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In this paper, we design receivers for filter bank multicarrier-based (FBMC-based) massive MIMO considering practical aspects such as channel estimation and equalization. In particular, we propose a spectrally efficient pilot structure and a channel estimation technique in the uplink to jointly estimate all the users’ channel impulse responses. We mathematically analyze our proposed channel estimator and find the statistics of the channel estimation errors. These statistics are incorporated into our proposed equalizers to deal with the imperfect channel state information (CSI) effect. We revisit the channel equalization problem for FBMC-based massive MIMO, address the shortcomings of the existing equalizers in the literature, and make them more applicable to practical scenarios. The proposed receiver in this paper consists of two stages. In the first stage, a linear combining of the received signals at the base station (BS) antennas provides a coarse channel equalization and removes any multiuser interference. In the second stage, a per subcarrier fractionally spaced equalizer (FSE) takes care of any residual distortion of the channel for the user of interest. We propose an FSE design based on the equivalent channel at the linear combiner output. This enables the applicability of our proposed technique to small and/or distributed antenna setups such as cell-free massive MIMO. Finally, the efficacy of the proposed techniques is corroborated through numerical analysis. [ABSTRACT FROM AUTHOR]

A new approach of channel estimation for multiantenna systems is put forward in this paper, which can be adopted in high-mobility situations such as high speed trains. The channel impulse response is abstracted as three domains to improve the modeling accuracy. Both the time-domain preamble and the frequency-domain pilot are adopted in the orthogonal frequency division multiplexing (OFDM) frame. First, the training in time domain is exploited to obtain the partial common support of the channel. Then, the pilot location optimized by the genetic algorithm is employed to build the framework of structured compressive sensing and recover the channel. A novel compressive recovery algorithm called adaptive support-aware block orthogonal matching pursuit for multiple input multiple output-OFDM systems is proposed to solve the problem. It is manifested in the simulation that the scheme in this paper outperforms the traditional ones in both recovery probability, mean square error, and bit error rate over the doubly selective channel with low computational complexity. [ABSTRACT FROM AUTHOR]

Ambient backscatter, an emerging green communication technology, has aroused great interest from both academia and industry. One open problem for ambient backscatter communication (AmBC) systems is channel estimation for a massive-antenna reader. In this paper, we focus on a channel estimation problem in AmBC systems with a uniform linear array at the reader consisting of large number of antennas. We first design a two-step method to jointly estimate channel gains and direction of arrivals (DoAs), and then refine the estimates through angular rotation. Additionally, Cramér–Rao lower bounds are derived for both the modulus of the channel gain and the DoA estimates. Simulations are then provided to validate the analysis, and to show the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper introduces a hybrid pilot-aided channel estimation technique for mitigating the effect of pilot contamination for the uplink of multi-cell multiuser massive MIMO systems. The proposed hybrid pilot is designed such that it enjoys the complementary advantages between time-multiplexed (TM) pilot and time-superimposed (TS) pilot and, thereby, allows superior solution to the conventional pilot schemes. We mathematically characterize the impact of hybrid pilot on the massive MIMO uplink by deriving a closed-form approximation for the uplink achievable rate. In the large-number-of-antennas regime, we obtain the asymptotically optimal solution for the hybrid pilot by jointly designing the TM pilot and the TS pilot. It is shown that either TM pilot or TS pilot has the advantages for large frame-size and limited frame-size transmission, respectively, while the hybrid pilot scheme can offer a superior performance to that employing either TM pilot or TS pilot. Numerical results demonstrate the effectiveness of the proposed design. [ABSTRACT FROM AUTHOR]

This paper investigates the downlink (DL) rate of multicell massive multiuser multiple-input and multiple-output systems over Ricean fading channels that takes into account channel estimation errors. To acquire channel state information at all users, beamforming training (BT) is examined. Considering both maximum-ratio transmission (MRT) and zero forcing, this paper derives closed-form expressions on the lower bound of the achievable rates for two cases, with or without BT. With the obtained expressions, Bernoulli's inequality is invoked to find the ranges for the length of DL pilots such that the sum spectral efficiency of the scheme with BT is superior to that of the scheme without BT, and vice versa. Various power scaling laws concerning DL data and pilot transmit powers and uplink pilot transmit power are analyzed. Numerical results corroborate the accuracy of the closed-form expressions. In particular, the results show that employing BT with MRT processing is only preferred in environments having a high signal-to-noise ratio, low mobility, and small Ricean $K$ -factors. [ABSTRACT FROM AUTHOR]

This paper investigates the uplink transmission in multicell multiuser multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. The system model considers imperfect channel estimation, pilot contamination (PC), and multicarrier and multipath channels. Analytical expressions are first presented on the mean square error (MSE) of two classical channel estimation algorithms [i.e., least squares (LS) and minimum mean square error (MMSE)] in the presence of PC. Then, a simple H-infinity (H-inf) channel estimation approach is proposed to have good suppression to PC. This approach exploits the space-alternating generalized expectation–maximization (SAGE) iterative process to decompose the multicell multiuser MIMO (MU-MIMO) problem into a series of single-cell single-user single-input single-output (SISO) problems, which reduces the complexity significantly. According to the analytic results given herein, increasing the number of pilot subcarriers cannot mitigate PC, and a clue for suppressing PC is obtained. It is shown from the results that the H-inf has better suppression capability to PC than classical estimation algorithms. Its performance is close to that of the optimal MMSE as the length of channel impulse response (CIR) is increased. By using the SAGE process, the performance of the H-inf does not degrade when the number of antennas is large at the base station (BS). [ABSTRACT FROM PUBLISHER]

Pilot contamination (PC) is a major problem in massive multiple-input multiple-output (MIMO) systems. This paper proposes a novel channel estimation scheme for such a system in Rician fading channels. First, the possible angle of arrivals (AOAs) of users served by a base station (BS) are derived by exploiting the channel statistical information, assuming a traditional pilot structure, where the pilots for the same-cell users are orthogonal but are identical for the same-indexed users from different cells. Although, with this pilot structure, the channel state information (CSI) derived contains CSI from other-cell users caused by PC, the line-of-sight (LOS) component of the desired user is PC-free when the number of antennas equipped at the BS is large. Then, based on the AOAs and the contaminated CSI, the LOS component of each user served by a BS is estimated, and data are detected by using the derived LOS components. Finally, the decoded data are used to update the CSI estimate via an iterative process. The achievable spectral efficiency of the proposed scheme is analyzed in detail, and simulation results are presented to compare the performance of the proposed scheme with that of three existing schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we analyze the performance of the uplink communication of massive multicell multiple-input multiple-output (MIMO) systems under the effects of pilot contamination and delayed channels because of terminal mobility. The base stations (BSs) estimate the channels through the uplink training and then use zero-forcing (ZF) processing to decode the transmit signals from the users. The probability density function (pdf) of the signal-to-interference-plus-noise ratio (SINR) is derived for any finite number of antennas. From this pdf, we derive an achievable ergodic rate with a finite number of BS antennas in closed form. Insights into the impact of the Doppler shift (due to terminal mobility) at the low signal-to-noise ratio (SNR) regimes are exposed. In addition, the effects on the outage probability are investigated. Furthermore, the power scaling law and the asymptotic performance result by infinitely increasing the numbers of antennas and terminals (while their ratio is fixed) are provided. The numerical results demonstrate the performance loss for various Doppler shifts. Among the interesting observations revealed is that massive MIMO is favorable even under channel aging conditions. [ABSTRACT FROM PUBLISHER]

Massive multiple-input multiple-output (MIMO) is widely recognized as a promising technology for future 5G wireless communication systems. To achieve the theoretical performance gains in massive MIMO systems, accurate channel-state information at the transmitter (CSIT) is crucial. Due to the overwhelming pilot signaling and channel feedback overhead, however, conventional downlink channel estimation and uplink channel feedback schemes might not be suitable for frequency-division duplexing (FDD) massive MIMO systems. In addition, these two topics are usually separately considered in the literature. In this paper, we propose a joint channel training and feedback scheme for FDD massive MIMO systems. Specifically, we first exploit the temporal correlation of time-varying channels to propose a differential channel training and feedback scheme, which simultaneously reduces the overhead for downlink training and uplink feedback. We next propose a structured compressive sampling matching pursuit (S-CoSaMP) algorithm to acquire a reliable CSIT by exploiting the structured sparsity of wireless MIMO channels. Simulation results demonstrate that the proposed scheme can achieve substantial reduction in the training and feedback overhead. [ABSTRACT FROM PUBLISHER]

Massive multiple-input–multiple-output (MIMO) antenna system implies the use of a large number of base station (BS) antennas to serve a relatively small number of user terminals (UTs) for extraordinary spectral efficiency. However, its performance is limited by pilot contamination due to unavoidable reuse of pilot sequences from UTs in different cells. In this paper, we analyze the performance of massive MIMO zero-forcing (ZF) systems using the time-shifted pilot scheme, which was known to combat pilot contamination effectively using conjugate beamforming if there is a very large number of antennas. We derive expressions for achievable sum rates and the signal-to-interference-plus-noise ratios (SINRs) of forward and reverse links if the number of BS antennas is finite. Then, the impact of system parameters, such as cell radius, transmit power, group number (a parameter related to the time-shifted pilot scheme), BS antenna number, etc., on the system performance are revealed. Our model embraces a series of previous works as special cases. Moreover, we compare the performance of conjugate and ZF precoders, from which a simple but effective large-scale fading-based UT scheduling scheme is proposed to enhance the system throughput. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the uplink performance of a multi-cell massive MIMO relay network, where the base stations (BSs) and the relay stations (RSs) are equipped with large scale antennas and conventional number of antennas, respectively. In each cell, a portion of users communicate with the BS directly while others are aided by the RSs, which are called direct transmission users (DTUs) and relayed transmission users (RTUs), respectively. The two types of users and RSs of all cells share the same time-frequency resource and thus interfere with each other. After describing the system model, we investigate linear minimum mean-squared error channel estimation for the DTUs and RTUs and derive tractable expressions of channel estimation accuracy. With maximal ratio combining and zero-forcing detections based on the estimated channel state information (CSI), we derive the closed-form lower bound and approximation of the achievable rates for DTUs and RTUs to reveal their mutual impact, including intra- and inter-cell interference and pilot contamination. Then, we propose the power scaling law, which proves to be a simple and energy-efficient way to enable the coexistence of DTUs and RTUs in all cells. Furthermore, an optimal power allocation (OPA) scheme is designed based on the proposed power scaling law to maximize the system sum rate. Numerical results verify the accuracy of our theoretical analysis and the effectiveness of the OPA scheme to guarantee performance improvement and fairness simultaneously. [ABSTRACT FROM AUTHOR]

Predictor antenna channel measurements from a 64-antenna base station are used to investigate the effects of channel aging on the precoder design for high-mobility users in a non-line-of-sight (NLOS) massive multiple-input multiple-output (M-MIMO) environment. The effects are evaluated in terms of received downlink (DL) signal-to-interference-and-noise ratio (SINR) and the corresponding ergodic capacity bound. A simulated velocity of 150 km/h is used with a carrier frequency of 2.18 GHz. Maximum ratio (MR) and a codebook-based precoders are used to evaluate single-user transmission; and zero-forcing (ZF), regularized zero-forcing (RZF), and minimum mean-squared error (MMSE) precoders are used to evaluate multi-user transmission with up to nine active users in a cell. Furthermore, predictor antenna predictions are evaluated as a mean of combating channel aging. It is also investigated how the predictor antenna can be used during data reception. Simulations show that outdated channel estimates significantly reduce the SINR and consequently the capacity for all investigated transmission techniques. Basic predictor antenna predictions outperform the use of outdated channel estimates for delays larger than 0.6 ms. In single-user transmission, channel prediction can improve the capacity by 6–14%. The gain from multi-user transmission typically disappears when using outdated channel estimates older than 1 ms. In contrast, the use of predictor antennas enables MIMO for these high-mobility users, which is demonstrated to increase the capacity bound by 100% compared to 1 ms old channel estimates. [ABSTRACT FROM AUTHOR]

Channel estimation for downlink millimeter wave (mmWave) multiuser multiple-input-multiple-output (MU-MIMO) communications over a time-varying channel is demandingly challenging. This is due to a massive number of channel coefficients to be estimated and the severe propagation loss of mmWave transmissions. To tackle this problem, this paper proposes an effective channel estimation scheme for time-varying mmWave channels. Discovering the property that the variations of angles of arrival/departure (AoAs/AoDs) are much slower than that of path gains, we propose a novel transmission frame structure, where the channel estimation is decoupled into two separated stages including AoAs/AoDs estimation followed by path gains estimation. In the first stage, the sparse nature of mmWave channels is leveraged to formulate the AoAs/AoDs estimation into a block-sparse signal recovery problem, and we develop an adaptive angle estimation algorithm to estimate the AoAs/AoDs. In the second stage, the pilot beamforming based on the estimated AoAs/AoDs is designed aiming for maximizing the desired pilot power so that the path gains can be accurately estimated. Simulation results demonstrate that the proposed scheme can effectively estimate the time-varying mmWave channels with a small number of pilots. [ABSTRACT FROM AUTHOR]

Channel estimation is challenging for millimeter-wave massive MIMO with hybrid precoding, since the number of radio frequency chains is much smaller than that of antennas. Conventional compressive sensing based channel estimation schemes suffer from severe resolution loss due to the channel angle quantization. To improve the channel estimation accuracy, we propose an iterative reweight-based superresolution channel estimation scheme in this paper. By optimizing an objective function through the gradient descent method, the proposed scheme can iteratively move the estimated angle of arrivals/departures towards the optimal solutions, and finally realize the superresolution channel estimation. In the optimization, a weight parameter is used to control the tradeoff between the sparsity and the data fitting error. In addition, a singular value decomposition-based preconditioning is developed to reduce the computational complexity of the proposed scheme. Simulation results verify the better performance of the proposed scheme than conventional solutions. [ABSTRACT FROM AUTHOR]

This paper studies the statistical channel state information (S-CSI) acquisition problem in the nonstationary massive multiple-input multiple-output (MIMO) environment, where both the instantaneous and statistical channel states are time varying. First, we set up a hidden statistical channel state Markov model (HSCSM model). Then, the parameter of the HSCSM model is estimated through the observed sequence of received signals. Next, based on the HSCSM model and its estimated parameter, the S-CSI is obtained through a maximum a-posteriori decision process. Simulation results show that an accurate S-CSI acquisition can be achieved by the proposed approach in the nonstationary massive MIMO environment. In addition, the estimation accuracy rate of the proposed approach increases with the length of observation sequence as well as the number of antennas, where a tradeoff between them exists given a limited computing ability/storage space. [ABSTRACT FROM AUTHOR]

In a massive multiple-input multiple-output (MIMO) system, the serious pilot contamination problem severely restricts its ability to boost the spectrum utilization. To tackle this problem, the conventional concept of softly reusing the spectrum resources for the inner regions of the neighboring cells has been extended to reuse the pilot resources so as to accommodate more users. Alternatively, properly selecting the users to reuse the pilots among the neighboring cells can alleviate the pilot contamination problem as well. In this paper, we delicately integrate these two concepts to properly reuse the pilots allocated to the outer regions of the cells. By well designing the hazard- and secure-edge regions to manage the pilot reuse, the increment of interference can be effectively suppressed, and, consequently, the more accommodated users can contribute to the remarkably higher sum data rates. Furthermore, via some adaptive power adjustment for the users within different regions, the user data rates can further be significantly enhanced. [ABSTRACT FROM AUTHOR]

In this paper, the feasibility of a new downlink transmission mode in massive multi-input multi-output (MIMO) systems is investigated with two types of users, i.e., the users with only statistical channel state information (CSI) and the users with imperfect instantaneous CSI. The problem of downlink precoding design with mixed utilization of statistical and imperfect instantaneous CSI is addressed. We first theoretically analyze the impact of the mutual interference between the two types of users on their achievable rate. Then, considering the mutual interference suppression, we propose an extended zero forcing and an extended maximum ratio transmission precoding methods to minimize the total transmit power of base station and to maximize the received signal power of users, respectively. Thanks to the exploitation of statistical CSI, pilot-based channel estimation is avoided enabling more active users, higher system sum rate, and shorter transmission delay. Finally, simulations are performed to validate the accuracy of the theoretical analysis and the advantages of the proposed precoding methods. [ABSTRACT FROM PUBLISHER]

In this paper, we study the performance of the training based two-step channel estimation in two-way multiple-input multiple-output relay systems over Rayleigh channels. We first estimate the forward channel during the first phase. During the second phase for the composite channel estimation, singular value decomposition based maximum likelihood method is applied in two way relay systems, which is extended from one way relay systems. Hence, the backward channel is estimated with the given forward channel and composite channel. In general, the proposed estimation scheme can also be extended from the system with a single relay antenna to multiple relay antennas. Moreover, we derive the proposed training sequences and relay gain that aim to minimizes the trace of the approximate Bayesian Cramér–Rao lower bound with respect to the individual channels. The numerical results are shown that although the training sequence is designed to improve individual channel mean square error performance, it can also improve composite channel estimator performance. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the individual channel estimation over the three-node one-way relay network, where all the nodes are equipped with multiple antennas. We first examine one simple but representative scenario, where the relay node is equipped with a single antenna. An iterative linear minimum mean-square-error (LMMSE) method, which has fast convergence speed, is proposed to estimate the individual channels. We derive the closed-form least square channel estimator through the matrix unitary diagonalization to provide one good initialization point for the iterative LMMSE estimator. To evaluate the performance of the proposed algorithm, we present two performance lower bounds: Bayesian Cramér lower bound and linear estimation lower bound (LELB). Then, the training block and the relay amplification factor are optimized through minimizing the LELB. After that, our studies are extended to the general case, where all the nodes are equipped with multiple antennas. Finally, numerical results are provided to corroborate our proposed studies. [ABSTRACT FROM PUBLISHER]

The cooperative communication or distributed multiple-input multiple-output (DMIMO) system, combined with orthogonal frequency division multiplexing (OFDM), is considered as an emerging paradigm for link reliability, high data rate, and coverage extension in fifth-generation (5G) wireless communication systems. The DMIMO system employs multiple relays with single or multiple antennas that opportunistically form virtual antenna array (VAA) in between the source and destination. Moving to the DMIMO-OFDM system from the conventional network with uncoordinated nodes requires robust synchronization and tracking. The signal received at the destination is characterized by multiple timing offsets (MTOs), multiple carrier frequency offsets (MCFOs), and frequency-selective channel gains. In this paper, we address the issue of joint time frequency and channel gain estimation for the estimate-and-forward (EF) relaying protocol. EF is a cost-effective solution but provides coarse estimation at the relays introducing intercarrier interferences (ICIs). OFDM system is very sensitive to the ICIs. We propose two iterative estimators: expectation conditional maximization (ECM) and space-alternating generalized expectation maximization (SAGE) to jointly estimate MTOs, MCFOs, and channel gains in the presence of ICIs. The robustness of the estimators is analyzed through mathematical formulation and simulations. The performances of the estimators are measured in terms of mean square error (MSE) and bit error rate (BER). The MSE performance is further verified with the theoretical Cramer–Rao lower bound (CRLB) derived. Simulation results show that the proposed estimators provide a significant performance gain in the DMIMO-OFDM system with MIMO configuration at the relays compared to the single-input single-output (SISO) system. [ABSTRACT FROM PUBLISHER]

In this paper, we study the performance of large-scale MIMO network where the base station has a large number of antennas and performs semi-blind channel estimation. We show that one can increase the number of antennas at the user side without increasing the overhead imposed by the channel estimation linearly with the number of user antennas. Specifically, we propose a simple data-aided channel estimation scheme which exploits the quasi-orthogonality of the channel vectors and takes advantage of the conventional pilot-aided channel estimation performed for the first antenna at each user. Two schemes are then analyzed using the extra antenna(s) at the users: data-multiplexing and interference alignment. We obtain achievable rates for the proposed uplink multi-cell MIMO system in both schemes. The rate bounds are tight and the system performance is also analyzed in terms of the outage probability to study the effect of the data length used for channel estimation scheme. [ABSTRACT FROM AUTHOR]

We investigate the heterogeneous cellular network (HetNet) where the macrocell base stations (MBSs) are equipped with very large antenna arrays. Since such a combined massive multi-input multi-output (MIMO) and HetNet system operates in the co-channel time-division duplex mode, to mitigate the pilot contamination effect to channel estimation, the number of users that can be served simultaneously is limited by the available pilot resources in the conventional designs. We propose a pilot reuse scheme for massive MIMO–HetNet to increase the user capacity. Specifically, location-aware channel estimation is employed at the MBSs to mitigate the severe pilot contamination introduced by pilot reuse, and we propose a novel pilot assignment algorithm to reduce the interference in HetNets. Simulation results demonstrate that our proposed scheme can support more users and increase both the uplink and the downlink sum-rate capacity, in comparison to the conventional scheme, particularly when the antenna number at the MBSs is sufficiently large. [ABSTRACT FROM AUTHOR]

We design a centralized and a decentralized variational Bayesian learning (C- and D-VBL) algorithms for the base station (BS) of a frequency division duplex massive multiple input multiple output (mMIMO) cellular system, wherein users send compressed information for it to estimate their downlink channels. The BS in the decentralized algorithm consists of multiple processing units (PUs), and each PU separately estimates the channels of a group of users, by employing the proposed D-VBL algorithm. To reduce channel estimation error, the PUs exploit the structured sparsity inherent in multi-user mMIMO channels by exchanging information among themselves. We investigate the proposed C-VBL and low-complexity D-VBL algorithms and show that i) they substantially outperform the state-of-the-art centralized and decentralized algorithms in terms of the normalized mean squared error and the bit error rate. This is because they beneficially exploit the inherent channel sparsity, while the existing state-of-the-art solutions fail to do so. The proposed D-VBL is also robust to PU failures, and provides a similar performance as its centralized counterpart (C-VBL), but with a much reduced complexity. [ABSTRACT FROM AUTHOR]

In this treatise, we have proposed an uplink channel estimation algorithm for nested and linear array antennas with hardware imperfections, antenna position error, and channel correlation in a multi-cell, multi-user wireless system with a one-ring scattering channel model. Hardware impairments and antenna position errors assume special importance in modern wireless system due to their severe impacts on system performance. With the increase of radio frequency (RF) in the modern wireless system and the subsequent usage of a large number of antennas for beamforming and meeting ever-increasing data rates, those errors are much relevant today. We have considered a sparse nested array (NA) and uniform linear array (ULA) for array geometry at the base station (BS). In this work, closed-form expression and bounds on the mean square error (MSE) of the linear minimum mean square error (LMMSE) channel estimate are derived. We have also analyzed the spectral efficiency (SE) of a simplified system with ULA and NA at the BS, given the model with hardware distortion and antenna position error. Two cases for (a) perfect channel side information (CSI) and (b) estimated channel are evaluated and compared in terms of their SEs, while the closed-form expression for SE with ULA at the BS considering perfect CSI is derived and verified. Numerical simulations are conducted to verify the accuracies of our derived results. [ABSTRACT FROM AUTHOR]

Artificial noise (AN) is an efficient way to enhance physical layer security of multiantenna wiretap channels with a passive eavesdropper (ED) whose channel state information is unavailable. However, the AN is known to be vulnerable to the eavesdropping attack with a large antenna array. To tackle the problem, the artificial fast fading (AFF) scheme has been developed to deliberately randomize the ED's effective channel so as to disrupt its channel estimation. Some recent progress has been made for the secrecy-rate performance of the AFF scheme in the multi-input single-output wiretap channels. However, it turns out that the performance is over-estimated. In this correspondence, we provide a comprehensive analysis on the secrecy-rate of the AFF scheme in general multi-input multi-output wiretap channels. Unfortunately, our analysis reveals a negative result that the conventional AFF is no better than the AN methods, without some pre-shared information among the legitimate parties. This is in fact in stark contrast to the previous observations. Motivated by our analysis, we propose a novel cross layer design by combining the AFF in the physical layer with the secret-keys in the upper layer crypto systems. Then, we mathematically prove that our method asymptotically nullifies the information leakage to the ED in the physical layer for any number of ED antennas even without the aid of the wiretap codes, while further enhancing the upper layer security, and thus provides an enhanced security over the layers. Finally, numerical results demonstrate the accuracy of our analysis and the efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

Given the critical dependence of broadcast channels by the accuracy of channel state information at the transmitter (CSIT), we develop a general downlink model with zero-forcing precoding, applied in realistic heterogeneous cellular systems with multiple-antenna base stations (BSs). Specifically, we take into consideration imperfect CSIT due to pilot contamination, channel aging due to users relative movement, and unavoidable residual additive transceiver hardware impairments (RATHIs). Assuming that the BSs are Poisson distributed, the main contributions focus on the derivations of the upper bound of the coverage probability and the achievable user rate for this general model. We show that both the coverage probability and the user rate are dependent on the imperfect CSIT and RATHIs. More concretely, we quantify the resultant performance loss of the network due to these effects. We depict that the uplink RATHIs have equal impact, but the downlink transmit BS distortion has a greater impact than the receive hardware impairment of the user. Thus, the transmit BS hardware should be of better quality than user's receive hardware. Furthermore, we characterise both the coverage probability and user rate in terms of the time variation of the channel. It is shown that both of them decrease with increasing user mobility, but after a specific value of the normalized Doppler shift, they increase again. Actually, the time variation, following the Jakes autocorrelation function, mirrors this effect on coverage probability and user rate. Finally, we consider space-division multiple access (SDMA), single-user beamforming (SU-BF), and baseline single-input single-output transmission. A comparison among these schemes reveals that the coverage by means of SU-BF outperforms SDMA in terms of coverage. [ABSTRACT FROM PUBLISHER]

Recent works have identified massive multiple-input multiple-output (MIMO) as a key technology for achieving substantial gains in spectral and energy efficiency. Additionally, the turn to low-cost transceivers, being prone to hardware impairments, is the most effective and attractive way for cost-efficient applications concerning massive MIMO systems. In this context, the impact of channel aging, which severely affects performance, is investigated herein by considering a generalized model. Specifically, we show that both Doppler shift due to the users' relative movement, as well as phase noise due to noisy local oscillators, contribute to channel aging. To this end, we first propose a joint model, encompassing both effects, to investigate the performance of a massive MIMO system based on the inevitable time-varying nature of realistic mobile communications. Then, we derive the deterministic equivalents for the signal-to-noise-and-interference ratios (SINRs) with maximum ratio transmission (MRT) and regularized zero-forcing (RZF) precoding. Our analysis not only demonstrates a performance comparison between MRT and RZF under these conditions but, most importantly, also reveals interesting properties regarding the effects of user mobility and phase noise. In particular, the large antenna limit behavior profoundly depends on both effects, but the burden due to user mobility is much more detrimental than phase noise even for moderate user velocities ( \approx 30 km/h), whereas the negative impact of phase noise is noteworthy at lower mobility conditions. Moreover, massive MIMO systems are favorable even in general channel aging conditions. Nevertheless, we demonstrate that the transmit power of each user to maintain a certain quality of service can be scaled down, at most, by \text{1}\sqrt{M} ( M$ is the number of base station antennas), which indicates that the joint effects of phase noise and user mobility do not degrade the power scaling law but only the achievable sum-rate. [ABSTRACT FROM AUTHOR]