The use of extremely large aperture arrays (ELAAs) in upper-mid frequencies (FR3) extends the Fraunhofer distance to several hundreds of meters. This necessitates wireless channels to be modeled via spherical wavefronts, and performance metrics to be derived in the near-field. This paper hence focuses on evaluating the near-field performance of cell-free massive multiple-input multiple-output (CF-mMIMO)-aided integrated sensing and communication (ISAC) systems. The achievable user rates, Cramér Rao bound, and signal-to-clutter-plus-noise ratio (SCNR) are derived by modeling near-field spatial correlation, imperfect channel estimation, and multiple clutters sources. A transmit power allocation algorithm is also proposed to maximize the weakest user’s rate while satisfying a SCNR threshold. Our numerical results confirm the necessity for near-field analysis of CF-mMIMO-aided ISAC with ELAAs in FR3 band.

Non-wide sense stationarity in the spatial dimension gives rise to partial visibility regions (VR) in the channels pertinent to extra-large (XL) antenna arrays (ELAAs). This paper investigates the detrimental impact of partial VRs for multi-cell XL multiple-input multiple-output (MIMO) non-orthogonal multiple-access (NOMA) systems due to VR-unaware precoding. We present an achievable rate analysis by modeling channels with VRs and hence to capture its effects on the downlink (DL) precoders. This rate analysis considers VR-aware precoding at the ELAAs, and thus, it can be used to study the rate losses due to VR-unaware precoding. This rate analysis also captures adverse effects of erroneously estimated uplink and DL channels, correlated fading, imperfect successive interference cancellation (SIC), and intra-cluster/cell pilot contamination. A VR-aware transmit power optimization is also proposed to achieve a system-wide common user rate across all NOMA clusters. We unveil that full visibility assumption for XL-MIMO leads to overestimation of user rates. To circumvent this, it is advocated to capture partial VRs in channel modeling and invoke VR-aware precoders when ELAAs are deployed to serve distributed NOMA clusters. To minimize the adverse effects of weakened channel hardening due to partial VRs and imperfect SIC at the users, it is also advocated to precode DL pilots such that the users adopt estimated channel state information to decode DL NOMA signals.

An intelligent reflecting surface (IRS) aided cell-free massive multiple-input multiple-output (CF-mMIMO) system with underlay spectrum sharing is investigated. The achievable rates for the primary and secondary users are derived in closed-form by considering imperfectly estimated cascaded channel state information (CSI) through linear minimum mean square error estimation, spatially correlated fading, residual interference caused by underlay spectrum sharing based primary/secondary system deployment, and beamforming/decision uncertainties. An IRS phase-shift optimization problem is formulated to minimize the secondary interference inflicted on the primary system based on the underlay spectrum sharing concept. The proposed phase-shift optimization procedure reduces the pilot overhead and computational complexity as its solution depends solely on statistical CSI. Our achievable rate analysis is validated through Monte-Carlo simulations.

The recently acquired mid-band frequency range (FR3) for 6G necessitates adopting extremely large aperture arrays (ELAAs) to leverage higher array gains and spatial multiplexing gains to compensate for larger path-losses compared to sub-6 GHz band and reduction of bandwidth availability compared to millimeter-waves, respectively. However, the nearfield of ELAAs may extend hundreds of meters depending on the aperture size and operating frequency. Hence, the planarwave based far-field channel models must be replaced by spherical-wave based near-field counterparts. To this end, we analyze the near-field performance of ELAA-based integrated sensing and communications (ISAC). This analysis captures the near-field spatial correlation, partial visibility due to spatially non-wide sense stationarities, erroneous channel estimates, an extended target, and clutter sources. A computationally-efficient conjugate precoding-based superimposed ISAC waveform is used at ELAAs. This waveform is further optimized via transmit power allocation to maximize the minimum achievable rate of the weakest communication user, while satisfying a sensing threshold for target detection. The achievable user rates and a target detector are derived. Our results demonstrate the potential of ELAA-based ISAC to improve the trade-off between the communication and sensing performance metrics.

The transition to millimeter-wave and sub-THz frequency bands necessitates that the base-stations (BSs) utilize extra-large antenna arrays (ELAA) to compensate for the associated huge path-losses. However, when higher frequencies and shorter transmission distances are utilized, the spherical wave curvature can no longer be neglected. Hence, the ELAAbased wireless systems tend to operate primarily in the near-field. Thus, the far-field channel models used for near-field users may detrimentally affect wireless system designs and performance gains. To this end, we investigate the impact of mismatches between far-field and near-field channel models/precoders on the performance of ELAA-based integrated sensing and communication (ISAC). To this end, the achievable user rates are derived for the near-field. Two detectors for sensing a target are designed based on known/unknown BS/target channels. The performance of these detectors are investigated by deriving the probability of detection and probability of false-alarm. A transmit power optimization procedure is also proposed to maximize the minimum achievable user rate, while ensuring a power threshold for sensing. Numerical results are used to study the fundamental trade-off between the probability of detection and achievable rates for near-field ELAA-based ISAC. We unveil that ELAAs can be leveraged to improve the ISAC performance trade-offs.

The performance of cell-free massive multiple-input multiple-output (MIMO)-aided integrated sensing and communication (ISAC) is investigated. Each transmit access point (AP) sends a superimposed ISAC waveform from which the users are able to decode data, while the reflected echos off a target are used at the receive APs to perform sensing functionalities. Each transmit AP adopts a local conjugate precoder, which is designed based on the locally acquired channel state information (CSI) via user pilots. This approach reduces the implementation complexity as it does not necessitate CSI exchanges. An efficient transmit power optimization is also proposed to construct the superimposed ISAC waveform. The performance is evaluated by deriving the achievable user rates and quantifying the two-dimensional MUltiple SIgnal Classification (MUSIC) spectrum function at the receive APs. Our performance analysis captures practical impairments, including erroneously estimated CSI, spatially correlated Rician fading, and clutter interference. Our analytical and numerical results demonstrate the potential of our proposed cell-free massive MIMO aided ISAC systems.

The performance of integrated sensing and communications (ISAC) empowered intelligent reflecting surface (IRS)aided massive multiple-input multiple-output (MIMO) systems operating over spatially correlated Rician fading is investigated. Computationally-efficient linear precoders are used to construct the ISAC signal by invoking the maximal ratio transmission (MRT) criterion into the composite channels containing both direct and IRS reflected channels. The uplink communication channels are estimated based on the linear minimum mean square error criterion and used to construct user precoders. The IRS phase-shifts are optimized based on the statistical channel knowledge to maximize the minimum average power gains of the composite communication channels subject to an average power threshold for the reflected sensing channel. The communication performance is evaluated by deriving the achievable user rates, while the sensing performance is studies by locating the target via the 2D MUltiple SIgnal Classification (MUSIC) algorithm. Our numerical results are used to study the trade-off between the communication and sensing performance metrics in IRS-aided massive MIMO systems with MRT-based linear precoders.

Cell-free (CF) integrated sensing and communication (ISAC) combines CF architecture with ISAC. CF employs distributed access points, eliminates cell boundaries, and enhances coverage, spectral efficiency, and reliability. ISAC unifies radar sensing and communication, enabling simultaneous data transmission and environmental sensing within shared spectral and hardware resources. CF-ISAC leverages these strengths to improve spectral and energy efficiency while enhancing sensing in wireless networks. As a promising candidate for next-generation wireless systems, CF-ISAC supports robust multi-user communication, distributed multi-static sensing, and seamless resource optimization. However, a comprehensive survey on CF-ISAC has been lacking. This paper fills that gap by first revisiting CF and ISAC principles, covering cooperative transmission, radar cross-section, target parameter estimation, ISAC integration levels, sensing metrics, and applications. It then explores CF-ISAC systems, emphasizing their unique features and the benefits of multi-static sensing. State-of-the-art developments are categorized into performance analysis, resource allocation, security, and user/target-centric designs, offering a thorough literature review and case studies. Finally, the paper identifies key challenges such as synchronization, multi-target detection, interference management, and fronthaul capacity and latency. Emerging trends, including next-generation antenna technologies, network-assisted systems, near-field CF-ISAC, integration with other technologies, and machine learning approaches, are highlighted to outline the future trajectory of CF-ISAC research.

The phase-shift control of intelligent reflective surface (IRS)-aided massive multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) systems requires pilot-intensive instantaneous estimation of cascaded channels. As a remedy, in this paper, statistical composite channel state information (CSI)-based techniques for SWIPT in IRS-aided massive MIMO are explored. Two phase-shift/power optimization strategies are proposed to guarantee system-wide user-fairness in terms of the average harvested energy and achievable rates, while keeping the pilot overhead and computational complexity significantly lower than the current state-of-the-art counterparts. By considering a hybrid time-switching/power-splitting protocol with a non-linear energy harvesting model, the average harvested energy and achievable rates are quantified. This analysis considers spatially correlated fading, imperfectly estimated composite channels, and optimization of IRS phase-shifts and transmit power control based on statistical composite CSI. The design insights and performance gains of the proposed techniques are presented through numerical results. Monte-Carlo simulations are used to validate our analysis.

Spatial non wide-sense stationarities cause partial visibility regions (VRs), and it is a unique propagation characteristic of emerging extra-large aperture arrays (ELAAs). Thus, classification of VRs is a necessity for accurate estimation of channels and efficient design of VR-aware precoders for ELAAs. In this paper, a deep learning framework is proposed to classify VRs in ELAAs. Our objective is to boost the accuracy of classifying VRs based on the uplink pilots received at the ELAAs. Consequently, we focus on guaranteeing user-fairness in the presence of wholly/partial VRs and improving the achievable rates by adopting VR-aware channel estimation and precoding. We propose a hybrid deep learning architecture comprising one dimensional convolutional neural networks and long-short term memory to classify VRs of each user at the ELAA. To achieve a higher accuracy, we generate a diverse dataset through Monte-Carlo simulations that captures numerous combinations of VRs at the ELAA. A transmit power allocation algorithm is also proposed to achieve a common downlink rate for all users irrespective of the different VRs, and its computational complexity is discussed. A set of numerical results is presented to evaluate the performance of our proposed framework. It is efficient and accurate in classifying VRs. Thus, it can be used to enhance the estimation accuracy of ELAA channels with VRs and thereby to design VR-aware precoders to boost spectral/energy efficiency of the next-generation wireless systems.

In downlink (DL) rate-splitting multiple access (RSMA), the users rely on successive interference cancellation (SIC) to remove contribution of the common signal prior to decoding their private messages. Since the users in time division duplexing based massive multiple-input multiple-output (MIMO) set-ups also rely on statistical channel state information (CSI) for signal decoding, perfect SIC may not be practically viable, specifically in the absence of DL pilots. Hence, this paper investigates the deleterious impact of imperfect SIC on the achievable rate for reconfigurable intelligent surface (RIS)-aided massive MIMO systems with RSMA. Our analysis quantifies the sum rate loss due to imperfect SIC in the presence of erroneously estimated cascaded channels, spatially correlated fading, and statistical CSI at the users. A transmit power control algorithm is also proposed to maximize the minimum achievable private rates, while guaranteeing that the minimum common rate at any user is no smaller than the optimized private rate. Our power allocation strategy ensures system-wide user fairness for the DL of RIS-aided massive MIMO RSMA that relies on statistical CSI.

The achievable rate performance of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided massive multiple-input multiple-output (MIMO) systems is investigated. Specifically, the achievable user rates are derived for three operating protocols of the STAR-RIS, namely the energy-splitting (ES), mode-switching (MS), and time-switching (TS) with both unicast and multicast transmissions. This analysis is useful in evaluating the system performance under imperfectly estimated channel state information (CSI), spatially correlated fading, pilot contamination, and statistical CSI based phase-shift optimization, transmit power control, and user signal decoding. For the high signal-to-noise ratio regime, the asymptotic achievable rates are also derived, and they serve as benchmarks or upper bounds for the rate performance comparisons for systems operating under the above transmission impediments. The composite uplink channels are estimated through linear minimum mean square error estimation techniques, and the phase-shift matrices at the STAR-RIS are optimized to maximize the effective average channel gains to minimize the channel estimation overhead. The base-station optimizes the transmit power based on the max-min criterion to attain a system-wide common user rate by negating the near-far effects of the downlink composite channels. Our numerical and simulation results validate our theoretical analysis and convergence of phase-shift and transmit power optimization algorithms. Our analytical and simulation results are useful in investigating the performance gains/comparisons among the ES, MS, and TS protocols for unicast and multicast transmissions to enable 360° smart coverage extensions with passive STAR-RIS aided massive MIMO.

The active pilot contamination attacks in intelligent reflecting surface (IRS) aided massive multiple-input multiple-output systems are investigated. By proposing a statistical channel state information based IRS phase-shift optimization technique, an achievable secrecy rate is derived in the presence of practical impediments, including erroneously estimated composite channels via linear minimum mean square error estimation criterion, residual interference due to active pilot contamination, artificial noise (AN) generation, and spatially correlated fading at the base-station antennas and IRS elements. A transmit power allocation technique is also proposed. Two active pilot attack detectors are designed based on the Neyman-Pearson and generalized likelihood ratio test criteria. The performance of these detectors is investigated by deriving the probability of detection, probability of false alarm, and receiver operating characteristics. Our secrecy rate analysis reveals that the rate leaked into the eavesdroppers by active pilot contamination attacks can be considerably high. The proposed power allocation algorithm jointly assigns transmit powers for the legitimate signals and AN sequences for maximizing the minimum secrecy rate of the weakest legitimate user to ensure user-fairness. The proposed detectors of active pilot attacks may be useful in designing remedial techniques to mitigate detrimental effects of active eavesdropping.

The achievable rates and computationally efficient statistical channel state information (CSI) based phase-shift and transmit power optimization techniques are investigated for multi-cell reconfigurable intelligent surface (RIS)-aided multi-user massive multiple-input multiple-output (MIMO). The uplink effective composite channels are estimated via linear minimum mean square error techniques. The channel covariance matrices are adopted to optimize the RIS phase-shifts to maximize the average sum power gains of the composite channels pertaining to all users, while minimizing the inter-cell interference. The proposed transmit power control algorithm maximizes the minimum user rate across all cells to achieve a common rate, while ensuring user-fairness by negating near-far effects. The performance of these techniques is evaluated by deriving the achievable user rates in closed-form by presenting two lemmas and two corollaries. These new results can be useful in accurate performance analysis of RIS-aided massive MIMO without invoking typical approximations based on the central limit theorem and moment matching with Gamma distribution. The achievable user rate analysis can also be used to evaluate the impact of spatially correlated fading, erroneously estimated CSI, intra-cell co-channel interference, pilot contamination, and statistical CSI-based user signal decoding. The pilot overhead and computational complexity of the proposed techniques are quantified. Thereby, we reveal that the proposed phase-shift optimization technique is both computationally efficient and scalable with large numbers of reflective elements and BS antennas. Our achievable rate analysis and convergence of the optimization algorithms are validated through Monte-Carlo simulations and numerical results.

We investigate the achievable rate of extra-large reconfigurable intelligent surface (XL RIS) aided downlink massive multiple-input multiple-output (MIMO) in the presence of wholly/partial visibility regions, spatial correlation, and imperfectly estimated channel state information (CSI). To reduce high pilot overhead associated with XL RIS-aided massive MIMO, a statistical CSI-based phase-shift optimization technique is adopted to maximize the minimum sum of eigenvalues of user covariance matrices. To ensure user-fairness in the presence of wholly/partial visibility regions, a transmit power allocation technique is designed based on a max-min optimization criterion. We present numerical/simulation results to validate our analysis/optimization solutions, to investigate the effects of wholly/partial visibility regions, and to reveal the performance gain of the XL RIS-aided massive MIMO systems.

We investigate statistical channel state information (CSI) based phase-shift and transmit power optimization techniques for the reconfigurable intelligent surface (RIS)-aided multi-user massive multiple-input multiple-output (MIMO) systems. Towards this end, the uplink composite channel at the massive MIMO base-station is estimated by using uplink pilots sent by the users via linear minimum mean square error estimation for an arbitrary phase-shift matrix at the RIS. Then, the RIS phase-shift matrix is iteratively optimized to maximize the sum of eigenvalues of the correlation matrix of the weakest user. Thereby, a maximal ratio transmission based precoder is designed by using the estimated composite channel together with the statistical CSI based optimal phase-shift matrix for the downlink payload transmission. Via the worst-case Gaussian technique, the downlink achievable user rates are derived in closed-form for correlated Rayleigh fading in the presence of imperfect CSI. A max-min based transmit power optimization algorithm is proposed to provide a common system-wide achievable user rate and thereby ensuring user-fairness while mitigating near-far effects. Monte-Carlo simulations are presented to validate our rate analysis, to exhibit the convergence of our proposed optimization algorithms, and to reveal system-design insights.

On the contrary to general consensus, we reveal that the best intelligent reflecting surface (IRS) selection outperforms the distributed IRSs in the presence of uniformly distributed phase-shift errors over [-π, π), which is the worst case for im-perfectly estimated channel phases. Nevertheless, the distributed IRS set-up regains its dominance when the channel phases are perfectly estimated and even for the case of discrete phase-shift adjustments with quantization errors. In this context, the outage performance of the best IRS selection is investigated and compared against the distributed IRS scheme with phase-shift errors. The best IRS selection criterion is designed to maximize the signal-to-noise ratio (SNR) by jointly optimizing the phase-shifts of passive reflecting elements at the best IRS. The end-to-end SNR for the Nakagami-m fading is statistically characterized by deriving a tight approximation to the cumulative distribution function in the presence of phase-shift errors at the IRSs. Our Monte-Carlo simulation results validate our analysis, and our numerical results compare the performance of the best IRS selection and distributed IRS set-ups.

A reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) non-orthogonal multiple-access (NOMA) system is investigated. A statistical channel state information (CSI) based RIS phase-shift optimization technique is adopted by considering the effective correlation matrices of the NOMA clusters pertaining to the composite channels. A linear minimum mean square error (LMMSE) estimation technique is used to estimate the uplink composite channel at the massive MIMO base-station via the user pilots for a fixed RIS phase-shift matrix. Thereby, for the downlink transmission, a maximum ratio transmission precoder is designed based on the LMMSE estimates of the uplink composite channels by virtue of channel reciprocity of time-division duplexing mode. The achievable sum rate is derived in closed-form for the spatially correlated Rayleigh fading channels in the presence of erroneously estimated CSI, intra-cluster pilot contamination, and imperfect successive interference cancellation by exploiting the statistical CSI-based optimal RIS phase-shift matrix, while adhering to the worst-case Gaussian technique. Monte-Carlo simulations are used to validate our achievable sum rate analysis and to depict the performance gains/degradations of the proposed RIS-aided massive MIMO NOMA system.

A performance analysis of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR- RIS) aided wireless communication system is presented. To this end, we present tight bounds/approximations for the outage probability, average achievable rate, and average symbol error rate (SER) in closed-form for the energy-splitting (ES) and mode-switching (MS) protocols. A high signal-to-noise ratio (SNR) analysis is also presented to obtain useful design insights. Thereby, we show that for a particular user, the asymptotic performance metrics depend on the transmit power allocation coefficients for the reflecting and transmitting users for a STAR- RIS aided communication setup. Our Monte-Carlo simulations validate our closed-form analysis, and our numerical results are used to obtain useful insights for STAR-RIS aided wireless communications.

We propose a graph-theoretic analytical framework to solve the sum rate maximization problem of a non-orthogonal-multiple-access (NOMA)-aided distributed millimeter wave massive multiple-input multiple-output (MIMO) system. The optimal solution for this system-wide sum rate maximization problem is neither mathematically tractable nor computationally-efficient when a traditional communication-theoretic analytical approach is solely invoked. Thus, the original problem is decoupled into two sub-problems, namely, a user access point (AP) association/clustering and a pilot resource allocation. In the first subproblem, APs optimally select a set of users having the highest average channel power gains, while the second sub-problem optimally assigns a set of limited orthogonal pilots among concurrently served users such that the pilot contamination is minimized. We propose a graph-theoretic analytical framework to find practically-viable and computationally-efficient solutions to both these sub-problems by virtue of modeling them via bipartite graph matching and vertex coloring problems. Thereby, we propose an algorithm to compute the minimum number of orthogonal pilots required for a given user-AP association/clustering. By exploiting the minimum pilot length and leveraging the benefits of our graph-theoretic approach, we propose a pragmatic solution of the coexistence of NOMA and orthogonal multiple-access schemes to further boost the achievable rate performance of our proposed system set-up.

This paper investigates the performance of intelligence reflective surface (IRS)-assisted relay systems. To this end, we quantify the optimal signal-to-noise ratio (SNR) attained by smartly controlling the phase-shifts of impinging electromagnetic waves upon an IRS. Thereby, a tightly approximated cumulative distribution function is derived to probabilistically characterize this optimal SNR. Then, we derive tight approximations/bounds for the achievable rate, outage probability, and average symbol error rate. Monte-Carlo simulations are used to validate our performance analysis. We present numerical results to reveal that the IRS-assisted relay system can boost the performance of end-to-end wireless transmissions.

In this paper, the feasibility of adopting an intelligent reflective surface (IRS) in a cell-free wireless communication system is studied. The received signal-to-noise ratio (SNR) for this IRS-enabled cell-free set-up is optimized by adjusting phase-shifts of the passive reflective elements. Then, tight approximations for the probability density function and the cumulative distribution function for this optimal SNR are derived for Rayleigh fading. To investigate the performance of this system model, tight bounds/approximations for the achievable rate and outage probability are derived in closed form. The impact of discrete phase-shifts is modeled, and the corresponding detrimental effects are investigated by deriving an upper bound for the achievable rate in the presence of phase-shift quantization errors. Monte-Carlo simulations are used to validate our statistical characterization of the optimal SNR, and the corresponding analysis is used to investigate the performance gains of the proposed system model. We reveal that IRS-assisted communications can boost the performance of cell-free wireless architectures.

We investigate the coexistence of underlay spectrum sharing in cell-free massive multiple-input multiple-output (MIMO) systems. A primary system with geographically distributed primary access points (P-APs) serves a multitude of primary users (PUs), while a secondary system serves a large number of secondary users (SUs) in the same primary/licensed spectrum by exploiting the underlay spectrum sharing. To mitigate the secondary co-channel interference inflected at PUs, stringent secondary transmit power constraints are defined for the secondary access points (S-APs). A generalized pilots sharing scheme is used to locally estimate the uplink channels at P-APs/S-APs, and thereby, conjugate precoders are adopted to serve PUs/SUs in the same time-frequency resource element. Moreover, the effect of a user-centric AP clustering scheme is investigated by assigning a suitable set of APs to a particular user. The impact of estimated downlink (DL) channels at PUs/SUs via DL pilots beamformed by P-APs/S-APs is investigated. The achievable primary/secondary rates at PUs/SUs are derived for the statistical DL and estimated DL CSI cases. User-fairness for PUs/SUs is achieved by designing efficient transmit power control policies based on a multi-objective optimization problem formulation of joint underlay spectrum sharing and max-min criteria. The proposed orthogonal multiple-access based analytical framework is also extended to facilitate non-orthogonal multiple-access. Our analysis and numerical results manifest that the primary/secondary performance of underlay spectrum sharing can be boosted by virtue of the average reduction of transmit powers/path-losses, uniform coverage/service, and macro-diversity gains, which are inherent to distributed transmissions/receptions of cell-free massive MIMO.

This paper investigates the throughput improvement of cell-free massive multiple-input multiple-output (MIMO) systems by non-orthogonal multiple access (NOMA) for future cellular networks under stochastic access point and user locations. In this context, the node locations are modeled with Poisson point processes. The time division duplexing mode is employed, and uplink channels are estimated locally using uplink pilots. Furthermore, unique pilot sequences are used between NOMA clusters, while pilot reuse occurs within each cluster to strike a balance between the training overhead and the number of clusters. Matched-filter-based precoding is utilized for downlink transmission. The aggregate received signal is analytically characterized by deriving the moment generating function and approximations via moment matching. Then, the asymptotic achievable rates of the NOMA users are derived, thereby quantifying the adverse impact of error propagation owing to imperfect successive interference cancellation. Special scenarios with prior downlink channel state information and log-distance power control are also considered. We show that NOMA greatly increases the achievable average rate, especially under low path loss exponents and dense networks, while user fairness may be boosted by the adoption of a log-distance transmit power control scheme with proper parameter selection (i.e. lower values for the power control parameter).

Simultaneous wireless information and power transfer (SWIPT) is increasingly seen as a viable technique to power energy constrained user devices while transmitting data. SWIPT can be readily implemented within the recently proposed cell-free massive MIMO networks, where a large number of interconnected access points (APs) simultaneously serve users. This paper characterizes the coexistence and interplay between these two technologies by using tools from stochastic geometry. To this end, we consider a spatially random network, where the APs are modeled stochastically using a Poisson point process, and a time-switching protocol is used for the SWIPT operation at the users. A time-division-duplexing protocol is considered in which uplink pilots are used to obtain channel state information at the APs, while conjugate beamforming is performed in the downlink. Moreover, we consider blockages due to obstacles in the channel and the resulting line-of-sight and non-line-of-sight conditions affecting the fading and path loss. We derive the mean and variance of the harvested energy along with the average achievable rate in the downlink for an energy user. The tradeoff between the downlink data throughput and harvested energy is quantified, and thereby, we show that spatially-distributed APs in a cell-free arrangement can boost the energy-rate trade-off of SWIPT.

In this paper, the performance of a distributed intelligent reflective surface (IRS)-aided communication system is investigated. To this end, the optimal signal-to-noise ratio (SNR) achievable through the direct and reflected channels is quantified by controlling the phase-shifts of the distributed IRS. This optimal SNR is statistically characterized by deriving tight approximations to the exact probability density function and cumulative distribution function for Nakagami- m fading. Thereby, the outage probability and achievable rate bounds are derived in closed-form, and they are validated via Monte-Carlo simulations. Our numerical results reveal that the distributed IRS-aided communication set-ups can boost the outage and rate performance of wireless systems.

The performance of an intelligent reflecting surface (IRS)-assisted time-switching simultaneous wireless information and power transfer (SWIPT) system is investigated from a maxmin user-fairness perspective. A series of optimization problems is formulated to maximize the minimum harvested energy and the achievable user rates via jointly optimizing the transmit powers at the base-station (BS) and phase-shifts at the IRS. The underlying optimization problems are non-convex, and thus, the efficient alternating optimization algorithms are developed to obtain sub-optimal solutions. A combination of geometric programming and convex optimization techniques has been employed in an iterative manner to solve the transmit power allocation and IRS phase-shift optimization problems, respectively. Max-min based common/system-wide harvested energy and achievable user rate are characterized when the BS adopts linear/conjugate precoding. Thereby, a max-min fairness-based energy-rate trade-off is quantified. Our numerical results validate the proposed optimization solutions and reveal the underlying performance gains of the optimized system.

In this paper, an intelligent reflective surface (IRS)-aided multi-way communication system is investigated. The full-duplex reflective properties of the IRS are exploited to enable full-mutual data exchange among multiple users within a single channel-use. A max-min fairness-based achievable rate optimization problem is formulated to control the phase-shift matrix at the IRS. To this end, a minorization-maximization based iterative IRS phase-shift optimization algorithm is used to maximize the minimum achievable system-wide user rate. The simulation/numerical results are presented to validate the convergence of the proposed IRS phase-shift optimization algorithm and to investigate the system performance. Thereby, it is revealed that the proposed system mitigates the adverse near-far effects by ensuring a common system-wide achievable user rate while accomplishing full-mutual data exchange via intelligently controlling the phase-shifts at the IRS. Our numerical results reveal that the proposed system outperforms the current state-of-the-art multi-way communication system based on multiple-input multiple-output (MIMO) relays in terms of the achievable sum rate in the moderate-to-large IRS element regime.

We investigate the feasibility of employing non-orthogonal multiple-access (NOMA) in cell-free massive multiple-input multiple-output (MIMO) operating with underlay spectrum-sharing. In our proposed system model, multiple clusters of NOMA-enabled secondary users (SUs) are concurrently served by geographically distributed secondary access-points (S-APs) via conjugate beamforming. The uplink channels are estimated locally at each S-AP via pilots sent by SUs. A set of orthogonal pilots is shared among the secondary and primary clusters to strike a balance between the throughput and training overhead, while enabling massive connectivity in primary and secondary systems. We derive the achievable rates of the secondary system by capturing the adverse effects of inter/intra-cluster interference, primary/secondary pilot contamination, imperfect successive interference cancellation (SIC) and partial channel state information (CSI). We propose a transmit power allocation policy for the secondary system to mitigate the detrimental impact of near-far effects by virtue of max-min fairness criterion. Through an achievable rate analysis, we reveal that although the number of concurrently served users can be substantially boosted by employing the proposed system model, the achievable rates are adversely affected due to detection uncertainties with imperfect SIC and statistical CSI at NOMA-enabled SUs.

A statistical characterization of the fundamental performance bounds of an intelligent reflective surface (IRS) intended for aiding wireless communications is presented. To this end, the outage probability, average symbol error probability and achievable rate bounds are derived in closed-form. By virtue of an asymptotic analysis in high signal-to-noise ratio (SNR) regime, the achievable diversity order is derived. Thereby, we show that a diversity gain in the order of the number of passive reflective elements embedded within the IRS can be achieved with only controllable phase adjustments. Thus, IRS has a great potential of boosting the wireless performance by intelligently controlling the propagation channels without employing additional active radio frequency chains.

The benefits of facilitating downlink (DL) channel estimation at users are investigated for multi-cell massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) systems. By leveraging channel reciprocity of time division duplexing mode and uplink channel estimates, the DL pilots are beamformed towards the clusters of NOMA users such that the DL pilot sequence length does not scale with the number of antennas at the base-station. This enables users to estimate their effective DL channels and adopt those to facilitate successive interference cancellation. Aiming at establishing the performance bounds, the achievable DL rates are derived based on the estimated DL channels, and thereby, the adverse joint impact of beamforming uncertainty, imperfect SIC, and residual intra/inter-cluster/cell interference is quantified. The residual inter-cell interference is mitigated by using pilot contamination precoding and the underlying asymptotically achievable user rates are derived. Based on our analytical results, we conclude that DL channel estimates at user nodes are essential in successfully reaping benefits of integrating NOMA with massive MIMO.

For a multi-way relay network (MWRN) with K users, K time slots are needed for full data exchange. Thus, the overall spectral efficiency, due to the 1/K pre-log factor, declines as number of users grows. It has recently been improved to roughly K/2 time slots, but even this improvement does not arrest the decline. Herein, we reduce this task to just two time slots regardless of K. To do this, we exploit the performance gains of non-orthogonal multiple-access (NOMA) and a massive multiple-input multiple-output (MIMO) relay. First, the users transmit their signals to the relay, which uses maximal ratio combining reception. Next, the relay transmits a superposition-coded signal for all users by using maximal ratio transmission. Each user then performs successive interference cancellation (SIC) decoding of data symbols of the other K - 1 user nodes. We use the so-called worst-case Gaussian approximation to derive the overall sum rate and demonstrate significant spectral-efficiency gains and energy-efficiency gains over the existing MWRN counterparts. We also design the relay power allocation matrix to maximize the minimum among the user rates, thus maximizing the user fairness. Furthermore, the effects of imperfect SIC and imperfect channel state information (CSI) on the sum rate are analyzed.

Active pilot attack detection in time division duplexing based sub-6GHz massive multiple-input multiple-output (MIMO) non-orthogonal multiple-access (NOMA) systems is investigated. A practically realizable generalized likelihood ratio test (GLRT) is formulated when the eavesdropper's signal parameters are unknown to the massive MIMO base-station. The performance of this detector is analyzed by deriving the probability of false alarm, probability of detection and receiver operating characteristics. The underlying performance is compared with respect to an optimal Neyman-Pearson (NP) based Clairvoyant detector, which is designed by assuming the perfect knowledge of eavesdropper's signal parameters. Thereby, we conclude that the limited knowledge of the eavesdropper's signal parameters must be taken into account in designing practically viable active pilot detectors because the Clairvoyant detector overestimates the detection performance. Nevertheless, we show that the proposed GLRT based detector asymptotically becomes optimal in NP sense when the number of antennas at the base-station grows without bound. Moreover, we reveal that there is a fundamental trade-off between the number of NOMA users that can be served simultaneously in the same time-frequency resource element and the detection performance of active pilot attacks.

The feasibility of enabling massive wireless connectivity to cell-edge users is investigated by means of multiple relay-aided massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA). The key challenge of channel state information (CSI) acquisition is overcome by estimating the cascaded relay channel at the base-station via pilots sent by users. The achievable rates are derived by assuming that the users rely on statistical channel knowledge for signal decoding. Our analysis is useful to quantify the joint adverse effects of intra-cluster pilot contamination, imperfect CSI, precoding uncertainty, and imperfect successive interference cancellation. The achievable rates of the proposed relay-aided massive MIMO NOMA are compared against the orthogonal multiple access (OMA) counterpart. We reveal that although multiple relayaided massive MIMO NOMA is able to support overloaded case, massive MIMO OMA outperforms NOMA counterpart in terms of the achievable sum rate in the underloaded cases.

The performance of non-orthogonal multiple-access (NOMA)-aided massive multiple-input multiple-output (MIMO) uplink is investigated. Spatially-distributed user nodes are grouped into multiple clusters based on spatial-directional information, and a set of orthogonal pilots are assigned to these clusters. To strike a balance between the pilot training overhead and the number of users that can be served simultaneously in the same time-frequency resource block, the NOMA-enabled users within a given cluster share the same pilot sequence. The uplink channels are estimated at the massive MIMO base-station (BS) by using the pilots transmitted by the user nodes in all clusters. A computationally-efficient maximal ratio combiner is constructed at the BS via the estimated uplink channels. The achievable rates of this system set-up are derived for both finite and infinite BS antenna regimes. Thereby, the effects of imperfectly estimated channel state information, intra-cluster pilot contamination, and imperfect successive interference cancellation are analytically quantified. In order to guarantee user-fairness and thereby to mitigate near-far effects in uplink NOMA transmissions, a max-min transmit power control is invoked. Thereby, max-min fairness optimal transmit power control coefficients are derived. These power control coefficients depends only on statistical knowledge of downlink channels. Thus, the proposed transmit power control can readily be implemented at NOMA user nodes, which primarily rely on channel hardening with no downlink pilots are being transmitted by the BS in an attempt to minimize the training overhead. Our analysis and numerical results reveal that the proposed system can be exploited to enable massive access by optimizing the fundamental tradeoff among the number of simultaneously served NOMA users, uplink achievable rates and implementation complexity.

The impact of low-dimensional digital precoding on the achievable sum rate of a training-based massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) system with a limited number of radio-frequency (RF) chains is investigated. A low-dimensional digital precoder is cascaded with a high-dimensional analog precoder and thus reducing the number of RF chains required at the NOMA-enabled massive MIMO base-station. Uplink channel cascaded with the analog precoder is estimated at the BS via pilots sent by the clustered users. Each cluster is allocated with an orthogonal pilot sequence, and it is shared among users within a cluster. The achievable downlink sum rate is derived by capturing the effects of practical impediment, including channel estimation errors, intra-cluster pilot contamination, imperfect successive interference cancellation, and statistical/partial channel knowledge at the users for signal decoding. Thereby, the sum rate degradation caused by these transmission impairments and the impact of reduced number of RF chains at the BS are quantified. Moreover, the achievable sum rate and the number of users that can be served simultaneously in the same time-frequency resource block by massive MIMO NOMA are compared with those of massive MIMO orthogonal multiple access (OMA). Our results are used to draw system-design insights on fundamental trade-offs between the number of simultaneously served users, achievable sum rates and computational complexity. We conclude that massive MIMO NOMA is practically-viable for supporting massive access with low rates requirements, whereas massive MIMO OMA is more desirable when the high rate requirement is more prevalence than the demand for massive access.

In this paper, the coexistence of cell-free massive multiple-input multiple-output (MIMO) and underlay spectrum-sharing is investigated. Thereby, the fundamental performance limits are established to characterize the feasibility of this coexistence. A set of spatially-distributed secondary access points (S-APs), which are underlaid in a primary cell-free massive MIMO system, serves many secondary users (SUs) in the same licensed spectrum of the primary access points (P-APs). Stringent secondary transmit power constraints are defined for the S-APs to mitigate undesired secondary cochannel interference (CCI) at the primary users (PUs). The uplink channels are estimated locally at the P-APs and S-APs via a generalized pilot sharing scheme, and thereby, conjugate precoders are used to serve PUs/SUs simultaneously. The achievable rates for both primary and secondary systems are derived for imperfectly estimated channels at the P-APs/S-APs, and the impact of intra-system pilot contamination is investigated. User-fairness for SUs is guaranteed by designing an efficient transmit power control policy based on the max-min criterion and secondary transmit power constraints. Through a rigorous analysis, we reveal that massive distributed primary/secondary transmissions can be exploited to mitigate detrimental impact of secondary CCI on PUs, and thereby, the achievable rates of primary/secondary systems can be boosted.

The coherence residual interference caused by intra-cell pilot contamination has been shown to be the most detrimental impediment to the underlay spectrum-sharing in massive multiple-input multiple-output (MIMO) systems. As a remedy, a reverse time-division-duplexing (R-TDD) transmission strategy is proposed for mitigating intra-cell pilot contamination. To this end, the performance of multi-cell multi-user underlay spectrum-sharing MIMO with R-TDD is investigated. The secondary transmit power constraints and achievable uplin/downlink sum rates are derived for both finite and infinite base-station (BS) antenna regimes. Thereby, the joint detrimental effects of spatial correlation, beamforming uncertainty caused by imperfectly estimated channels, inter-cell co-channel interference (CCI) and residual interference incurred by inter-cell pilot contamination are analytically quantified and compared against the conventional TDD (C-TDD) counterpart. Our analysis reveals that the secondary performance metrics with imperfectly estimated channels become independent of primary interference threshold when the number of BS antennas grows without bound. Thus, the secondary system can be operated in its maximum average transmit power independent of the primary system without hindering its asymptotic achievable rates. This is because the intra-cell coherence CCI of two systems can be asymptotically mitigated by exploiting R-TDD and asymptotic channel orthogonality in massive MIMO systems.

The feasibility of adopting distributed massive multiple-input multiple-output (D-MMIMO) for mitigating the achievable rate loss incurred by spatially-correlated fading at space-constrained user antenna arrays when served by co-located massive MIMO (C-MMIMO) counterpart is investigated. In order to explore a practically-viable design, the cumulative effects of spatial correlation at both multi-antenna access points (APs) and multi-antenna users, beamforming uncertainty caused by imperfectly estimated channel state information (CSI), and adverse effects of pilot contamination have been taken into account. The achievable user rates of the proposed D-MMIMO downlink operating in a multi-cell set-up are derived for finite/infinite antenna array regimes at the distributed APs. Thereby, the achievable user rates for C-MMIMO counterpart are deduced and compared with those of the proposed D-MMIMO downlink. Through a rigorous analysis and simulation results, we show that the distributed transmissions rendered by D-MMIMO can provide significant performance gains compared to the C-MMIMO counterpart (i) by minimizing adverse effects of spatial correlation via distinct spatial-directions/signatures rendered by distributed transmissions, (ii) by mitigating shadow fading via leveraging macro-diversity gains, and (iii) by reducing the average path-losses through effectively shortening transmission distances. Moreover, we reveal that the proposed D-MMIMO can be exploited to recover a significant portion of rate loss incurred by the lost of asymptotic channel orthogonality due to doubly-correlated channels when both APs and user nodes are equipped with space-constrained multiple-antenna arrays.

The feasibility of implementing non-orthogonal multiple access (NOMA) in massive multiple-input multiple-output (MIMO) downlink with distributed antenna arrays is investigated. The achievable downlink rates are derived for two channel state information (CSI) cases, namely (i) estimated uplink CSI at the access points (APs) via user uplink pilots and statistical CSI at the users, and (ii) estimated uplink CSI at the APs via uplink user pilots and estimated downlink CSI at the users via downlink pilots beamformed by the APs. The trade-off between the number of served user nodes and their achievable rates is investigated. The adverse effects of imperfect successive interference cancellation (SIC) and detection uncertainty on the achievable downlink rates are quantified. We show that the achievable downlink rate of NOMA can be inferior to that of the orthogonal multiple-access (OMA) counterpart in the low-user regime. This is a direct consequence of residual interference caused by intra-cluster pilot contamination and error propagation from imperfect SIC. However, the proposed massive MIMO NOMA downlink outperforms the OMA counterpart in the high-user regime in terms of the achievable downlink rate. Moreover, the impact of downlink pilots on the sum rate is also investigated.

The feasibility of a hybrid relay-assisted massive multiple-input multiple-output (MIMO) downlink for simultaneous wireless information and power transfer (SWIPT) is investigated. The system performance is investigated for a generalized wireless energy harvesting protocol, which facilitates performance analysis for both time-switching (TS) and power-splitting (PS) protocols in the presence of imperfect channel state information (CSI). The harvested energy and the achievable sum rate are derived, and thereby, the joint/individual effects of TS/PS ratios and pilot contamination are quantified. Our analysis reveals that the pilot contamination can be beneficial for energy harvesting, although it is detrimental for the achievable rates. This energy-rate trade-off is quantified in closed-form, and thereby, valuable system-design insights are obtained.

We propose a novel transmission protocol for multiway relay networks (MWRNs) in which the number of timeslots required for full mutual multi-way data exchange among K user nodes can be reduced to just two from Γ(K - 1)/21 + 1 in the current state-of-the-art. The proposed MWRN adopts superposition-coded transmission, successive interference cancellation (SIC) reception, power-domain non-orthogonal multipleaccess (NOMA) and linear detection/precoding facilitated by massive multiple-input multiple-output (MIMO). First, the user nodes transmit their signals to a massive MIMO-enabled relay, where a linear detector based on maximal ratio combining criterion is used for signal reception. Next, the relay composes a superposition-coded signal for each user node and transmits towards the user nodes by using a linear precoder based on maximal ratio transmission criterion. User nodes perform SICbased decoding for retrieving symbols sent by the remaining K user nodes. Thus, our proposed MWRN protocol completes the full mutual multi-way data exchange among all users within two time-slots. We derive the achievable sum rate of it via the so-called worst-case Gaussian approximation and show that a significant spectral efficiency gain can be achieved over the existing MWRN counterparts.

Cell-free massive multiple-input multiple-output (MIMO) is a form of distributed massive MIMO aiming to provide massive access and improve spectral efficiency by inheriting favorable properties of traditional massive MIMO, while mitigating detrimental effects such as shadowing and spatially correlated fading. This paper investigates how the throughput of cell-free massive MIMO is affected by non-orthogonal multiple access (NOMA) for the next-generation cellular networks under stochastic access point (AP) and user locations. Thus, we consider homogeneous Poisson point processes (PPPs) to model node locations, while considering a Rayleigh channel with log-distance path loss. The time division duplexing (TDD) mode is employed and uplink channels are estimated autonomously/locally at each AP via uplink pilots sent by users. Moreover, while unique pilots are used between NOMA clusters, pilots are reused within each cluster in order to strike a balance between the training overhead and number of clusters. Matched filter based precoding is performed within the downlink based on the estimated channels. The aggregate signal received from all access points is characterized based on the moment generating function and approximated via moment matching. Thereby, the achievable rates for the users are derived, under the consideration of error propagation due to imperfect successive interference cancellation (SIC). It is shown that NOMA increases the overall rate under environments with low path loss exponents and networks with high access point densities, while careful power allocation can significantly improve user fairness.

The detrimental effects of pilot contamination attacks by active eavesdroppers are investigated for multi-cell multi-user massive multiple-input multiple-output (MIMO) relay networks. To this end, secure transmission strategies are designed for both users-to-relay and relay-to-destination channels in the presence of active pilot attacks with imperfect legitimate user channel state information (CSI) and with no eavesdropper CSI knowledge at the relay. The excess degrees-of-freedom offered by the massive MIMO relay are exploited to mitigate detrimental effects of cooperative jamming (CJ) signals and to generate artificial noise (AN) during the first and second time-slots, respectively. Thereby, the achievable secrecy rate lower bounds for active attacks are derived in the finite/infinite relay antenna regimes. The secrecy rates for passive eavesdropping are deduced and compared to that of active attacks. A joint optimal power allocation scheme for the pilot, payload data, and AN and CJ signals is formulated and solved by using geometric programming techniques. Rigorous numerical and simulation results are provided to obtain valuable insights, which are useful in designing secure physical layer transmission strategies for multi-cell multi-user massive MIMO relay networks.

In this paper, the achievable secrecy rate of a relay-assisted massive multiple-input multiple-output (MIMO) downlink is investigated in the presence of a multi-antenna active/passive eavesdropper. The excess degrees-of-freedom offered by a massive MIMO base-station (BS) are exploited for sending artificial noise (AN) via random and null-space precoders. An active eavesdropper contaminates the uplink channel estimates by sending pilot sequences identical to those of the legitimate users/relay. This active pilot contamination makes the massive MIMO BS implicitly beamform the confidential signals toward the active eavesdropper during two-hop downlink transmissions. The achievable secrecy rates are derived by taking the detrimental effects of actively contaminated channel state information with estimation errors and spatially correlated fading at the multiple-antenna terminals into account. The secrecy rate loss incurred by active pilot attacks over passive eavesdropping is investigated, and the secrecy rate gap between random and null-space-based AN is compared. A novel transmit power control policy is designed to efficiently allocate transmit power at the BS/relay for payload data and AN sequences for maximizing the achievable secrecy rate. Our results reveal that active pilot contamination attacks significantly degrade the achievable secrecy rate in dual-hop transmissions, and the corresponding detrimental effects cannot be asymptotically mitigated in the infinite BS antenna regime.

Multi-cell multi-user underlay spectrum-sharing massive multiple-input multiple-output systems operating with reverse time division duplexing (R-TDD) are investigated. By primarily aiming at fully mitigating intra-cell pilot contamination and coherent interference, in the proposed R-TDD scheme, the primary/secondary systems are allowed to operate only in the opposite transmission directions. In order to establish fundamental performance limits, the secondary transmit power constraints and achievable rates are derived in the presence of training-based channel estimation. Thereby, the joint detrimental effects of spatial correlation, beamforming uncertainty, and inter-/intra-cell coherence interference due to pilot contamination are quantified and compared against the conventional TDD (C-TDD) counterpart. A max-min optimal power control policy is designed, and thereby, the common achievable rates and power control coefficients are derived. It is shown that by invoking R-TDD, the secondary power constraints and sum rates can be made to become asymptotically independent of primary interference threshold. Thus, the secondary system can be operated with its maximum average transmit power, independent of the primary system without hindering its asymptotically achievable rates by the virtue of the inherent intra-cell coherent interference mitigation benefit of the R-TDD. By exploiting the pilot decontamination feature of R-TDD, the achievable rates of primary/secondary systems can be significantly boosted, compared to the underlay spectrum sharing with C-TDD.

The performance of multi-cell massive multiple-input multiple-output (MIMO) downlink (DL) with nonorthogonal multiple access (NOMA) is investigated. A novel pilot assignment for NOMA users is proposed to mitigate intra-cluster pilot contamination and to alleviate the detrimental impact of inter-cluster in the useful operating regime. The user nodes grouped into the same cluster based on the spatial-direction information are assigned orthogonal pilots to mitigate intracluster pilot contamination. These pilots are shared among the clusters to reduce the training overhead. However, the intercluster pilot contamination is mitigated by exploiting the distinct spatial directions of clusters. This pilot assignment ensures that the number of NOMA users that can be served simultaneously in the same time-frequency-spatial resource block is not limited by the length of coherence interval. A max-min fairness optimal transmit power allocation algorithm is proposed to guarantee user-fairness. The achievable DL sum rates are derived, and thereby, the cumulative impact of channel estimation errors, imperfect successive interference cancellation, and statistical channel knowledge at users is quantified. Our analysis reveals that the proposed massive MIMO NOMA can support massive access without compromising the spectral efficiency gains.

Massive multiple-input multiple-output (MIMO) enabled base stations employing non-orthogonal multiple access (NOMA) hold immense potential in increasing the spectral efficiency of future cellular networks. In this paper, we evaluate the achievable rate of N-user NOMA under a Poisson process of massive MIMO enabled base stations. We adopt a timedivision duplexing (TDD) mode, where the uplink pilots are reused among the different base stations, and within each NOMA cluster of each base station, while matched-filter based precoding is employed in the downlink. The achievable rate by a typical NOMA user is characterized by taking into account imperfect successive interference cancellation (SIC) and error propagation. To this end, the moment generating function of the interference from other base stations due to pilot contamination is derived along with the signal detection probability. It is shown that NOMA can significantly improve the rate performance under most system parameters, and that the rate performance can be increased further through denser networks. Moreover, we show that the individual user rates and fairness amongst users within a NOMA cluster are significantly impacted by the specific power allocation algorithm.

A relay-aided multi-user massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) downlink transmission is proposed to support simultaneous massive access for cell-edge user nodes in the same time-frequency-spatial resource block. These spatially-distributed user nodes are grouped into clusters based on their spatial directional information and long-term fading statistics. Each cluster is allocated with an orthogonal pilot sequence, while the user nodes within a cluster share the same pilot. The achievable downlink rates of this relay-aided massive MIMO NOMA are derived, and thereby, the cumulative impact of channel estimation errors, imperfect successive interference cancellation and intra-cluster pilot contamination is investigated. The achievable sum rates and the number of simultaneously served users by the proposed massive MIMO NOMA relaying are compared with the orthogonal multiple access counterpart. Consequently, the trade-offs among the sum rate gains, number of users and implementation/computational complexity are discussed, and thereby, useful insights for practically-viable system-design are obtained.

The objective of this paper is to analytically quantify the performance gap between the hybrid processing and full-dimensional (FD) digital processing for simultaneous wireless information and power transfer (SWIPT) in massive multiple-input multiple-output (MIMO) systems. To this end, a hybrid precoder/combiner structure, which consists of a low-dimensional digital precoder/decoder cascaded with an analog beamformer/combiner, is employed at the base-station (BS) for SWIPT. For two hybrid processing designs, the harvested energy, achievable rates and fundamental energy-rate trade-off are derived when the number of BS antennas grows without bound with respective to the number of user nodes. Thereby, the percentage losses of the achievable rate and the harvested energy of the proposed hybrid precoding/combining over the FD digital precoding/combining are quantified. Our analysis and numerical results reveal that the proposed hybrid processing technique for SWIPT significantly reduces the number of radio frequency chains at the massive MIMO BS, while yielding only marginal energy-rate trade-off degradation over the FD digital counterpart.

In this paper, the performance of simultaneous wireless information and power transfer (SWIPT) for training-based cell-free massive multiple-input multiple-output (MIMO) is investigated. The key idea is to simultaneously transmit information and power via a larger number of spatially-distributed single antenna access points (APs) towards geographically-distributed single-antenna information/energy users. The APs are connected to a central processing unit via a backhaul network and perform conjugate beamforming precoding in downlink (DL) and matched filtering decoding in uplink (UL). The achievable harvested energy and the achievable DL/UL rates are derived in closed-form. Thereby, the DL/UL energy-rate trade-offs are quantified. Our analysis reveals that cell-free massive MIMO can boost the performance of SWIPT by leveraging the benefits of distributed transmission/reception with large number of APs.

The achievable secrecy rates for a cell-free massive multiple-input multiple-output (MIMO) in the presence of a single-antenna active eavesdropper are derived and compared with that of co-located massive MIMO. The active eavesdropper contaminates the uplink channel estimates at the access points (APs), and the downlink precoders at the APs are constructed based on this contaminated channel estimates. Hence, the APs inadvertently beamform confidential information towards the active eavesdropper during the downlink transmission. The achievable rates at the legitimate user nodes and the rates leaked into the active eavesdropper are derived for estimated/imperfect channel state information in the finite and infinite regimes of the number of APs. A transmit power allocation algorithm for maximizing the achievable secrecy rate is developed. Our analysis and numerical results reveal that the rate leaked into the eavesdropper can be of significance in the presence of active pilot attacks in cell-free massive MIMO.

The asymptotic performance of multi-user multi-hop massive multiple-input multiple-output (MIMO) relay networks, in which multiple spatially distributed user nodes communicate with a multiple-antenna destination via multi-antenna amplify-and-forward relays, is investigated. To this end, the signal-to-interference-plus-noise ratio and achievable sum rate expressions are derived for three specific antenna configurations at the relay and destination nodes, namely (i) infinitely many relay and destination antennas, (ii) finitely many relay antennas and infinitely many destination antennas, and (iii) finitely many relay and destination antennas. The asymptotic achievable sum rates are derived when the numbers of antennas at the relays and destination grow unbounded while keeping fixed ratios among them. The upper and lower bounds of the average sum rates are derived for the finite antenna regime by using bounds for harmonic mean and Jensen's inequality. The detrimental effects of channel estimation errors are investigated by deriving the achievable sum rate expressions. Our sum rate analysis reveals that the massive MIMO technology can be exploited to achieve significant spectral efficiency gains for multi-hop relay networks.

In this paper, the achievable secrecy rates are derived for the relay-assisted massive multiple-input multiple-output (MIMO) downlink with limited number of radio frequency (RF) chains at the base-station (BS). Two hybrid precoder designs are investigated for the dual-hop transmission of information and artificial noise. Two channel estimation techniques are proposed. Thereby, the achievable secrecy rate gap between the hybrid precoding and full-dimensional digital precoding is quantified for imperfect channel state information. Our analysis reveals that the proposed hybrid precoders can significantly reduce the number of RF chains at the BS, while yielding only a marginal percentage loss of the achievable secrecy rate compared to the full-dimensional digital precoders. Hence, the proposed hybrid precoding can be used for provisioning physical layer security in relay-aided massive MIMO downlink with a lower computational/implementation complexity.

The performance of massive multiple-input multiple-output (MIMO) configurations for multi-cell multi-user amplify-and-forward relay networks is investigated. Two massive MIMO signal processing techniques (SPT-1 and SPT-2) are proposed, and their computational complexity and performance gains are compared with multi-pair massive MIMO relaying (SPT-3) by deriving the partial and full achievable asymptotic sum rates for perfect and imperfect channel state information. Thereby, the cumulative effects of channel estimation errors, co-channel interference (CCI), and pilot contamination are investigated. The best relay selection for the multi-branch relaying is investigated. An optimal user power control algorithm based on max-min fairness is formulated, and thereby, the power allocation co-efficients and optimal common achievable user rate are derived in closed-form. Our analysis reveals that the effects of pilot contamination for the multi-cell massive MIMO relaying become more severe than that for the single-hop counterpart due to the multiple sources of CCI and propagation of residual interference in dual-hop transmissions.

In this paper, the detrimental effects of intra-cell pilot contamination for physical layer secure communication in cognitive multi-user massive multiple-input multiple-output (MIMO) systems with underlay spectrum sharing are investigated. The channel estimates at the primary base-station (PBS) and secondary base-station are obtained by using non-orthogonal pilot sequences transmitted by the primary user nodes and secondary user nodes, respectively. Hence, these channel estimates are affected by intra-cell pilot contamination. Furthermore, a passive multi-antenna eavesdropper is assumed to be eavesdropping upon either the primary or secondary confidential transmissions. In this context, a physical layer security strategy is provisioned for the primary and secondary transmissions via artificial noise generation at the PBS and zero-forcing precoders. For this system set-up, the average and asymptotic achievable secrecy rate expressions are derived in closed-form, and thereby, the secrecy rate degradation due to intra-cell pilot contamination is quantified. Our analysis reveals that a physical layer secure communication can be provisioned for both primary and secondary massive MIMO systems even with channel estimation errors and pilot contamination.

The achievable sum rate of multi-cell multi-user massive multiple-input multiple-output (MIMO) downlink is investigated. Hybrid beamformers, which are constructed by using estimated/imperfect channel state information, are employed at the base-station. Thus, the massive MIMO base-station in each of the L cells is enabled with a typical power-intensive digital precoder and a quantized analog beamformer. This setup can significantly reduce the number of radio frequency (RF) chains required for the digital precoder, and thereby, the power consumption in the digital signal processing and the complexity of circuitry at the massive MIMO base-station. The achievable asymptotic sum rate expressions are derived for linear digital precoders namely, (i) zero-forcing transmission and (ii) maximum ratio transmission cascaded with a phase-shifting analog beamformer. Thereby, the asymptotic sum rate degradation due to the hybrid beamforming is quantified and compared against the full-dimensional digital beamforming. This sum rate loss is a function of the number of phase quantization levels and cannot be canceled completely even in the asymptotic base-station antenna regime. Nevertheless, our analysis reveals that the detrimental effects of phase quantization and reduced number of RF chains of the hybrid beamforming can be mitigated in the limit of increasingly many base-station antennas when the receiver thermal noise power is negligibly smaller than the residual interference due to pilot contamination.

In this paper, secure transmission strategies for the relay-assisted massive multiple-input multiple-output (MIMO) downlink are investigated by using artificial noise (AN) generation and by exploiting the excess degrees-of-freedom through the random and null-space based precoders. The achievable rate expressions are derived for the estimated channel state information, and hence, the detrimental effects of channel estimation errors in designing precoders are quantified. Specifically, the achievable secrecy rate at the relayed user nodes is derived in closed-form, and thereby, the performance gap between the random and null-space based precoders is investigated. Our performance analysis reveals that the AN generation by using random precoders can be employed to design secure physical layer transmission strategies for the relay-assisted massive MIMO downlink systems. The AN generation can be useful in the finite antenna regime for guaranteeing physical layer security in the base-station-to-relay hop of the relay-assisted massive MIMO downlink. Although the AN generated at the base-station propagates to the relay-to-user hop via amplify-and-forward operation at the relay, sophisticated security provisions are needed to secure the end-to-end transmission when the relay is equipped with finitely many antennas. Consequently, the performance gap between the random and null-space based precoders gradually diminishes in the limit of infinitely many base-station antennas. Nevertheless, the achievable secrecy rate steadily vanishes with an increasing number of antennas at the passive eavesdropper.

The sum rate performance of simultaneous relay and direct massive multiple-input multiple-output (MIMO) downlink transmissions is investigated for the imperfect channel state information (CSI) case. In this context, a massive MIMO base-station transmits simultaneously to spatially distributed relayed and direct user nodes by using two independent zero-forcing based precoders. The uplink CSI at the base-station is estimated by using the non-orthogonal pilots transmitted by relayed and direct user nodes, and hence, the channel estimates are affected by pilot contamination. To this end, the detrimental effects of intra-cell pilot contamination are quantified by deriving the achievable sum rates when the number of antennas at the base-station is allowed to grow without bound. Furthermore, the performance degradation due to concurrent relayed and direct transmissions is quantified by analyzing the intra-cell interference effects for imperfect CSI cases. Our analysis and numerical results reveal that massive MIMO can be exploited for spectral efficient aggressive spatial multiplexing for simultaneous relayed and direct downlink transmissions.

The sum rate performance of cognitive multi-user massive multiple-input multiple-output (MIMO) relay networks is investigated. Specifically, a secondary relay network is underlaid in the same cell of a primary multi-user network. Both primary and secondary networks are allowed to share the same frequency spectrum. Hence, the transmit power of the secondary relay network is constrained such that the interference inflicted at the primary network due to the secondary concurrent transmissions does not exceed a predefined interference temperature. Under the aforementioned system set-up, the asymptotic signal-to-interference-plus-noise ratio and achievable sum rate expressions are derived for two specific antenna configurations at the relay, secondary and primary base-stations. Our asymptotic analysis reveals that the secondary relay network can be operated at its peak average transmit power level without degrading the performance of the primary network whenever the numbers of antennas at the relay, secondary and primary base-stations are allowed to grow without bound while keeping fixed ratios among them. Consequently, the asymptotic performance metrics for both primary and secondary networks become independent of the corresponding interference temperature. Furthermore, the intra-cell co-channel interference inflicted at the secondary network due to the primary network and vice-versa can be asymptotically mitigated. Therefore, massive MIMO technology can be exploited for successful deployments of cognitive relay networks with underlay spectrum sharing.

The asymptotic sum rate performance of multi-cell/multi-user cognitive massive multiple-input multiple-output (MIMO) systems with underlay spectrum sharing is investigated. Specifically, each cell consists of a licensed (primary) multi-user massive MIMO system and a cognitive (secondary) multi-user MIMO system which is allowed to utilize the licensed frequency spectrum provided that the intra-cell interference inflicted at the primary base-station due to the concurrent transmissions of the secondary user nodes is maintained below a predefined interference temperature. For the uplink transmission of the aforementioned system set-up, the signal-to-interference-plus-noise ratio and achievable sum rate expressions are derived for three specific antenna configurations; (i) infinitely many primary and secondary base-station antennas, (ii) infinitely many primary base-station antennas and finitely many secondary base-station antennas, and (iii) finitely many primary and secondary base-station antennas. Our asymptotic analysis reveals that the achievable sum rate expressions become independent of the primary interference threshold whenever the number of primary base-station antennas grows unbounded. Consequently, the secondary network can be operated at its maximum average transmit power level without degrading the asymptotic performance of the primary network. Therefore, the primary and secondary networks can be operated independent of each other as both intra-cell and inter-cell interference can be asymptotically mitigated by exploiting the zero-forcing detectors employed at the massive MIMO enabled base-stations.

This paper investigates the impact of co-channel interference (CCI), imperfect channel state information (CSI) and pilot contamination for multi-pair massive multiple-input multiple-output (MIMO) two-way relay networks (TWRNs). We consider a multi-cell TWRN system consisting of single-antenna user nodes and amplify-and-forward (AF) relay nodes having very large antenna arrays. Under the aforementioned channel imperfections, the asymptotic signal-to-interference-noise ratio and asymptotic sum rate expressions are derived in closed-form whenever the number of relay antennas grows unbounded with respect to the number of user nodes. For perfect CSI case, the transmit power at the user nodes and the relay can be scaled down inversely proportional to the number of antennas at the relay. Moreover, for the imperfect CSI case, these transmit powers can only be scaled down inversely proportional to the square-root of the relay antenna count. Thus, even with imperfect CSI, the benefits of employing a massive MIMO-enabled relay on transmit power savings are significant. Moreover, our analysis shows that although the detrimental effect of CCI can be asymptotically negated completely, the residual interference due to pilot contamination cannot be mitigated even in the limit of infinitely many relay antennas.

Simultaneous wireless information and power transfer techniques for multiway massive multiple-input multiple-output (MIMO) relay networks are investigated. By using two practically viable relay receiver designs, namely 1) the power splitting receiver and 2) the time switching receiver, asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived for an unlimited number of antennas at the relay. These asymptotic SINRs are then used to derive asymptotic symmetric sum rate expressions in closed form. Notably, these asymptotic SINRs and sum rates become independent of radio frequency-to-direct current (RF-to-DC) conversion efficiency in the limit of infinitely many relay antennas. Moreover, tight average sum rate approximations are derived in closed form for finitely many relay antennas. The fundamental tradeoff between the harvested energy and the sum rate is quantified for both relay receiver structures. Notably, the detrimental impact of imperfect channel state information (CSI) on the MIMO detector/precoder is investigated, and thereby, the performance degradation caused by pilot contamination, which is the residual interference due to nonorthogonal pilot sequence usage in adjacent/cochannel systems, is quantified. The presence of cochannel interference (CCI) can be exploited to be beneficial for energy harvesting at the relay, and consequently, the asymptotic harvested energy is an increasing function of the number of cochannel interferers. Notably, in the genie-aided perfect CSI case, the detrimental impact of CCI for signal decoding can be cancelled completely whenever the number of relay antennas grows without bound. Nevertheless, the pilot contamination severely degrades the sum rate performance even for infinitely many relay antennas.

The performance of multi-user massive MIMO amplify-and-forward relay networks with linear zero-forcing detectors is investigated by deriving closed-form sum rate upper bounds for finitely many antennas and asymptotic approximations for infinitely many antennas at the relay and destination. The acquisition of channel state information (CSI) is investigated by using minimum mean square error channel estimation, and thereby, the impact of imperfect CSI on transmit power scaling laws at the user nodes and relay is studied. For genie-aided perfect CSI case, the transmit power at the user nodes and/or relay can be scaled down inversely proportional to the number of destination antennas. Nevertheless, for the imperfect CSI case, the transmit power can only be scaled down inversely proportional to the square-root of the destination antenna count. Specifically, asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived for three transmit power scaling laws for both perfect and imperfect CSI cases and are used for deriving the corresponding asymptotic sum rates for the case in which the antenna counts at the relay and destination grow without bound while keeping a fixed ratio. Notably, these asymptotic SINRs and sum rates become independent of the fast fading component of the wireless channel for infinitely many relay and destination antennas, and consequently, paving the way to low-complexity medium access control layer operations and reduced latency in the air interface.

Simultaneous wireless information and power transfer for multi-way relay networks with massive multiple-input multiple-output (MIMO) is investigated. By using two practically viable relay receiver designs, namely (i) the power splitting receiver and (ii) the time switching receiver, asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived for an unlimited number of antennas at the relay. These asymptotic SINRs are then used to derive asymptotic symmetric sum rate expressions in closed-form. Notably, these asymptotic SINRs and sum rates become independent of radio frequency-to-direct current (RF-to-DC) conversion efficiency in the limit of infinitely many relay antennas. Moreover, the fundamental trade-off between the harvested energy and the achievable sum rate is quantified for both relay receiver structures. This analysis reveals that the transmit power of each user node can be scaled down inversely proportional to the number of relay antennas, and the corresponding asymptotic SINR and sum rate expressions become independent of the fast fading effects of the wireless channels. The presence of co-channel interference (CCI) can be exploited to be beneficial for energy harvesting at the relay, and consequently, the asymptotic harvested energy is an increasing function of the number of co-channel interferers. Nevertheless, the detrimental impact of CCI for signal decoding can be cancelled completely whenever the number of relay antennas grows without bound.

The detrimental effects of channel aging due to relative movements of user nodes and scatterers in multi-way relay networks (MWRNs) with massive multiple-input multiple-output (MIMO) are investigated. To this end, asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived by exploiting a time-varying fading channel model for the case in which the number of antennas at the relay grows without bound. Further, the impact of channel estimation errors and co-channel interference on the performance of MIMO MWRNs with massive MIMO is studied, and thereby, the cumulative effect of pilot contamination and outdated/delayed channel state information due to non-orthogonal pilot sequence reuse and channel aging, respectively, is quantified. The closed-form asymptotic SINRs are then used to derive asymptotic symmetric and asymmetric sum rate expressions. These asymptotic SINR and sum rate expressions are independent of the fast fading effects of the wireless channel. Our results reveal that the transmit power of each user can be scaled down inversely proportional to the relay antenna count for the channel aging only case. Nevertheless, when the system is affected by both pilot contamination and channel aging, the user transmit powers can only be scaled inversely proportional to the square-root of the number of relay antennas. Our results show that the effects of channel aging and pilot contamination significantly degrade the system performance even with relays having very large antenna arrays.

The asymptotic performance of multi-user amplify-and-forward relay networks with massive MIMO is investigated. By using transmit power scaling laws at the user nodes, the asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived when the antenna counts at the relay and destination are allowed to grow unbound, and thereby, the asymptotic sum rate expressions are obtained. Notably, these asymptotic SINRs and sum rates are independent of the fast fading component of the wireless channel, and consequently, yield a low-complexity medium access control layer and reduced latency in the air interface. Further, the detrimental impact of practical transmission impairments, including (i) imperfect channel state information (CSI), (ii) co-channel interference (CCI), and (iii) pilot contamination is studied by deriving the corresponding asymptotic SINRs and sum rates. For the perfect CSI case, the transmit power at each user node can be scaled down inversely proportional to the antenna count at the relay without degrading the system performance. However, for the imperfect CSI case, the transmit powers of the user nodes can only be scaled down inversely proportional to the square-root of the number of relay antennas. Interestingly, for the perfect CSI case, the presence of CCI neither affects these transmit power scaling laws nor degrades the asymptotic SINR. However, pilot contamination significantly limits the system performance.

Relay selection strategies help to improve spectral and energy efficiencies, to enhance transmission robustness, or to reduce latency in multi-relay cooperative networks. Two novel relay selection strategies are proposed and analyzed here for multiple-input multiple-output (MIMO) amplify-and-forward (AF) two-way relay networks (TWRNs) with spatial multiplexing. Specifically, they are designed to maximize the effective end-to-end signal-to-noise ratio (SNR), and thereby minimize the overall outage probability or maximize the achievable sum rate. Interestingly, the first strategy amounts to maximizing the minimum of the eigenvalues of the Wishart matrices from the selected relay to the two user nodes. Counter-intuitively, the latter strategy amounts to maximizing the minimum of the determinant of the same Wishart matrices. The performance of these two strategies is investigated by deriving lower/upper bounds of the overall outage probability and the average sum rate approximations in closed form. Further, the asymptotic high-SNR approximations of the outage probability are derived, and thereby, the achievable diversity-multiplexing tradeoff is quantified. This tradeoff reveals that whenever the sum of relay antennas is fixed, the achievable diversity order is always a constant, and hence, the multiplexing gain can indeed be improved by equally distributing antennas among the available set of relays. Our results reveal that relay selection indeed significantly alleviates the inherent diversity-gain loss associated with the use of available degrees of freedom for spatial multiplexing.

The performance of amplify-and-forward (AF) multi-way relay networks (MWRNs) with very large relay antenna arrays is investigated. Asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived when the number of antennas at the relay is substantially higher than the number of user nodes. These asymptotic SINRs are independent of the fast fading component of the wireless channel, and hence, the latency in the air interface due to fast fading can be reduced. The transmit power at each user node and/or relay can be scaled down inversely proportional to the number of antennas at the relay without degrading the system performance. The asymptotic SINR expressions are then used to derive asymptotic spectral and energy efficiencies of AF MWRNs with symmetric and asymmetric data traffic. These spectral and energy efficiency results show that MWRNs with massive MIMO achieve substantial multiplexing gains while allowing the transmit powers of user nodes to become infinitesimal.

Two transmission strategies, namely (i) pairwise zero-forcing transmission and (ii) non-pairwise zero-forcing transmission, for multiple-input multiple-output (MIMO) amplify-and-forward (AF) multi-way relay networks (MWRNs) are analytically studied. To this end, lower and upper bounds of the outage probability, the corresponding high signal-to-noise ratio outage probability approximations, the achievable sum rate, and the fundamental diversity-multiplexing trade-off are derived in closed-form. The proposed pairwise zero-forcing transmission strategy possesses a lower practical implementation complexity as each node requires only the instantaneous respective node-to-relay channel knowledge. Counter intuitively, the non-pairwise zero-forcing transmission strategy achieves higher spatial multiplexing gains over the pairwise counterpart at the expense of higher relay processing complexity and more stringent channel state information requirements. Moreover, numerical results are presented to further validate our analysis and thereby to obtain valuable insights into practical MIMO AF MWRN implementation.

The sum rate of multiple-input multiple-output (MIMO) amplify-and-forward (AF) two-way relay networks (TWRNs) with zero-forcing (ZF) transmission is analyzed. Namely, (1) ZF at the two sources for transmission and reception and (2) ZF at the relay for transmission and reception, are treated. Specifically, the exact sum rate expressions and corresponding high signal-to-noise ratio (SNR) approximations are derived for uncorrelated and min-semi-correlated (i.e., correlation exists only at the minimum antenna terminal) Rayleigh fading cases in closed-form. Moreover, the closed-form upper and lower bounds of the sum rate are derived for max-semi-correlated (i.e., correlation exists only at the maximum antenna terminal) and doubly-correlated Rayleigh fading cases. Notably, these sum rate bounds and high SNR approximations provide valuable insights into practical MIMO AF TWRN system-design and the maximum achievable spatial multiplexing gain. All the analyses are verified by using Monte-Carlo simulations.

The sum rate of multiple-input multiple-output (MIMO) amplify-and-forward (AF) two-way relay networks (TWRNs) with transmit/receive zero-forcing (ZF) is analytically studied. Specifically, the exact sum rate expressions are derived for uncorrelated and semi-correlated Rayleigh fading cases in closed-form. Moreover, the closed-form upper and lower bounds of the sum rate are derived for doubly-correlated Rayleigh fading. In particular, these sum rate bounds are tight, and consequently, serve as benchmarks providing valuable insights into practical MIMO AF TWRN system-design. All the analyses are verified by using Monte-Carlo simulations.

A pair-wise transmit/receive zero-forcing (Tx/Rx ZF) transmission strategy is proposed and analyzed for multiple-input multiple-output (MIMO) amplify-and-forward (AF) multi-way relay networks (MWRNs). The performance of this system set-up is studied by deriving lower and upper bounds of the overall outage probability, the corresponding high signal-to-noise ratio outage approximations, and the achievable diversity-multiplexing trade-off. The proposed pair-wise Tx/Rx ZF transmission strategy possesses a lower implementation complexity as each source requires only the instantaneous respective source-to-relay channel knowledge. Moreover, our analysis provides valuable insights into practical MIMO AF MWRN implementation.

A novel joint beamforming and antenna selection strategy is proposed and analyzed for two-way multiple-input multiple-output amplify-and-forward relay networks. Specifically, this strategy selects the optimal transmit precoding and receiver filtering vectors at the two source terminals, and an optimal transmit/receive antenna at the relay terminal based on minimizing the overall outage probability. The performance of this transmission strategy is quantified by first deriving the exact cumulative distribution function of the effective signal-to-noise ratio (SNR), and thereby, evaluating the overall outage probability, its asymptotically exact high SNR approximation and achievable diversity order. For a multiple relay scenario, a joint relay, beamforming, and antenna selection strategy is proposed and analyzed as well. Interestingly, our selection strategies are optimal in the sense of the overall outage probability, and hence, in the sense of achievable diversity order as well.

Two new transmit/receive (Tx/Rx) antenna selection strategies are proposed and analyzed for two-way multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay networks. These two strategies select the best transmit and receive antennas at the two sources and the relay based on (i) minimizing the overall outage probability and (ii) maximizing the sum-rate. The performance of these selection strategies is quantified by deriving the overall outage probability, its high SNR approximation and the diversity order providing valuable insights into practical system-designs. Importantly, multiple relay and multiple user two-way relay network set-ups are also treated by proposing and analyzing (i) joint relay and antenna selection strategies, and (ii) joint user, relay and antenna selection strategies, respectively. Interestingly, our outage probability results reveal that the joint relay and antenna selection strategies achieve significant diversity and array gains over those of their single relay counterparts. In fact, the diversity orders of individual relayed-branches accumulate to yield the overall diversity of the multi-relay networks. For example, at 10-2outage probability, the dual-antenna relay provides a 14 dB gain over a single-antenna relay, and having two dual-antenna relays improves the gain by another 5 dB. Moreover, the performance degradation due to practical transmission impairments (i) feedback delays, (ii) spatially-correlated fading and (iii) non-identically distributed fading is quantified. Impact of channel prediction to circumvent outdated channel state information for antenna selection due to feedback delay is also studied. All the derivations are validated through Monte-Carlo simulations.

A comprehensive performance analysis framework for dual-hop multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay networks with hop-by-hop beamforming (i.e. both source and relay perform beamforming) is presented. The system performance degradation due to practical transmission impairments (i) feedback delays, (ii) channel estimation errors and (iii) spatially-correlated fading is quantified. To this end, closed-form expressions for the cumulative distribution function of the end-to-end signal-to-noise ratio, its moment generating function, the outage probability, and the average bit error rate (BER) are derived. The asymptotic high SNR approximations of the outage probability and average BER are derived to obtain valuable system-design insights such as the diversity order and array gain. In order to illustrate the usefulness of our analysis, four applications, which employ dual-hop MIMO relaying with hop-by-hop beamforming, are also presented and analyzed. Furthermore, our analyses are validated through Monte-Carlo simulations.

Four joint relay and antenna selection strategies for dual-hop amplify-and-forward (AF) multiple-input multiple-output relay networks are studied. Two of them require full channel state information (CSI) whereas the other two require only partial CSI. The relays are either channel-assisted AF or fixed-gain AF type. The first joint selection strategy involves choosing the best relay and the best single transmit antennas at the source and the relay. The second strategy jointly involves choosing the best relay and the best single transmit/receive antenna pairs at the source-to-relay and relay-to-destination channels. Moreover, two partial selection strategies, which can be used when the global CSI is not available, are also proposed and analyzed. In order to quantify the system performance analytically, the exact outage probability of all selection strategies is derived in closed-form. Direct insights into the system-design are obtained by deriving the asymptotic outage probability, asymptotic average symbol error rate, diversity order and array gain.

A novel transmit/receive (Tx/Rx) antenna selection strategy is proposed and analyzed for two-way multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay networks. This strategy involves choosing the best transmit and receive antennas at the two sources and the relay based on the minimization of the overall outage probability. The performance of the proposed selection strategy is quantified by deriving the overall outage probability and its high SNR approximation. Specifically, the diversity order is derived to obtain valuable insights into practical system designing. In particular, our results are extended to cater the multiple relay scenario, and thereby, a joint relay and Tx/Rx antenna selection strategy is proposed and analyzed. To this end, the overall outage probability, its high SNR approximation and diversity order are derived. Our numerical results show that the proposed selection strategies achieve the full diversity order. All the analyses are validated through Monte-Carlo simulations.

A comprehensive performance analysis of dual-hop multiple-input multiple-output amplify-forward relay networks with hop-by-hop beamforming is presented. The impact of practical transmission impairments; (i) feedback delays, (ii) channel estimation errors and (iii) spatially-correlated fading on the system performance is studied. Specifically, the amount of performance degradation due to these impairments are quantified analytically and illustrated through numerical results. Numerical results show that these impairments degrade the system performance significantly. The cumulative distribution function of the end-to-end signal-to-noise ratio is derived and used to obtain the moment generating function, the outage probability, and the average symbol error rate (SER) in closed-form. The asymptotic outage probability and average SER are derived to obtain valuable system-design insights such as the diversity order and array gain. Further, our analyses are validated through Monte-Carlo simulations.

A novel approximation for the end-to-end signal-to-noise ratio (e2e SNR) of multi-hop (N≥2) fixed-gain amplify-and-forward (FG-AF) relay networks over independent and non-identically distributed Nakagami-m fading channels is proposed. Two types of FG-AF relays; (i) blind-AF, and (ii) semi-blind-AF are treated. The cumulative distribution and the moment generating function of the proposed e2e SNR approximation are derived in closed-form and used to derive the outage probability, the average symbol error rate, and the generalized SNR moments. The resulting performance metrics for the blind-AF relay case are asymptotically exact and thus, the asymptotic outage probability, the asymptotic average SER, the diversity order, and the coding gain are derived. Numerical and simulation results are presented to verify the comparative performance against the exact performance metrics and existing bounds. Our results reveal that the proposed performance approximations outperform the existing bounds in most of the cases.

A new class of upper bounds on the end-to-end signal-to-noise ratio (SNR) of channel-assisted amplify-and-forward (AF) multi-hop (N ≥ 2) relay networks is presented. It is the half-harmonic mean of the minimum of the first P ≥ 0 hop SNRs and the minimum of the remaining N-P hop SNRs. The parameter P varies between 0 to N and may be chosen to provide the tightest bound. The closed-form cumulative distribution function and moment generating function are derived for independent and non-identically distributed Rayleigh fading and for independent and identically distributed Nakagami-m fading, where m is an integer. The resulting outage probability and the average symbol error rate bounds are asymptotically-exact. The asymptotic-exactness holds for any 0 ≤ P ≤ N. As applications, two cases of multi-hop multi-branch relay networks (i) the best branch selection and (ii) maximal ratio combining reception are treated. Numerical results are provided to verify the comparative performance against the existing bounds.

In this paper, an analytical framework is developed for the performance analysis of three transmit antenna selection (TAS) strategies for dual-hop multiple-input multiple-output channel-assisted amplify-and-forward (CA-AF) relay networks over Rayleigh fading. The cumulative distribution function of a lower bound of the end-to-end signal-to-noise ratio (SNR) of the optimal TAS strategy is derived and used to obtain the upper bounds of the outage probability and the average symbol error rate (SER). The exact moment generating functions (MGFs) of the end-to-end SNR of two suboptimal TAS strategies are also derived for the ideal CA-AF MIMO relay networks. These MGFs are then used to present accurate and efficient closed-form approximations to evaluate the outage probability and average SER. Numerical and Monte-Carlo simulation results are provided to analyze the performance of the system and to verify the accuracy of our analytical framework.

In this paper, the effect of feedback delays on the performance of multiple-input multiple-output antenna amplify-and-forward relay networks with the best transmit/receive antenna pair selection over Rayleigh fading is studied. The cumulative distribution function and the moment generating function of the end-to-end signal-to-noise ratio (SNR) are derived. Closed-form expressions for the outage probability, average symbol error rate (SER), and the SNR moments are also derived. To gain further insights, the asymptotic outage probability, average SER, diversity order, and coding gain are presented. Numerical results and Monte-Carlo simulations are provided to illustrate the detrimental effects of feedback delays on the system performance and to verify the accuracy of our analysis.

The performance of a multi-hop amplify-and-forward relay network is analyzed. The source and destination terminals are equipped with multiple-antennas and the relays with single-antennas. The cumulative distribution function and the moment generating function of two tight upper bounds of the end-to-end signal-to-noise ratio are derived. The lower bounds for the outage probability and the average symbol error rate (SER) are also derived. The results take into account the source-relay and the relay-destination correlation matrices; the uncorrelated case is treated as well. The asymptotic outage probability, average SER, diversity order and coding gain are also derived. Numerical results and Monte-Carlo simulations are presented to analyze the system performance and show the tightness of the proposed bounds.

In this paper, we propose an output-threshold multiple relay selection scheme for dual-hop multi-branch cooperative wireless networks. The proposed scheme selects the first Lcarbitrary ordered relays out of L relays such that the maximal ratio combined signal-to-noise-ratio (SNR) of the Lcrelayed paths and the direct path barely exceeds a preset threshold. Closed-form expressions are derived for the cumulative distribution function, the probability density function, and the moment generating function of an output SNR upper bound for independent and identically distributed Rayleigh fading. Lower bounds for the outage probability, the average symbol error rate, and the average number of selected relays are also derived. Moreover, upper bounds for the average output SNR and the ergodic capacity are also derived. The analytical results are verified via the Monte-Carlo simulation. The performance of our proposed scheme is compared to that of the existing relay selection schemes. The proposed schemes provide more flexibility in utilizing bandwidth and spatial diversity in cooperative wireless networks.

This paper presents a new upper bound on the end-to- end signal-to-noise ratio (SNR) of channel-assisted amplify-and-forward (AF) multi-hop relay networks. The harmonic mean of the minimum of the first P ≥ 0 hop SNRs and the minimum of the remaining hop SNRs forms the new bound. Closed-form expressions are derived for the cumulative distribution function and the moment generating function of this SNR upper bound for independent and non-identically distributed Rayleigh, and independent and identically distributed Nakagami-m fading, where m is an integer. The outage probability and the average symbol error rate bounds are also derived. Our proposed bounds are compared against the existing bounds.