Stacked intelligent metasurfaces (SIMs) and fluid antenna systems (FAS) are emerging technologies for wave-domain and spatial signal manipulation, respectively. This letter proposes a novel joint SIM–FAS communication model in which transmission and reception are performed by a SIM and an FAS, respectively. Using the block-diagonal matrix approximation (BDMA), a closed-form expression for the outage probability is derived, and the SIM phase shifts are optimized to minimize outage. Numerical results validate the analytical accuracy and demonstrate substantial performance gains over conventional benchmark schemes.

Fluid antenna multiple access (FAMA) enables each user to rapidly switch among several closely spaced ports and select the strongest received signal. Although this mechanism offers micro-scale spatial diversity, its behavior in multiuser downlink systems with spatial correlation and linear precoding is not well understood. This paper develops a unified analytical framework for the multiple-input single-output (MISO) downlink with FAMA users served via maximum ratio transmission (MRT) or zero-forcing (ZF). We show that the per-port signal-to-interference ratio (SIR) follows a Beta-prime distribution with parameters (Meff,L), whereMeff=Munder MRT andMeff=M−U+ 1 under ZF, and derive closed-form finite-sum cumulative distribution functions (CDFs) for both cases. We further provide the first analytical characterization of cross-port SIR correlation. Furthermore, we derive rigorous outage probability bounds that tightly bracket the exact performance and become exact in the limiting cases of fully correlated and independent ports. Asymptotic analyses reveal the fundamental diversity orders and tail behavior for each precoder. Numerical results confirm the accuracy of the SIR distributions, correlation model, and outage bounds, and show that MRT achieves weaker port correlation and larger selection gains than ZF when the base station (BS) has ample spatial degrees of freedom. The framework offers explicit guidelines for port configuration and precoder selection in practical FAMA systems.

Stacked intelligent metasurfaces (SIM) transceiver design enables precoding in the wave domain while enjoying reduced energy consumption and hardware cost. On this ground and contrary to previous works studying various achievable rates, we derive the ergodic mutual information (EMI) at the large system region in closed form for SIM-assisted multiple-input-multiple-output (MIMO) systems based on statistical channel state information (CSI). Next, by applying a gradient ascent algorithm, we maximize the EMI with respect to the phase shifts of the two SIMs of the transceiver simultaneously, which saves significant overhead compared to a traditional alternating optimization (AO) approach. Simulations shed light in the performance of the proposed system at the large system limit and provide a comparison under different CSI conditions.

Although reconfigurable intelligent surface (RIS) is a promising technology for shaping the propagation environment, it consists of a single-layer structure within inherent limitations regarding the number of beam steering patterns. Based on the recently revolutionary technology, denoted as stacked intelligent metasurface (SIM), we propose its implementation not only on the base station (BS) side in a massive multiple-input multiple-output (mMIMO) setup but also in the intermediate space between the base station and the users to adjust the environment further as needed. For the sake of convenience, we call the former BS SIM (BSIM), and the latter channel SIM (CSIM). To this end, we achieve hybrid wave-based combining at the BS and wave-based configuration at the intermediate space. Specifically, we propose a channel estimation method with reduced overhead, being crucial for SIM-assisted communications. Next, we derive the uplink sum spectral efficiency (SE) in closed form in terms of statistical channel state information (CSI). Notably, we optimize the phase shifts of both BSIM and CSIM simultaneously by using the projected gradient ascent method (PGAM). Compared to previous works on SIMs, we study the uplink transmission in a mMIMO setup, channel estimation in a single phase, a second SIM at the intermediate space, and simultaneous optimization of the two SIMs. Simulation results show the impact of various parameters on the sum SE, and demonstrate the superiority of our optimization approach compared to the alternating optimization (AO) method.

In this paper, we study the resource allocation problem in multi-RIS-aided outdoor-to-indoor communications. Specifically, we aim to provide geographical fairness to ensure that users in different hotspot areas in a smart city can be served regardless of their location. We consider a scenario where RISs are deployed to extend coverage to indoor users in different buildings where there is limited network accessibility. This design is crucial in smart cities in the context of emergency communication and ubiquitous connectivity since it ensures service availability to as many users as possible independently of the locations. Thus, to achieve geographical fairness, we formulate a max-min fairness problem to maximize the minimum number of users served by each RIS by jointly optimizing the active precoding and RIS-based beamforming subject to power and quality of service constraints. The geographical location of users is directly linked to the RIS which means that users are served by the RIS closest to them. In this case, we ensure that a certain number of users can be supported by each RIS. The formulated problem is a mixed integer nonlinear program, which is challenging to solve directly using methods of convex optimization. Accordingly, we propose an efficient successive convex approximation-based alternating optimization algorithm to tackle the complexity of the formulated problem. The presented results show the performance gain of the proposed design in providing geographical fairness compared to the relevant benchmark schemes.

Stacked intelligent metasurfaces (SIM) is a revolutionary technology, which can outperform its single-layer counterparts by performing advanced signal processing relying on wave propagation. In this work, we exploit SIM to enable transmit precoding and receiver combining in holographic multiple-input multiple-output (HMIMO) communications, and we study the achievable rate by formulating a joint optimization problem of the SIM phase shifts at both sides of the transceiver and the covariance matrix of the transmitted signal. Notably, we propose its solution by means of an iterative optimization algorithm that relies on the projected gradient method, and accounts for all optimization parameters simultaneously. We also obtain the step size guaranteeing the convergence of the proposed algorithm. Simulation results provide fundamental insights such the performance improvements compared to the single-RIS counterpart and conventional MIMO system. Remarkably, the proposed algorithm results in the same achievable rate as the alternating optimization (AO) benchmark but with a less number of iterations.

Reconfigurable intelligent surface (RIS) has emerged as a cost-effective solution to improve wireless communication performance through just passive reflection. Recently, the concept of simultaneously transmitting and reflecting RIS (STAR-RIS) has appeared but the study of minimum signal-to-interference-plus-noise ratio (SINR) and the impact of hardware impairments (HWIs) remain open. In addition to previous works on STAR-RIS, we consider a massive multiple-input multiple-output (mMIMO) base station (BS) serving multiple user equipments (UEs) at both sides of the RIS. Specifically, in this work, focusing on the downlink of a single cell, we derive the minimum SINR obtained by the optimal linear precoder (OLP) with HWIs in closed form. The OLP maximises the minimum SINR subject to a given power constraint for any given passive beamforming matrix (PBM). Next, we obtain deterministic equivalents (DEs) for the OLP and the minimum SINR, which are then used to optimise the PBM. Notably, based on the DEs and statistical channel state information (CSI), we optimise simultaneously the amplitude and phase shift by using a projected gradient ascent algorithm (PGAM) for both energy splitting (ES) and mode switching (MS) STAR-RIS operation protocols with reduced feedback, which is quite crucial for STAR-RIS systems that include the double number or variables compared to reflecting only RIS. Simulations verify the analytical results, shed light on the impact of HWIs, and demonstrate the better performance of STAR-RIS compared to conventional RIS. Also, a benchmark full instantaneous CSI (I-CSI) based design is provided and shown to result in higher SINR but lower net achievable sum-rate than the statistical CSI based design because of large overhead associated with the acquisition of full I-CSI acquisition. Thus, not only do we evaluate the impact of HWIs but we also propose a statistical CSI based design that provides higher net sum-rate with low overhead and complexity.

Reconfigurable intelligent surfaces (RIS)-assisted massive multiple-input multiple-output (mMIMO) is a promising technology for applications in next-generation networks. However, reflecting-only RIS provides limited coverage compared to a simultaneously transmitting and reflecting RIS (STAR-RIS). Hence, in this paper, we focus on the downlink achievable rate and its optimization of a STAR-RIS-assisted mMIMO system. Contrary to previous works on STAR-RIS, we consider mMIMO, correlated fading, and multiple user equipments (UEs) at both sides of the RIS. In particular, we introduce an estimation approach of the aggregated channel with the main benefit of reduced overhead links instead of estimating the individual channels. Next, leveraging channel hardening in mMIMO and the use-and-forget bounding technique, we obtain an achievable rate in closed-form that only depends on statistical channel state information (CSI). To optimize the amplitudes and phase shifts of the STAR-RIS, we employ a projected gradient ascent method (PGAM) that simultaneously adjusts the amplitudes and phase shifts for both energy splitting (ES) and mode switching (MS) STAR-RIS operation protocols. By considering large-scale fading, the proposed optimization can be performed every several coherence intervals, which can significantly reduce overhead. Considering that STAR-RIS has twice the number of controllable parameters compared to conventional reflecting-only RIS, this accomplishment offers substantial practical benefits. Simulations are carried out to verify the analytical results, reveal the interplay of the achievable rate with fundamental parameters, and show the superiority of STAR-RIS regarding its achievable rate compared to its reflecting-only counterpart.

This paper focuses on the fundamental problem of maximizing the achievable weighted sum rate (WSR) at information receivers (IRs) in an intelligent reflecting surface (IRS) assisted simultaneous wireless information and power transfer system under a multiple-input multiple-output (SWIPT-MIMO) setting, subject to a quality-of-service (QoS) constraint at the energy receivers (ERs). Notably, due to the coupling between the transmit precoding matrix and the passive beamforming vector in the QoS constraint, the formulated non-convex optimization problem is challenging to solve. We first decouple the design variables in the constraints following a penalty dual decomposition method, and then apply an alternating gradient projection algorithm to achieve a stationary solution to the reformulated optimization problem. The proposed algorithm nearly doubles the WSR compared to that achieved by a block-coordinate descent (BCD) based benchmark scheme. At the same time, the complexity of the proposed scheme grows linearly with the number of IRS elements while that of the benchmark scheme is proportional to the cube of the number of IRS elements.

Intelligent reflecting surface (IRS), consisting of low-cost passive elements, is a promising technology for improving the spectral and energy efficiency of the fifth-generation (5G) and beyond networks. It is also noteworthy that an IRS can shape the reflected signal propagation. Most works in IRS-assisted systems have ignored the impact of the inevitable residual hardware impairments (HWIs) at both the transceiver hardware and the IRS while any relevant works have addressed only simple scenarios, e.g., with single-antenna network nodes and/or without taking the randomness of phase noise at the IRS into account. In this work, we aim at filling up this gap by considering a general IRS-assisted multi-user (MU) multiple-input single-output (MISO) system with imperfect channel state information (CSI) and correlated Rayleigh fading. In parallel, we present a general computationally efficient methodology for IRS reflecting beamforming (RB) optimization. Specifically, we introduce an advantageous channel estimation (CE) method for such systems accounting for the HWIs. Moreover, we derive the uplink achievable spectral efficiency (SE) with maximal-ratio combining (MRC) receiver, displaying three significant advantages being: 1) its closed-form expression, 2) its dependence only on large-scale statistics, and 3) its low training overhead. Notably, by exploiting the first two benefits, we achieve to perform optimization with respect to the RB that can take place only per several coherence intervals, and thus, reduces significantly the computational cost compared to other methods based on instantaneous CSI which require frequent phase optimization. Among the insightful observations, we highlight that the unrealistic assumption of uncorrelated Rayleigh fading does not allow optimization of the SE, which makes the application of an IRS ineffective. Also, in the case that the phase drifts, describing the distortion of the phases in the RBM, are uniformly distributed, the presence of an IRS provides no advantage. The analytical results outperform previous works and are verified by Monte-Carlo (MC) simulations.

Although the intelligent reflecting surface (IRS) has attracted significant interest, existing works have not addressed adequately the impact of its inevitable phase errors by taking into account their randomness. In this work, we focus on covering this gap by considering a general large IRS-assisted multi-user (MU) multiple-input single-output (MISO) system with imperfect CSI and correlated Rayleigh fading. On this ground, we perform a beneficial channel estimation (CE), and we obtain the achievable sum spectral efficiency (SE) in closed-form in terms of the large-scale channel statistics. The whole approach suggests a novel computationally efficient method for reflect beamforming matrix (RBM) optimization of IRS-assisted large multi-antenna systems that can take place at every several coherence intervals. Monte-Carlo simulations verify the analytical insightful results. Among the observations, we highlight that if the IRS phase noise follows the uniform distribution or if independent Rayleigh fading is assumed, the use of the IRS has no benefit.

Abstract Hybrid processing in millimeter wave (mmWave) communication has been proposed as a solution to reduce the cost and energy consumption by reducing the number of radio‐frequency (RF) chains. However, the impact of the inevitable residual transceiver hardware impairments (RTHIs), including the residual additive transceiver hardware impairments (RATHIs) and the amplified thermal noise (ATN), has not been sufficiently studied in mmWave hybrid processing. In this work, the hybrid precoder and combiner are designed, which include both digital and analog processing by taking into account the RATHIs and the ATN. In particular, a thorough study is provided to shed light on the degradation of the spectral efficiency (SE) of the practical system. The outcomes show the steady degradation of the performance by the ATN across all SNR values, which becomes increasingly critical for higher values of its variance. Furthermore, it is shown that RATHIs result in degradation of the system only in the high SNR regime. Hence, their impact in mmWave system operating at low SNRs might be negligible. Moreover, an increase concerning the number of streams differentiates the impact between the transmit and receive RATHIs with the latter having a more severe effect.

Despite the deleterious effect of hardware impairments (HWIs) on wireless systems, most prior works in cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems have not accounted for their impact. In particular, the effect of phase noise (PN) has not been investigated at all in CF systems. Moreover, there is no work investigating HWIs in scalable CF (SCF) mMIMO systems, encountering the prohibitively demanding fronthaul requirements of large networks with many users. Hence, we derive the uplink spectral efficiency (SE) under HWIs with minimum mean-squared error (MMSE) combining in closed-form by means of the deterministic equivalent (DE) analysis. Notably, previous works, accounted for MMSE decoding, studied the corresponding SE only by means of simulations. Numerical results illustrate the performance loss due to HWIs and result in insightful conclusions.

The increasing demand for green wireless communications and the benefits of the promising cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems towards their optimal energy efficiency (EE) are the focal points of this work. Specifically, despite previous works assuming a uniform placement for the access points (APs), we consider that their locations follow a Poisson point process (PPP) which approaches their opportunistic spatial randomness. Based on stochastic geometry, we derive a lower bound on the average spectral efficiency, and under a realistic power consumption model for CF mMIMO systems, we formulate an EE maximization problem achieving to obtain in closed form the optimal EE per unit area in terms of the pilot reuse factor and the AP density. Note that we have defined the EE per unit area and not just the EE to characterize the energy in systems with multi-point transmission. Thus, we provide important design insights for energy-efficient CF mMIMO systems.

Given that fifth generation (5G) networks suggest heterogeneous networks (HetNets) design and millimeter-wave (mmWave) transmission as promising technologies to achieve its vision, we consider the downlink of a multi-user multiple-input multiple-output (MU-MIMO) HetNet operating at the region of mmWave frequencies. Actually, by focusing on a realistic assessment, the proposed framework includes the effects of channel aging, residual additive transceiver hardware impairments (RATHIs), and amplified thermal noise (ATN). After providing the definition of the coverage probability for this novel synergy between HetNets and mmWave transmission with its special characteristics under realistic conditions, we proceed with its derivation. Monte Carlo simulations verify the analytical results that allow to quantify the degradation obtained in this new paradigm, and provide interesting design insights. Hence, among others, we determine the degradation of the system due to channel aging, and we demonstrate that the RATHIs play a significant role in the high signal-to-noise ratio (SNR) regime.

Small-cell densification is a strategy enabling the offloading of users from macro base stations (MBSs), in order to alleviate their load and increase the coverage, especially, for cell-edge users. In parallel, as the network increases in density, the BS cooperation emerges as an efficient design method towards the demands for drastic improvement of the system performance against the detrimental overall interference. We, therefore, model and scrutinize a heterogeneous network (HetNet) of two tiers (macro and small cells) with multiple-antenna BSs serving a multitude of users, which differ with respect to their basic design parameters, e.g., the deployment density, the number of transmit antennas, and transmit power. In addition, the tiers are enhanced with cell association policies by introducing the concept of the association probability. Above this and motivated by the advantages of cooperation among BSs, the small base stations (SBSs) are enriched with this property in their design. The SBS cooperation allows shedding light into its impact on the cell selection rules in multi-antenna HetNets. Under these settings, software-defined networking (SDN) is introduced smoothly to play the leading role in the orchestration of the network. In particular, heavy operations such as the coordination and the cell association are undertaken by virtue of an SDN controller performing and managing efficiently the corresponding computations due to its centralized adaptability and dynamicity towards the enhancement and potential scalability of the network. In this context, we derive the coverage probability and the mean achievable rate. Not only we show the outperformance of BS cooperation over uncoordinated BSs, but we also demonstrate that the SBS cooperation enables the admittance of more users from the macro-cell BSs (MBSs). Furthermore, we show that by increasing the number of BS antennas, the system performance is improved as the metrics under study reveal. Moreover, we investigate the performance of different transmission techniques, and we identify the optimal bias in each case when SBSs cooperate. Finally, we depict that the SBS densification is beneficial until a specific density value since a further increase does not increase the coverage probability.

A notable commonality in the existing studies on millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems is the assumption of perfect hardware during communication. However, this is a strong hypothesis since residual tranceiver hardware impairments (RTHIs) are inevitable in reality. Hence, this paper proposes a mmWave MIMO system that generalizes the state of the art by considering the inevitable RTHIs. We shed light on the impact of three major hardware impairments, namely, the multiplicative phase noise (PN), the amplified thermal noise (ATN), and the residual additive transceiver hardware impairments (RATHIs). In particular, we derive the spectral efficiency of the system under the presence of RTHIs. Additionally, we provide a detailed analysis to quantify the degradation caused to the spectral efficiency of the system by each separate impairment. Among the noteworthy outcomes is that the multiplicative PN is the most critical of the three impairments. Furthermore, we verify that the merits of the mmWave MIMO system are improved in line with large MIMO, which needs to be deployed in a cost-efficient manner.

Despite the importance of Rayleigh-product multiple-input multiple-output channels and their experimental validations, there is no work investigating their performance in the presence of residual additive transceiver hardware impairments, which arise in practical scenarios. Hence, this paper focuses on the impact of these residual imperfections on the ergodic channel capacity for optimal receivers, and on the ergodic sum rates for linear minimum mean-squared-error (MMSE) receivers. Moreover, the low- and high-signal-to-noise ratio cornerstones are characterized for both types of receivers. Simple closed-form expressions are obtained that allow the extraction of interesting conclusions. For example, the minimum transmit energy per information bit for optimal and MMSE receivers is not subject to any additive impairments. In addition to the exact analysis, we also study the Rayleigh-product channels in the large system regime, and we elaborate on the behavior of the ergodic channel capacity with optimal receivers by varying the severity of the transceiver additive impairments.

Relay systems improve both coverage and system capacity. Toward this direction, a full-duplex (FD) technology, being able to boost the spectral efficiency by transmitting and receiving simultaneously on the same frequency and time resources, is envisaged to play a key role in future networks. However, its benefits come at the expense of self-interference (SI) from their own transmit signal. At the same time, massive multiple-input massive multiple-output systems, bringing unconventionally many antennas, emerge as a promising technology with huge degrees-of-freedom. To this end, this paper considers a multi-pair decode-and-forward FD relay channel, where the relay station is deployed with a large number of antennas. Moreover, the rate-splitting (RS) transmission has recently been shown to provide significant performance benefits in various multi-user scenarios with imperfect channel state information at the transmitter (CSIT). Engaging the RS approach, we employ the deterministic equivalent analysis to derive the corresponding sum-rates in the presence of interferences. Initially, numerical results demonstrate the robustness of RS in half-duplex (HD) systems, since the achievable sum-rate increases without bound, i.e., it does not saturate at high signal-to-noise ratio. Next, we tackle the detrimental effect of SI in FD. In particular, and most importantly, not only FD outperforms HD, but also RS enables increasing the range of SI over which FD outperforms HD. Furthermore, increasing the number of relay station antennas, RS appears to be more efficacious due to imperfect CSIT, since SI decreases. Interestingly, increasing the number of users, the efficiency of RS worsens and its implementation becomes less favorable under these conditions. Finally, we verify that the proposed DEs, being accurate for a large number of relay station antennas, are tight approximations even for realistic system dimensions.

A significant burden on wireless networks is brought by the uploading of user-generated contents to the Internet by means of applications such as social media. To cope with this mobile data tsunami, we develop a novel multiple-input multiple-output (MIMO) network architecture with randomly located base stations (BSs) a large number of antennas employing cache-enabled uplink transmission. In particular, we formulate a scenario, where the users upload their content to their strongest BSs, which are Poisson point process distributed. In addition, the BSs, exploiting the benefits of massive MIMO, upload their contents to the core network by means of a finite-rate backhaul. After proposing the caching policies, where we propose the modified von Mises distribution as the popularity distribution function, we derive the outage probability and the average delivery rate by taking advantage of tools from the deterministic equivalent and stochastic geometry analyses. Numerical results investigate the realistic performance gains of the proposed heterogeneous cache-enabled uplink on the network in terms of cardinal operating parameters. For example, insights regarding the BSs storage size are exposed. Moreover, the impacts of the key parameters such as the file popularity distribution and the target bitrate are investigated. Specifically, the outage probability decreases if the storage size is increased, while the average delivery rate increases. In addition, the concentration parameter, defining the number of files stored at the intermediate nodes (popularity), affects the proposed metrics directly. Furthermore, a higher target rate results in higher outage because fewer users obey this constraint. Also, we demonstrate that a denser network decreases the outage and increases the delivery rate. Hence, the introduction of caching at the uplink of the system design ameliorates the network performance.

Full-duplex (FD) systems, suggested to play a key role in future networks, boost the spectral efficiency, although they suffer from self-interference (SI). In parallel, massive multiple-output (MIMO) systems, employing a large number of antennas, emerge as a promising technology offering huge degrees-of-freedom. Hence, after careful consideration, this paper considers a multi-pair decode-and-forward FD relay channel, where the relay station is deployed with a large number of antennas. Also, since the rate-splitting (RS) transmission is applicable in multi-user scenarios, we include it in our analysis in terms of deterministic equivalents. Remarkably, numerical results show the robustness of RS both half-duplex (HD) and FD systems. Moreover, RS increases the range of SI over which FD outperforms HD. Outstandingly, RS proves to be more robust as the number of relay antennas increases.

This work encompasses Rate-Splitting (RS), providing significant benefits in multi-user settings in the context of huge degrees of freedom promised by massive Multiple-Input Multiple-Output (MIMO). However, the requirement of massive MIMO for cost-efficient implementation makes them more prone to hardware imperfections such as phase noise (PN). As a result, we focus on a realistic broadcast channel with a large number of antennas and hampered by the unavoidable PN. Moreover, we employ the RS transmission strategy, and we show its robustness against PN, since the sum-rate does not saturate at high signal-to-noise ratio (SNR). Although, the analytical results are obtained by means of the deterministic equivalent analysis, they coincide with simulation results even for finite system dimensions.

Massive multiple-input multiple-output (MIMO) is a promising technology aiming at achieving high spectral efficiency by deploying a large number of base station (BS) antennas using coherent combining. Channel aging due to user mobility is a significant degrading factor of such systems. In addition, cost efficiency of massive MIMO is a prerequisite for their deployment, that leads to low cost antenna elements inducing high phase noise. Since phase is time-dependent, it contributes to channel aging. For this reason, we present a novel joint channel-phase noise model, that enables us to study the downlink of massive MIMO with maximum ratio transmission (MRT) precoder under these conditions by means of the deterministic equivalent of the achievable sum- rate. Among the noteworthy outcomes is that the degradation due to user mobility dominates over the effect of phase noise. Nevertheless, the impact of phase noise can be eliminated as we increase the number of separate independent local oscillators, i.e., massive MIMO can be robust regarding phase noise.

We consider the uplink of non-cooperative multicellular systems deploying multiple antenna elements at the base stations (BS), covering both the cases of conventional and very large number of antennas. Given the inevitable pilot contamination and an arbitrary path-loss for each link, we address the impact of time variation of the channel due to the relative movement between users and BS antennas, which limits system's performance even if the number antennas is increased, as shown. In particular, we propose an optimal linear receiver (OLR) maximizing the received signal-to-interference-plus-noise (SINR). Closed-form lower and upper bounds are derived as well as the deterministic equivalent of the OLR is obtained. Numerical results reveal the outperformance of the proposed OLR against known linear receivers, mostly in environments with high interference and certain user mobility, as well as that massive MIMO is preferable even in time-varying channel conditions.

This paper investigates the achievable sum-rate of uplink massive multiple-input multiple-output (MIMO) systems considering a practical channel impairment, namely, aged channel state information (CSI). Taking into account both maximum ratio combining (MRC) and zero-forcing (ZF) receivers at the base station, we present tight closed-form lower bounds on the sum-rate for both receivers, which provide efficient means to evaluate the sum-rate of the system. More importantly, we characterize the impact of channel aging on the power scaling law. Specifically, we show that the transmit power of each user can be scaled down by 1/√(M), which indicates that aged CSI does not affect the power scaling law; instead, it causes only a reduction on the sum rate by reducing the effective signal-to-interference-and-noise ratio (SINR).

This paper investigates the achievable sum-rate of massive multiple-input multiple-output (MIMO) systems in the presence of channel aging. For the uplink, by assuming that the base station (BS) deploys maximum ratio combining (MRC) or zero-forcing (ZF) receivers, we present tight closed-form lower bounds on the achievable sum-rate for both receivers with aged channel state information (CSI). In addition, the benefit of implementing channel prediction methods on the sum-rate is examined, and closed-form sum-rate lower bounds are derived. Moreover, the impact of channel aging and channel prediction on the power scaling law is characterized. Extension to the downlink scenario and multicell scenario is also considered. It is found that, for a system with/without channel prediction, the transmit power of each user can be scaled down at most by 1/√M (where M is the number of BS antennas), which indicates that aged CSI does not degrade the power scaling law, and channel prediction does not enhance the power scaling law; instead, these phenomena affect the achievable sum-rate by degrading or enhancing the effective signal to interference and noise ratio, respectively.

Delayed channel state information at the transmitter (CSIT) due to time variation of the channel, coming from the users' relative movement with regard to the BS antennas, is an inevitable degrading performance factor in practical systems. Despite its importance, little attention has been paid to the literature of multi-cellular multiple-input massive multiple-output (MIMO) system by investigating only the maximal ratio combining (MRC) receiver and the maximum ratio transmission (MRT) precoder. Hence, the contribution of this work is designated by the performance analysis/comparison of/with more sophisticated linear techniques, i.e., a minimum-mean-square-error (MMSE) detector for the uplink and a regularized zero-forcing (RZF) precoder for the downlink are assessed. In particular, we derive the deterministic equivalents of the signal-to-interference-plus-noise ratios (SINRs), which capture the effect of delayed CSIT, and make the use of lengthy Monte Carlo simulations unnecessary. Furthermore, prediction of the current CSIT after applying a Wiener filter allows to evaluate the mitigation capabilities of MMSE and RZF. Numerical results depict that the proposed achievable SINRs (MMSE/RZF) are more efficient than simpler solutions (MRC/MRT) in delayed CSIT conditions, and yield a higher prediction at no special computational cost due to their deterministic nature. Nevertheless, it is shown that massive MIMO are preferable even in time-varying channel conditions.

We consider a realistic cellular multi-user uplink channel with an excess of base station (BS) antennas, where the number of BS antennas and the number of users per cell increase at the same rate. Specifically, we investigate the negative impact of delayed channel state information at the transmitter (CSIT), when a minimum-mean-square-error (MMSE) detector is applied. Nevertheless, channel prediction is used for overcoming delayed CSIT degradation. We provide the asymptotic signal-to-interference-plus-noise ratios (SINRs) that demonstrate not only their dependence on delayed and predicted CSIT, but also the outperformance of MMSE against maximal ratio combiner (MRC). The deterministic nature of the results renders them easily computed, while simulations show their accuracy even for practical system dimensions.

In this work we investigate the degrees of freedom (DoF) performance of the multiple-input multiple-output (MIMO) interference channel (IC) with limited channel state information (CSI) feedback. We generalise two space-time interference alignment (STIA) algorithms to the K user MIMO IC with a transmit power constraint and show how these schemes exploit both current and outdated CSI to achieve an improved DoF performance. We show that by combining the STIA schemes with traditional methods major DoF gain can be achieved for a variety of limited CSI feedback scenarios in comparison to what would be obtained via the use of the traditional techniques on their own. In particular we prove that optimal DoF can still be achieved in situations where current CSI is unavailable for a derived fraction of the time. Finally we validate the promised DoF results via system simulation and show how these DoF gains reflect in terms of sum rate achievable.

This work studies the uplink of a cellular network with zero-forcing (ZF) receivers under imperfect channel state information at the base station. More specifically, apart from the pilot contamination, we investigate the effect of time variation of the channel due to the relative users' movement with regard to the base station. Our contributions include analytical expressions for the sum-rate with finite number of BS antennas, and also the asymptotic limits with infinite power and number of BS antennas, respectively. The numerical results provide interesting insights on how the user mobility degrades the system performance which extends previous results in the literature.

In this paper, we study the degrees of freedom (DoF) of the two-user time-correlated multiple-input-multiple-output (MIMO) interference channel (IC), under realistic assumptions. In particular, the transmitters have imperfect knowledge of the current and the delayed channel state information (CSI). The novelty of this study relies upon the fact that this is the first time, within the literature of IC, that imperfect CSI is addressed for such a case. The delayed CSI at the transmitter (CSIT) is assumed to be more accurate than the current value. We identify the DoF region, which provides an insight on the behaviour of the DoF as a function of the varying qualities of the current and the delayed channel. It is also worth mentioning that any knowledge of imperfect delayed CSIT can also be utilized. Furthermore, an achievability scheme is proposed for each vertex in DoF region. Finally, simulation of the proposed scheme verifies our results.

The ergodic channel capacity (ECC) of single-branch receivers is studied under the scenarios described by means of α-η-μ, α-κ-μ, and α-λ-μ-η generalized fading channels. Novel expressions are derived, which are the most general in this scientific area. Moreover, it is shown that, for any given fading condition, the α-μ ECC divides the fading plane in two regions of capacity, appearing as either lower or upper bound in the α-η-μ and α-κ-μ fading environments. Numerical results are presented to illustrate the proposed mathematical analysis and to examine the effects of the fading severity on the concerned quantities.

Certain practical limitations, such as finite CSI feedback delay, make the knowledge of instantaneous perfect CSI impossible and bring the term of delayed CSIT to the forefront. In this paper, it is described how both current and delayed CSI could be exploited by generalizing the space-time interference alignment transmission algorithm (STIA) to the K (K ≥ 3) user M × N interference channel. Specifically, the degrees of freedom (DoF) gain is characterized as a function of the CSI feedback delay γ and the system parameters (K, M, N). Surprisingly, the DoF become optimal, i.e., no loss is achieved with respect to the case of perfect current CSIT, as far as the normalized CSI feedback delay is less than a specific value dependent on the number of users, and the number of transmit antennas equals to N(K - 1). The proposed algorithm reveals unprecedented properties characterizing the performance of the system by providing the limits of the multiplexing gain with relation to the feedback time delay.

We consider a multi-cell multi-user downlink channel of a time-division duplex (TDD) MIMO system, where the base stations (BSs) employ the concept of massive MIMO, i.e., they are equipped with a large number of antennas. In addition, the number of users increases with the same speed. Focusing on the practical impairments of the channel such as pilot contamination and, in particular, delayed channel state information at the transmitter (CSIT), we derive an approximation of the sum rate with regularized zero-forcing (RZF) precoding, which provides a quantification of the capacity loss. As a result, it is deemed necessary to obtain the deterministic equivalent sum rate by incorporating in our analysis channel prediction circumventing the degradation due to delayed CSIT. The proposed results are accurate for realistic system dimensions, as simulations testify. Finally, we show the benefits of applying RZF in the sum rate against using eigenbeamforming (BF) for the same Doppler shift with no extra computational complexity.

We consider the two-user time correlated multiple-antenna interference channel (IC) under realistic conditions. Specifically, the transmitters have not only perfect delayed channel state information (CSIT), but also asymmetrically imperfect current CSIT. Delayed CSIT, met to cases of practical interest (certain feedback latency and limited quality), can still be useful as shown by Maddah-Ali and Tse. In parallel, the assumption of unequal prediction of current CSIT based on past samples across different links, conduces to the consideration of a more realistic scenario, where different links face different Doppler spread. The degrees of freedom (DoF) region of the IC under these general conditions is obtained and characterized. In particular, we investigate the effects of the asymmetry appearing to different links, such as how the feedback capability of one user affects the other. In addition, the achievability schemes are provided. Finally, Monte Carlo simulation in terms of the sum rate validates the theoretical results and provides deeper insight.

In this paper, a novel general small-scale fading model for wireless communications, that describes the non- homogeneous nature of the propagation medium, is introduced. Its probability density function (PDF) is given by a simple, exact, and closed-form expression. Namely, the η � λ � μ includes the λ � μ ,t heη � μ, the Gamma, the Exponential, the Hoyt, the Nakagami-m, the Rayleigh, and the One-Sided Gaussian distri- butions as special cases. Field measurements and Monte Carlo simulation have been used to validate the proposed distribution. An outperformance has been shown among the widely known fading distributions by fitting to the experimental data.

In this paper, a new, simple, and exact closed-form expression for the envelope-phase joint distribution of a signal, operating in α — μ generalized fading channels, has been derived. The marginal distribution of the phase is also obtained in an exact closed-form expression and studied in depth. The analytical results are general and after suitable simplifications, they are verified mathematically, since they coincide to the respective ones of the models included in the α — μ distribution (i.e., the Nakagami-m, the Weibull, and the Rayleigh distributions for which the corresponding solutions are known). Finally, a sample of numerical results, obtained by the Monte Carlo simulation, is presented in order to validate the formulations developed in this paper.

In this paper, a general fading model for wireless communications is introduced describing the nonlinearity, and at the same time the non-homogeneous nature of the propagation medium. Namely, the a - lambda - mu - eta includes the a - mu , the lambda - mu, the eta - mu, the gamma, the exponential, the Weibull, the Hoyt, the Nakagami-m, the Rayleigh, and the one-sided Gaussian distributions as special cases. Field measurements and Monte Carlo simulation have been used to validate the proposed distribution. An outperformance has been shown among the widely known fading distributions by fitting to the experimental data.