level and technical contribution of MIMO systems and millimeter wave (mmWave) bands in 5G wireless cellular networks (WCNs) and gives important recommendations.

This paper provides an analytical performance characterization of both the uplink (UL) and downlink (DL) user-centric network multiple-input multiple-output (MIMO) systems, where a cooperating base station (BS) cluster is formed for each user individually and the clusters for different users may overlap. In this model, cooperating BSs (each equipped with multiple antennas) jointly perform zero-forcing beamforming to the set of single-antenna users associated with them. As compared with a baseline network MIMO system with disjoint BS clusters, the effect of user-centric clustering is that it improves signal strength in both the UL and DL, while reducing cluster-edge interference in the DL. This paper quantifies these effects by assuming that BSs and users form Poisson point processes and by further approximating both the signal and interference powers using Gamma distributions of appropriate parameters. We show that BS cooperation provides significant gain as compared to single-cell processing for both the UL and DL, but the advantage of user-centric clustering over the baseline disjoint clustering system is significant for the DL cluster-edge users only. Although the analytic results are derived with the assumption of perfect channel state information and infinite backhaul between the cooperating BSs, they nevertheless provide architectural insight into the design of the future cooperative cellular networks. [ABSTRACT FROM AUTHOR]

A base-station (BS) equipped with multiple antennas can use its spatial dimensions in three different ways: 1) to serve multiple users, thereby achieving a multiplexing gain; 2) to provide spatial diversity in order to improve user rates; and 3) to null interference in neighboring cells. This paper answers the following question: What is the optimal balance between these three competing benefits? We answer this question in the context of the downlink of a cellular network, where multi-antenna BSs serve multiple single-antenna users using zero-forcing beamforming with equal power assignment, while nulling interference at a subset of out-of-cell users. Any remaining spatial dimensions provide transmit diversity for the scheduled users. Utilizing tools from stochastic geometry, we show that, surprisingly, to maximize the per-BS ergodic sum rate, with an optimal allocation of spatial resources, interference nulling does not provide a tangible benefit. The strategy of avoiding inter-cell interference nulling, reserving some fraction of spatial resources for multiplexing, and using the rest to provide diversity, is already close-to-optimal in terms of the sum-rate. However, interference nulling does bring significant benefit to cell-edge users, particularly when adopting a range-adaptive nulling strategy where the size of the cooperating BS cluster is increased for cell-edge users. [ABSTRACT FROM AUTHOR]

Unicast Internet protocol television (IPTV) services that can support live TV, video-on-demand, video conferencing, and online gaming applications over broadband wireless cellular networks have been becoming popular for many years. However, video streaming services significantly impact the performance of wireless cellular networks because they are bandwidth hogs. To maintain the system performance, effective admission control and resource allocation mechanisms based on an accurate mathematical analysis are required. On the other hand, the quality of a wireless link usually changes with time because of user mobility or time-varying channel characteristics. To counteract such time-varying channels and improve the spectral efficiency, an adaptive modulation and coding (AMC) scheme is adopted in offering unicast IPTV services for mobile users. In this paper, closed-form solutions for the bandwidth usage, blocking rate, and dropping rate of unicast IPTV services over wireless cellular networks were derived based on the novel queueing model that considers AMC. Simulations were also conducted to validate the accuracy of analytical results. Numerical results demonstrate that the presented analytical results are accurate. Based on the accurate closed-form solutions, network providers can implement precise admission control and resource allocation for their networks to enhance the system performance. [ABSTRACT FROM PUBLISHER]

Uplink transmission power control is an essential task in Wireless Cellular Networks (WCNs) due to the resource limitation of the Mobile Stations (MSs). One remaining problem is the effect of the delay caused by measuring the signal strength and decision making in the Inner-Loop Power Control (ILPC). In this article, we develop the Potential Feedback Controller (PFC) for a linear scalar discrete-time system with disturbance in order to take into account an unknown bounded time-varying input delay for uplink ILPC. The main interest of the PFC is to treat easily a stabilization problem with a constraint on the state space by using a nonlinear feedback control with a short computation time. Simulations illustrate that by applying the PFC, the communication connectivity is ensured by maintaining the signal strength above a required limit. [ABSTRACT FROM AUTHOR]

Explicit derivation of interferences in hexagonal wireless networks has been widely considered intractable and requires extensive computations with system level simulations. In this paper, we fundamentally tackle this problem and explicitly evaluate the downlink interference-to-signal ratio (ISR) for any mobile location $m$ in a hexagonal wireless network, whether composed of omni-directional or tri-sectorized sites. The explicit formula of ISR is a very convergent series on $m$ and involves the use of Gauss hypergeometric and Hurwitz Riemann zeta functions. Besides, we establish simple identities that well approximate this convergent series and turn out quite useful compared to other approximations in literature. The derived expression of ISR is easily extended to any frequency reuse pattern. Moreover, it is also exploited in the derivation of an explicit form of SINR distribution for any arbitrary distribution of mobile user locations, reflecting the spatial traffic density in the network. Knowing explicitly about interferences and SINR distribution is very useful information in capacity and coverage planning of wireless cellular networks and particularly for macro-cells’ layer that forms almost a regular point pattern. [ABSTRACT FROM PUBLISHER]

In this paper, two different models for permanent user channel assignment, based on Markov chain, are proposed for wireless cellular networks. Both models include channels for calling, handover, and permanent assignment. Models in this paper provide comparison of the blocking probabilities and handover failure probabilities after introducing the permanent user channel assignment, further permanent user channel blocking probability is also derived. Based on the blocking probability results, risk analysis to predict the blocked channels is provided at the end of this paper using the @Risk tool. The simulation results are provided in two parts, i.e. (1) the probability curves against the number of assigned channels are shown and (2) the results using @Risk tool for the risk analysis are shown. [ABSTRACT FROM PUBLISHER]

This paper proposes a Prioritized New Call Threshold Policy for Call Admission Control schemes. It is known that connection reattempts negatively affect the system performance. In currently proposed policy, the system's performance is improved by decreasing the number of connection reattempts. In order to demonstrate that the proposed scheme is better than the traditionally utilized ones in terms of various parameters, the simulations were utilized. It predicts the time that the mobile station will spend in the current cell, mobile station with different remaining time will have different number of channels available for them. More channels are available for the new calls with higher remaining time. Simulations were used in order to show that the proposed scheme outperforms the traditionally employed mechanisms in terms of various parameters. [ABSTRACT FROM AUTHOR]

The objective of this paper is to establish a theoretical expression of the link performance in the downlink of a multiple input multiple output (MIMO) cellular network and compare it to the real Long-Term Evolution (LTE ) performance. In order to account for the interference, we prove that the worst additive noise process in the MIMO context is the white Gaussian one. Based on this theoretical result, we build an analytic expression of the link performance in LTE cellular networks with MIMO. We study also the minimum mean square error (MMSE) scheme currently implemented in the field, as well as its improvement MMSE-SIC (successive interference cancellation) known to achieve the MIMO capacity. Comparison to simulation results as well as to measurements in the field shows that the theoretical expression predicts well practical link performance of LTE cellular networks. This theoretical expression of link performance is the basis of a global analytic approach to the evaluation of the quality of service perceived by the users in the long run of their arrivals and departures. [ABSTRACT FROM AUTHOR]

The majority of call admission control schemes proposed for wireless cellular networks do not take new call redials into account. However, connection reattempts are known to have a negative impact on the system performance because they generate more load. In this paper, we shall investigate how some popular call admission control schemes perform under more realistic conditions. [ABSTRACT FROM AUTHOR]

Recently, as it can greatly increase the capacity of cellular networks through spatial diversity, cooperative communications has been obtaining more and more attention. As a widely used schema, user (user equipment, UE) cooperation presents its advantage. However, due to the users' selfish nature, UE may be unwilling to serve as a relay node if they cannot obtain a corresponding reward. On the contrary, to save energy for longer standby time, particularly when there is energy shortage, many source users would like to purchase the relay service from other idle UE. Therefore, reconciling the demand of both sides is a challenging problem to be resolved. In this paper, a realistic double-auction scenario is constructed between multiple source UE and multiple idle UE in a cellular network. We take the avaricious psychology of network entities into consideration by determining the ask and bid prices through a markup, which is the function of their residual energy. To solve this double-auction-based optimal relay assignment problem, we transform it into maximum matching (MM) and maximum weighted matching (MWM) problems, respectively, and we solve them by corresponding algorithms. Experimental results show that the proposed algorithms dramatically maximize the system performance involving successful source–relay pairs, system throughput, and social welfare (SW), compared with other idealized truthful double-auction scheme that only consider the system throughput. [ABSTRACT FROM PUBLISHER]

The densification and expansion of wireless networks pose new challenges on energy efficiency. With a drastic increase of infrastructure nodes (e.g. ultradense deployment of small cells), the total energy consumption may easily exceed an acceptable level. While most studies focus on the energy radiated by the antennas, the bigger part of the total energy budget is actually consumed by the hardware (e.g., coolers and circuit energy consumption). The ability to shut down infrastructure nodes (or parts of it) or to adapt the transmission strategy according to the traffic will therefore become an important design aspect of energy-efficient wireless ?architectures. Network infrastructure should be ?regarded as a resource that can be occupied or released on demand, and the modeling and optimization of such systems are highly nontrivial problems. In particular, elements of the network infrastructure should be released by taking into account traffic forecasts to avoid losing the required coverage and capacity. However, even if traffic profiles were perfectly known, the determination of the elements to be released is complicated by the potential interference coupling between active elements and the sheer size of the optimization problems in dense networks. [ABSTRACT FROM PUBLISHER]

The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream; first by delivering wireless access to voice communications, then by providing wireless data services, and recently by delivering a Wi-Fi-like experience with wide-area coverage and user mobility management. The support for high data rates has been the main objective in recent years [1], as seen from the academic focus on sum-rate optimization and the efforts from standardization bodies to meet the peak rate requirements specified in IMT-Advanced. In contrast, a variety of metrics/objectives are put forward in the technological preparations for fifth-generation (5G) networks: higher peak rates, improved coverage with uniform user experience, higher reliability and lower latency, better energy efficiency (EE), lower-cost user devices and services, better scalability with number of devices, etc. These multiple objectives are coupled, often in a conflicting manner such that improvements in one objective lead to degradation in the other objectives. Hence, the design of future networks calls for new optimization tools that properly handle the existence of multiple objectives and tradeoffs between them. [ABSTRACT FROM PUBLISHER]

Cloud radio access networks (C-RANs) provide a novel architecture for next-generation wireless cellular systems whereby the baseband processing is migrated from the base stations (BSs) to a control unit (CU) in the ?cloud.? The BSs, which operate as radio units (RUs), are connected via fronthaul links to the managing CU. The fronthaul links carry information about the baseband signals?in the uplink from the RUs to the CU and vice versa in the downlink?in the form of quantized in-phase and quadrature (IQ) samples. Due to the large bit rate produced by the quantized IQ signals, compression prior to transmission on the fronthaul links is deemed to be of critical importance and is receiving considerable attention. This article provides a survey of the work in this area with emphasis on advanced signal processing solutions based on network information theoretic concepts. Analysis and numerical results illustrate the considerable performance gains to be expected for standard cellular models. [ABSTRACT FROM PUBLISHER]

Fifth-generation (5G) networks will be the first generation to benefit from location information that is sufficiently precise to be leveraged in wireless network design and optimization. We argue that location information can aid in addressing several of the key challenges in 5G, complementary to existing and planned technological developments. These challenges include an increase in traffic and number of devices, robustness for mission-critical services, and a reduction in total energy consumption and latency. This article gives a broad overview of the growing research area of location-aware communications across different layers of the protocol stack. We highlight several promising trends, tradeoffs, and pitfalls. [ABSTRACT FROM PUBLISHER]

To cope with the growing demand for wireless data and to extend service coverage, future fifth-generation (5G) networks will increasingly rely on the use of low-power nodes to support massive connectivity in a diverse set of applications and services [1]. To this end, virtualized and mass-scale cloud architectures are proposed as promising technologies for 5G in which all the nodes are connected via a backhaul network and managed centrally by such cloud centers. The significant computing power made available by the cloud technologies has enabled the implementation of sophisticated signal processing algorithms, especially by way of parallel processing, for both interference management and network provision. The latter two are among the major signal processing tasks for 5G due to an increased level of frequency sharing, node density, interference, and network congestion. This article outlines several theoretical and practical aspects of joint interference management and network provisioning for future 5G networks. A cross-layer optimization framework is proposed for joint user admission, user-base station (BS) association, power control, user grouping, transceiver design, as well as routing and flow control. We show that many of these cross-layer tasks can be treated in a unified way and implemented in a parallel manner using an efficient algorithmic framework called weighted minimum mean squared error (WMMSE). Some recent developments in this area are highlighted and future research directions are identified. [ABSTRACT FROM PUBLISHER]

Current estimates of mobile data traffic in the years to come foresee a 1,000 increase of mobile data traffic in 2020 with respect to 2010, or, equivalently, a doubling of mobile data traffic every year. This unprecedented growth demands a significant increase of wireless network capacity. Even if the current evolution of fourth-generation (4G) systems and, in particular, the advancements of the long-term evolution (LTE) standardization process foresees a significant capacity improvement with respect to third-generation (3G) systems, the European Telecommunications Standards Institute (ETSI) has established a roadmap toward the fifth-generation (5G) system, with the aim of deploying a commercial system by the year 2020 [1]. The European Project named ?Mobile and Wireless Communications Enablers for the 2020 Information Society? (METIS), launched in 2012, represents one of the first international and large-scale research projects on fifth generation (5G) [2]. In parallel with this unparalleled growth of data traffic, our everyday life experience shows an increasing habit to run a plethora of applications specifically devised for mobile devices, (smartphones, tablets, laptops)for entertainment, health care, business, social networking, traveling, news, etc. However, the spectacular growth in wireless traffic generated by this lifestyle is not matched with a parallel improvement on mobile handsets? batteries, whose lifetime is not improving at the same pace [3]. This determines a widening gap between the energy required to run sophisticated applications and the energy available on the mobile handset. A possible way to overcome this obstacle is to enable the mobile devices, whenever possible and convenient, to offload their most energy-consuming tasks to nearby fixed servers. This strategy has been studied for a long time and is reported in the literature under different names, such as cyberforaging [4] or computation offloading [5], [6]. In recent years, a strong impulse to computation offloading has come through cloud computing (CC), which enables the users to utilize resources on demand. The resources made available by a cloud service provider are: 1) infrastructures, such as network devices, storage, servers, etc., 2) platforms, such as operating systems, offering an integrated environment for developing and testing custom applications, and 3) software, in the form of application programs. These three kinds of services are labeled, respectively, as infrastructure as a service, platform as a service, and software as a service. In particular, one of the key features of CC is virtualization, which makes it possible to run multiple operating systems and multiple applications over the same machine (or set of machines), while guaranteeing isolation and protection of the programs and their data. Through virtualization, the number of virtual machines (VMs) can scale on ?demand, thus improving the overall system computational efficiency. Mobile CC (MCC) is a specific case of CC where the user accesses the cloud services through a mobile handset [5]. The major limitations of today?s MCC are the energy consumption associated to the radio access and the latency experienced in reaching the cloud provider through a wide area network (WAN). Mobile users located at the edge of macrocellular networks are particularly disadvantaged in terms of power consumption and, furthermore, it is very difficult to control latency over a WAN. As pointed out in [7]?[9], humans are acutely sensitive to delay and jitter: as latency increases, interactive response suffers. Since the interaction times foreseen in 5G systems, in particular in the so-called tactile Internet [10], are quite small (in the order of milliseconds), a strict latency control must be somehow incorporated in near future MCC. Meeting this constraint requires a deep ?rethinking of the overall service chain, from the physical layer up to virtualization. [ABSTRACT FROM PUBLISHER]

Cloud computing draws significant attention in the information technology (IT) community as it provides ubiquitous on-demand access to a shared pool of configurable computing resources with minimum management effort. It gains also more impact on the communication technology (CT) community and is currently discussed as an enabler for flexible, cost-efficient and more powerful mobile network implementations. Although centralized baseband pools are already investigated for the radio access network (RAN) to allow for efficient resource usage and advanced multicell algorithms, these technologies still require dedicated hardware and do not offer the same characteristics as cloud-computing platforms, i.e., on-demand provisioning, virtualization, resource pooling, elasticity, service metering, and multitenancy. However, these properties of cloud computing are key enablers for future mobile communication systems characterized by an ultradense deployment of radio access points (RAPs) leading to severe multicell interference in combination with a significant increase of the number of access nodes and huge fluctuations of the rate requirements over time. In this article, we will explore the benefits that cloud computing offers for fifth-generation (5G) mobile networks and investigate the implications on the signal processing algorithms. [ABSTRACT FROM PUBLISHER]

It is anticipated that the mobile data traffic will grow 1,000 times higher from 2010 to 2020 with a rate of roughly a factor of two per year [1]. This increasing demand for data in next-generation mobile broadband networks will lead to many challenges for system engineers and service providers. To address these issues and meet the stringent demands in coming years, innovative and practical solutions should be identified that are able to provide higher spectral efficiency, better performance, and broader coverage. Next generations of wireless cellular networks, which are known as fifth generation (5G) or beyond fourth generation (B4G) wireless networks, are expected to produce higher data rates for mobile subscribers in the order of tens of gigabits per second (Gbit/s) and support a wide range of services. Despite the absence of official standards for the 5G, the data rate of 1?Gbit/s per user anywhere for 5G mobile networks is expected to be deployed beyond 2020. [ABSTRACT FROM PUBLISHER]

Fifth-generation (5G) cellular communications promise to deliver the gigabit experience to mobile users, with a capacity increase of up to three orders of magnitude with respect to current long-term evolution (LTE) systems. There is widespread agreement that such an ambitious goal will be realized through a combination of innovative techniques involving different network layers. At the physical layer, the orthogonal frequency division multiplexing (OFDM) modulation format, along with its multiple-access strategy orthogonal frequency division multiple access (OFDMA), is not taken for granted, and several alternatives promising larger values of spectral efficiency are being considered. This article provides a review of some modulation formats suited for 5G, enriched by a comparative analysis of their performance in a ?cellular environment, and by a discussion on their interactions with specific 5G ingredients. The interaction with a massive multiple-input, multiple-output (MIMO) system is also discussed by employing real channel measurements. [ABSTRACT FROM PUBLISHER]