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This correspondence paper studies the impact of nonidentically distributed channel estimation error on performance of a scheduled space-time block coding with mean-value power allocation in cognitive-radio multiple-input multiple-output system. Using the derived probability density function, the exact closed-form expressions of the proposed system for outage probability, ergodic capacity, and symbol-error rate (SER) with both $\rm M$ -ary quadrature amplitude modulation and phase shift keying modulation are derived. Using asymptotic analysis, this paper quantifies the diversity order for both outage probability and SER in the presence of nonidentically distributed error. From the analysis results, this paper shows that the diversity order is enhanced by the multiuser diversity as the number of user terminals increases regardless of outage probability and SER, while the spatial diversity is eliminated. [ABSTRACT FROM AUTHOR]

This paper concerns the uplink of multicell multiuser multiple-input multiple-output (MIMO) systems. To tackle the effect of pilot contamination that is generally viewed as a bottleneck in previous work, this paper presents a superimposed pilot (SP)-aided uplink channel estimation scheme and mathematically characterizes the impact that an SP has on the performance of such a very large MIMO system. It is shown that there are two types of interference components that do not vanish, even when the number of antennas $M$ grows to infinity. The first type, which is referred to as cross-contamination, is due to the correlation between the SP and data among different cells. The second type, which is referred to as self-contamination, is due to the dependence between channel estimation and estimation error. Cross-contamination is, in principle, similar to pilot contamination in a conventional pilot-based multicell MIMO system, whereas self-contamination is unique for the SP-aided scheme. Both theoretical and simulation results demonstrate that the SP-aided scheme can effectively reduce the estimation contamination by increasing the data frame size and, in turn, achieve a significant improvement over the spectral efficiency, in comparison with conventional pilot-based methods. [ABSTRACT FROM AUTHOR]

This paper focuses on precoding design for sum-rate maximization while considering the effects of residual self-interference for multiuser multiple-input–multiple-output (MU-MIMO) full-duplex (FD) systems. The problem formulation leads to a nonconvex matrix-variable optimization problem, where we develop two efficient sum-rate maximization algorithms using sequential convex programming (SCP), namely, the difference of convex functions (DC)-based and the sequential convex approximations for matrix-variable programming (SCAMP) algorithms. In addition, we derive the achievable sum rate under the effect of residual self-interference. Simulation results show that, even in cases of high self-interference and high estimation error, the SCAMP algorithm provides approximately 20%–30% sum-rate improvements over both conventional optimized half-duplex (HD) transmission and the existing state-of-the-art FD algorithm in a wide range of scenarios. Finally, the convergence results indicate that the DC-based algorithm tends to initially give the best performance; however, at convergence, the SCAMP algorithm tends to significantly outperform the other algorithms. [ABSTRACT FROM AUTHOR]

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]

In multi-user multiple-input–multiple-output (MU-MIMO) systems that employ pilot-symbol aided channel estimation, the pilot-to-data power ratio (PDPR) has a large impact on the system performance. In this paper, we consider the problem of setting the PDPR in multi-cell MU-MIMO systems in the presence of channel estimation errors, intercell interference and pilot contamination. To analyze and address this problem, we first develop a model of the multi-cell MU-MIMO system and derive a closed-form expression for the mean squared error of the uplink received data symbols. Building on this result, we then propose two decentralized PDPR-setting algorithms based on game theoretic approaches that are applicable in multi-cell systems. We find that both algorithms converge to a Nash equilibrium and provide performance improvements over systems that do not properly set the PDPR, while they maintain different levels of fairness. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) has emerged as a promising supplement to existing radio frequency-based communication systems. Recently, the use of massive light emitting diodes (LED) and photodetector (PD) arrays have been proposed to increase the capacity of the overall VLC link. At the receiver, the signals received by the PD arrays are combined to enhance the achievable data rates. However, successful combining and subsequent detection depends on accurate channel estimation. In this paper, we consider a typical massive multiple input multiple output VLC scenario with maximal ratio combining, and derive an asymptotic analytical expression for the probability density function (p.d.f) of the residual additive distortion for mobile users. Since the minimum error entropy (MEE)-based learning paradigm outperforms the traditional Bussgang approaches due to the incorporation of order statistics, we derive an MEE-based channel estimator using the analytical expression for the p.d.f of the additive distortion. Simulations are carried out for various LED array-sizes, and under various LED transmit half angles. Furthermore, using the analytically derived p.d.f, the proposed MEE-criterion-based channel estimator achieves lower bit error rate, and faster convergence, as compared to existing minimum mean square error based channel estimator. [ABSTRACT FROM AUTHOR]

In this correspondence paper, we design a massive nonorthogonal multiple access (NOMA) scheme with delay provisioning for cellular internet-of-things. In the context of massive access, the severe interuser interference decreases the quality of the received signal, such that it is a nontrivial task to provide a delay provisioning for heterogeneous wireless services. To solve this challenge, we propose a massive NOMA scheme to meet the delay requirements of a large number of users by exploiting the properties of rateless codes. Especially, we present a power allocation algorithm to minimize the power consumption while achieving delay-constrained massive access. Finally, simulation results validate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper proposes an amplify-and-forward-based massive multiple-input–multiple-output full-duplex relaying (AF-MM-FDR) protocol, where multiple source–destination pairs communicate simultaneously with a common full-duplex relay. A zero-forcing (ZF)-based relay transceiver design with semiblind gain control is presented, considering the problem of relay oscillation. The asymptotic expression of end-to-end signal-to-interference-plus-noise power (SINR) is derived under the general power scaling scheme. The scaling behaviors of echo interference (EI) and effective channel estimation error are determined. Scaling results show that the deployment of very large antenna arrays at the relay has the potential to eliminate the effect of EI due to the full-duplex operation, if the power scaling scheme is selected properly. Moreover, based on the asymptotic analysis, a low-complexity power control scheme is proposed to optimize the spectral efficiency of AF-MM-FDR. Simulation results show that the proposed power control scheme improves the spectral–energy efficiency tradeoff of AF-MM-FDR significantly. [ABSTRACT FROM AUTHOR]

In this paper, we consider time-domain vector perturbation (TDVP) in a large-system limit when channel state information (CSI) is imperfect due to pilot contamination, and we derive the system's achievable sum rate per cell. We use random matrix methods to avoid time-consuming Monte Carlo simulations. Numerical results show that, in general, linear precoding ensures a higher sum rate than TDVP in the massive multiple-input–multiple-output (MIMO) regime. [ABSTRACT FROM AUTHOR]

For large-scale antenna array multiple-input multiple-output (MIMO) systems, a typical solution often put forward for uplink detection consists in applying low-complexity linear receivers such as zero-forcing (ZF) and minimum mean-square error (MMSE) combiners. In this paper, the performance of uplink MMSE detection has been analyzed in the context of a multi-cell multiuser MIMO system. An approximate expression for the signal-to-interference-plus-noise ratio (SINR) is proposed, which is in simple form and becomes exact in the low SNR regime. This approximate SINR applies to systems where the base station (BS) has the statistical information of the out-of-cell interfering signals, and systems where the BS ignores the presence of such interfering signals. This approximate SINR is tight for arbitrary user powers, arbitrary number of antennas at the base station, and arbitrary channel correlation matrix associated with any particular user. Approximate expressions for capacity and bit-error rate/symbol-error rate have also been derived. Particularly, it can be proven that, when the MMSE receiver ignores the presence of out-of-cell interfering signals, the performance gap between ZF and MMSE vanishes in the high SNR regime. [ABSTRACT FROM AUTHOR]

This paper proposes a flexible pilot assignment method to jointly optimize the uplink and downlink data transmission in multi-cell Massive multiple input multiple output (MIMO) systems with correlated Rayleigh fading channels. By utilizing a closed-form expression of the ergodic spectral efficiency (SE) achieved with maximum ratio processing, we formulate an optimization problem for maximizing the minimum weighted sum of the uplink and downlink SEs subject to the transmit powers and pilot assignment sets. This combinatiorial optimization problem is solved by two sequential algorithms: a heuristic pilot assignment is first proposed to obtain a good pilot reuse set and the data power control is then implemented. Numerical results manifest that the proposed algorithm converges fast to a better minimum sum SE per user than the algorithms in previous works. [ABSTRACT FROM AUTHOR]

Linear decoding of space–frequency block codes (SFBCs) based on the Alamouti structure with orthogonal frequency-division multiplexing (OFDM) requires the channel to be constant across two consecutive tones. However, time-dispersive multipath fading channels exhibit frequency-selective behavior wherein the channel across two tones will vary. This paper provides analytical tools for evaluating the performance of SFBCs with OFDM in frequency-selective channels. The analysis uses the average signal-to-interference-plus-noise ratio (SINR) as a sufficient statistic to describe the performance of SFBCs in frequency-selective channels. A unified formula is derived to characterize the channel correlation between two consecutive tones for various frequency-selective channels. A closed-form solution of the average SINR is obtained, which takes into account imperfect channel estimation and frequency selectivity. An interpolation method of the channel estimate is proposed, which is shown to improve the bit-error-rate performance by 3 dB at a high SNR. The accuracy of the theoretical analyses is verified by numerical simulations under multipath channels such as the International Telecommunications Union (ITU) pedestrian and vehicular models. [ABSTRACT FROM PUBLISHER]

This paper is concerned with the sum-rate maximization problem in multiple-input multiple-output interference channels. We design the transmit covariance matrix, associated with each transmitter to maximize the sum-rate of the network when the number of data symbols is unknown. The design problem is nonconvex and then hard to be solved. We devise a semidistributed design methodology according to majorization–minimization technique to deal with the optimization problem. This leads us to a convex quadratically constrained quadratic program at each iteration with a semiclosed form solution. The proposed method is computationally efficient and converges to stationary points of the problem. The fact that the method is based on a distributed processing framework along with relatively low computational burden ( $\mathcal{O}(\max \lbrace M,N\rbrace ^{2.3})$ per iteration with $M$ and $N$ being the number of antennas at the transmitter and receiver, respectively) for the user terminals can make it a potential candidate for practical implementations. Finally, we extend the proposed method for the case with channel estimation errors. Simulation results verify the efficiency of the proposed method, and in a typical scenario we have around 60 times lower run-time when compared to the counterparts of the method. [ABSTRACT FROM AUTHOR]

This paper considers a novel virtual pilot-assisted channel estimation algorithm for multiple input multiple output single carrier frequency domain equalization (MIMO-SCFDE) systems over fast time-varying multipath channels. Given that the fast time-varying channels can no longer support the assumption that the channel frequency-domain response remains invariant for the duration of one SC-FDE symbol, most of the channel estimation methods cannot be directly applied to MIMO-SCFDE systems. We put forward an iterative interfrequency interference cancellation method for the time-varying multipath channels over one SC-FDE symbol. The proposed method utilizes the virtual pilot-assisted channel estimation and partial minimum-mean-square-error equalization to improve the accuracy of the estimation. Simulation results validate the improved performance of the proposed method for MIMO-SCFDE systems over fast time-varying multipath channels. [ABSTRACT FROM AUTHOR]

This paper investigates an outage-constrained secrecy rate maximization (OC-SRM) problem based on the statistical channel uncertainty assumption in an underlay multiple-input multiple-output (MIMO) cognitive radio network, where the secondary transmitter provides simultaneous wireless information and power transfer to receivers. Our objective is to design the transmit covariance matrix and artificial noise aided covariance matrix through maximizing the secrecy rate of the secondary user while satisfying the given outage probability requirements. The designed problem is nonconvex and challenging. We employ the existing theory to reformulate the original problem into two equivalent subproblems by introducing auxiliary variables in order to overcome the difficulty arising from the Shannon capacity expression. The Bernstein-type inequality approach is resorted to conservatively approximate the probabilistic constraints. The merit of the transformation and conversion is that the tractable solutions of the original OC-SRM problem can be easily obtained through solving two convex conic subproblems alternately. Furthermore, we extend the proposed algorithm to solve full uncertainty model design. Numerical results demonstrate the efficacy of the proposed designs. [ABSTRACT FROM AUTHOR]

Combined with N-continuous (NC) precoding, the spatial modulation (SM) orthogonal frequency division multiplexing (OFDM) system offers considerable sidelobe suppression for the downlink transmission, at the cost of additional interference to the transmit signal. Therefore, this paper focuses on investigating the impact of the NC precoder on the bit error rate (BER) performance of the SM-OFDM system. The BER performance is analyzed over the frequency-selective Rayleigh fading channel under two distinct scenarios, i.e., perfect channel estimation and interference suppression based minimum mean square error (MMSE) channel estimation. First, we propose an approximate system model for the NC precoded SM-OFDM system along with an analysis on the introduced interference, and then derive the average BER performance of the system with perfect channel estimation. Based on the above proposed approximate system model, we further analyze the interference based upon MMSE channel estimation, and investigate the characteristics of channel estimation errors. Furthermore, we derive the average BER performance of the NC precoded SM-OFDM system with imperfect channel estimation. The numerical results show that the analytical BER closely matches its simulated counterpart under different system configurations, and demonstrate that the proposed approximate system model is in good agreement with the precise one. [ABSTRACT FROM PUBLISHER]

This paper investigates pilot design and allocation in multi-cell massive multiple-input multiple-output systems with two-tier receiving. As the length of pilot is limited, the pilots cannot be orthogonal and cause interference. The sum rate as well as the signal-to-interference-plus-noise ratio (SINR) of the system are firstly analyzed. The sum rate upper bound and the asymptotic SINR are derived. The analysis shows that the pilot correlation and the spatial correlation jointly affect the sum rate. Based on this observation, the discrete Fourier transform vectors are employed in designing pilots with various correlation values. Then, with the channel correlation information and the designed pilots, the pilots are allocated to the cells in a greedy way with the object of maximizing the sum rate upper bound. Moreover, the sum rate analysis, the pilot design, and the pilot allocation are extended to the scenario with grouped correlations. Simulation results show that the proposed pilot design and allocation performs better than other pilots and the derived upper bound is effective. [ABSTRACT FROM AUTHOR]

Different from the existing works, in this paper we investigate the pilot allocation in multi-cell massive multiple-input multiple-output (MIMO) systems, aiming to maximize the spectral efficiency (SE) subject to the constraint that the number of user equipments (UEs) satisfying the quality of service (QoS) is maximized. Since the considered bilevel optimization problem that is tough to handle, we resort to the greedy algorithms with low computational complexity. We propose a QoS constrained (QC) pilot allocation scheme, which sequentially allocates the pilot sequence having large interference power to the UE with small signal power so that the number of UEs satisfying QoS can be maximized and then the SE can also be maximized. Simulation results show that the propose QC scheme outperforms the conventional scheme and smart pilot allocation (SPA) scheme. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the spectral efficiency of multicell massive multiple-input–multiple-output (MIMO) systems with downlink training and a new pilot contamination precoding (PCP) scheme. First, we analyze the spectral efficiency of the beamforming training (BT) scheme with maximum-ratio transmission (MRT) precoding. Then, we derive an approximate closed-form expression of the spectral efficiency to find the optimal lengths of uplink and downlink pilots. Simulation results show that the achieved spectral efficiency can be improved due to channel estimation at the user side, but in comparison with a single-cell scenario, the spectral efficiency per cell in multicell scenario degrades because of pilot contamination. We focus on the practical case where the number of base station (BS) antennas is large but still finite and propose the BT and PCP (BT-PCP) transmission scheme to mitigate the pilot contamination with limited cooperation between BSs. We confirm the effectiveness of the proposed BT-PCP scheme with simulation, and we show that the proposed BT-PCP scheme achieves higher spectral efficiency than the conventional PCP method and that the performance gap from the perfect channel state information (CSI) scenario without pilot contamination is small. [ABSTRACT FROM AUTHOR]

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]

For massive multiuser multiple input multiple output (MIMO) (MU-MIMO) systems, pilot contamination (PC) and data interference (DI) are two main factors that affect the accuracy of the superimposed pilot (SP) based channel estimation, provided that the channel coherence time is less than the total number of users. In this paper, to tackle the effect of the PC, we propose a block-diagonal Grassmannian line packing (GLP) approach, in which the specific sequences for different cells are first designed based on the GLP, and then are block-diagonally extended to form the SP matrices for the users in different cells. To also alleviate the effect of DI on the channel estimation, with the designed SP matrices, an iterative channel estimation (ICE) method based on Tikhonov regularization is presented. The impact that the proposed ICE method has on the signal-to-interference-plus-noise ratio with matched filtering receiver is theoretically analyzed. Moreover, the optimal power allocation factor to the SP by maximizing the spectral efficiency (SE) of the target cell is also derived. Numerical results show that the proposed ICE method with the designed SP matrices effectively mitigates the effects of the PC and DI, and hence, improves the accuracy of channel estimation and further the SE of the massive MU-MIMO systems. [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]

Two-stage beamforming is a transmit strategy that uses two types of beamformers to reduce the feedback overhead of frequency-division-duplexing massive multiple-input multiple-output systems that are spatially correlated. In this paper, we present large system analysis of two-stage beamforming when a transmitter has limited channel information from feedback and when regularized-zero-forcing (RZF) is used as a second-stage beamformer. We consider two random-vector-quantization-based feedback schemes that can be respectively applied when users have perfect channel information or perfect effective channel information. For each feedback method, we analyze both expected signal-to-interference-plus-noise ratio (SINR) and expected rate loss and then characterize their bounds as a function of the number of feedback bits. From the characterization, we reveal that the sum rate of two-stage beamforming is very sensitive to the regularization parameter of RZF, especially when the number of feedback bits is limited. Motivated by this, we derive the optimal regularization parameter that maximizes the SINR of two-stage beamforming with limited feedback. Using simulations, we verify the tightness of the characterized bounds and quantify how the use of the optimal regularization parameter improves the sum rate of two-stage beamforming. [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 propose an optimal channel training method in the sense of linear minimum mean square error for multiple-input multiple-output amplify-and-forward relay systems in the presence of interference. By using a relay processing matrix, the received interference is cancelled or mitigated. To make the problem tractable, we first derive the optimal structure of the training signal and the relay processing matrix. Then, we propose an optimal channel training method. In order to reduce the complexity, we also propose an asymptotically optimal channel training method. Simulation results demonstrate that the two proposed methods outperform the conventional training signal design methods in terms of both the mean square error and in the bit error rate. [ABSTRACT FROM PUBLISHER]

Channel estimation is critical to the performance of a multiple-input multiple-output and orthogonal frequency-division-multiplexing (MIMO-OFDM) communication system. Current MIMO-OFDM channel estimation techniques suffer from either high complexity or poor performance. In fact, this issue has become one of the bottlenecks of a practical MIMO-OFDM system. This paper solves the problem by introducing a new technique that has minimum complexity and yet provides superior channel tracking performance close to a minimum mean square error (MMSE) estimate over a wide range of channel selectivity and noise variance. The performance was evaluated via numerical simulations. [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]

In this paper, we propose an iterative structure for channel estimation and data detection for multiple-input–multiple-output orthogonal frequency-division multiplexing systems (MIMO-OFDM) with insufficient cyclic prefix (CP) and a limited number of pilot subcarriers. Insufficient CP leads to increased intersymbol interference (ISI) and intercarrier interference (ICI). The interference corrupts pilot subcarriers used for channel estimation and affects the detection process. We propose a multistep channel estimation process, which is assisted by a small number of pilot subcarriers. First, the channel covariance matrix and the number of channel paths are acquired from the channel least square estimates at the pilot subcarriers. We then formulate a maximum likelihood process to approximate the time-domain channel. For data detection, a high-performance bidirectional M-algorithm (BDMA) is proposed for trellis-based equalization. Simulation results show that the channel estimate mean square error converges to the Cramer–Rao bound (CRB) after a few iterations. In addition, the achieved bit error rate (BER) can reach that of the sufficient CP case, even when the delay spread is much longer than the CP.1 [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]

The users at cell edge of a massive multiple-input–multiple-output (MIMO) system suffer from severe pilot contamination (PC), which leads to poor quality of service (QoS). To enhance the QoS for these edge users, soft pilot reuse (SPR) combined with multicell block diagonalization (MBD) precoding is proposed. Specifically, the users are divided into two groups according to their large-scale fading coefficients, which are referred to as the center users, who only suffer from modest PC, and the edge users, who suffer from severe PC. Based on this distinction, the SPR scheme is proposed for improving the QoS for the edge users, whereby a cell-center pilot group is reused for all cell-center users in all cells, whereas a cell-edge pilot group is applied for the edge users in the adjacent cells. By extending the classical block diagonalization precoding to a multicell scenario, the MBD precoding scheme projects the downlink transmit signal onto the null space of the subspace spanned by the intercell channels of the edge users in adjacent cells. Thus, the intercell interference contaminating the edge users' signals in the adjacent cells can be efficiently mitigated, and hence, the QoS of these edge users can be further enhanced. Our theoretical analysis and simulation results demonstrate that both the uplink and downlink rates of the edge users are significantly improved, albeit at the cost of the slightly decreased rate of center users. [ABSTRACT FROM AUTHOR]

We consider the detection of multiple cochannel single-carrier spatially multiplexed data streams. To this end, we propose a hybrid time–frequency-domain decision feedback equalizer, which performs parallel detection of the data streams. A practical parameter estimation algorithm for these receivers is developed, which estimates the MIMO channel in parallel as a set of effective channel vectors. To avoid interference cancellation, we develop a two-stage frequency-domain (FD) forward section that implements linear cochannel interference (CCI) suppression in cascade with equalization utilizing estimated channel-state information. The resulting receiver architecture outperforms interference-cancellation-based equalizers in the presence of channel estimation errors. Furthermore, all transmitted data streams achieve equal diversity gains. [ABSTRACT FROM PUBLISHER]

In this work, we investigate the power allocation needed to maximize the energy efficiency (EE) of a massive multiple-input-multiple-output (MIMO) system. We first derive a closed-form expression for the user rate with the presence of pilot contamination caused by inter-cell interference during the channel estimation phase. From the definition of system EE, we propose a maximization problem with two constraints: limited power for pilot and data signals and a minimum value for every user rate. The proposed maximization problem is a fractional programming problem and is very hard to solve directly. Therefore, we propose the first iterative algorithm to transform the original problem into subtractive form. Moreover, we propose the second iterative algorithm to solve the subtractive form maximization problem by approximating it as a convex problem. The convergence and feasibility of the two proposed algorithms are also discussed. Finally, the effectiveness of our scheme is shown by simulation results. [ABSTRACT FROM AUTHOR]

In massive multiple-input multiple-output (MIMO) crowded networks, the random access (RA) performance of strongest-user collision resolution (SUCRe) protocol can be improved by replacing the hard decision retransmission rule by a soft decision one, so that each user equipment (UE) decides to retransmit or not its pilot sequence with a suitable probability. We obtain this probability for each UE according to the probability of this UE being the strongest contender, while also proposing an analytical approximated probability expression for this event. Hence, the $k$ th UE is able to calculate the probability of itself being the strongest contender in a pilot collision, choosing to retransmit or not its RA pilot in the next step of the protocol according to this probability, without requiring any excessive complexity or additional overheads. Our numerical results demonstrate significant improvements in comparison to the original SUCRe protocol, while maintaining its favorable feature of being a decentralized and uncoordinated approach. [ABSTRACT FROM AUTHOR]

The limited fronthaul capacity imposes a challenge on the uplink of a centralized radio access network (C-RAN). We propose to boost the fronthaul capacity of a massive multiple-input multiple-output (MIMO)-aided C-RAN by globally optimizing the power sharing between channel estimation and data transmission both for the user devices (UDs) and the remote radio units (RRUs). Intuitively, allocating more power to the channel estimation will result in more accurate channel estimates, which increases the achievable throughput. However, increasing the power allocated to the pilot training will reduce the power assigned to data transmission, which reduces the achievable throughput. In order to optimize the powers allocated to the pilot training and to the data transmission of both the UDs and the RRUs, we assign an individual power sharing factor to each of them and derive an asymptotic closed-form expression of the signal-to-interference-plus-noise ratio for the massive MIMO-aided C-RAN consisting of both the UD-to-RRU links and the RRU-to-baseband unit (BBU) links. We then exploit the C-RAN architecture's central computing and control capability for jointly optimizing the UDs’ power sharing factors and the RRUs’ power sharing factors aiming at maximizing the fronthaul capacity. Our simulation results show that the fronthaul capacity is significantly boosted by the proposed global optimization of the power allocation between channel estimation and data transmission both for the UDs and for their host RRUs. As a specific example of 32 receive antennas (RAs) deployed by the RRU and 128 RAs deployed by the BBU, the sum rate of 10 UDs achieved with the optimal power sharing factors improves by 33% compared with the one attained without optimizing power sharing factors. [ABSTRACT FROM AUTHOR]

We propose a location-aware pilot allocation algorithm for a massive multiple-input multiple-output (MIMO) network with high-mobility users, where the wireless channels are subject to Rician fading. Pilot allocation in massive MIMO is a hard combinatorial problem and depends on the locations of users. As such, it is highly complex to achieve the optimal pilot allocation in real-time for a network with high-mobility users. Against this background, we propose a low-complexity pilot allocation algorithm, which exploits the behavior of line-of-sight (LOS) interference among the users and allocate the same pilot sequence to the users with small LOS interference. Our examination demonstrates that our proposed algorithm significantly outperforms the existing algorithms, even with localization errors. Specifically, for the system considered in this work, our proposed algorithm provides up to 37.26% improvement in sum spectral efficiency (SE) and improves the sum SE of the worst interference-affected users by up to 2.57 bits/sec/Hz, as compared to the existing algorithms. [ABSTRACT FROM AUTHOR]

We consider a multiple-input–multiple-output (MIMO) relaying broadcast channel in downlink cellular networks, where the base station and the relay stations are both equipped with multiple antennas, and each user terminal has only a single antenna. In practical scenarios, channel estimation is imperfect at the receivers. Aiming to maximize the signal-to-interference noise ratio (SINR), at each user, we develop two robust linear beamforming schemes for the single-relay case and the multirelay case, respectively. The two proposed schemes are based on singular value decomposition (SVD), minimum mean square error (MMSE), and regularized zero forcing (RZF). Simulation results show that the proposed scheme outperforms the conventional schemes with imperfect channel estimation. [ABSTRACT FROM PUBLISHER]

Intercell cochannel interference (CCI) mitigation is investigated in the context of cellular systems relying on dense frequency reuse (FR). A distributed base-station (BS)-cooperation-aided soft reception scheme using the probabilistic data association (PDA) algorithm and soft combining (SC) is proposed for the uplink of multiuser multicell MIMO systems. The realistic 19-cell hexagonal cellular model relying on unity FR is considered, where both the BSs and the mobile stations (MSs) are equipped with multiple antennas. Local-cooperation-based message passing is used, instead of a global message passing chain for the sake of reducing the backhaul traffic. The PDA algorithm is employed as a low-complexity solution for producing soft information, which facilitates the employment of SC at the individual BSs to generate the final soft decision metric. Our simulations and analysis demonstrate that, despite its low additional complexity and backhaul traffic, the proposed distributed PDA-aided SC (DPDA-SC) reception scheme significantly outperforms the conventional noncooperative benchmarkers. Furthermore, since only the index of the possible discrete value of the quantized converged soft information has to be exchanged for SC in practice, the proposed DPDA-SC scheme is relatively robust to the quantization errors of the soft information exchanged. As a beneficial result, the backhaul traffic is dramatically reduced at negligible performance degradation. [ABSTRACT FROM PUBLISHER]