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As the number of antennas increases, the massive multiple-input multiple-output (MIMO) system can precisely point to user equipments (UEs) with narrow beams. Accurate and timely channel state information (CSI) feedback is crucial to keep UEs in service. Mobile UEs, however, may suffer from the narrow beam nature of the massive MIMO system since UEs can move out of the beam coverage. When intelligent reflecting surface (IRS) is applied to the massive MIMO system, the adjustment of the IRS cannot be frequent as the IRS is controlled remotely by the base station (BS). Limiting the number of CSI feedback and the number of both BS and IRS adjustments significantly reduces the overhead of transmission and computation to the system. In this paper, we consider the UEs’ mobility adaptation problem in an IRS assisted multiuser massive MIMO downlink system with infrequent CSI feedback. We propose a beam control method that adapts to UEs’ mobility. The problem is constructed as a sum rate problem where both the BS and IRS are taken into account to jointly optimize the beamforming matrices. Simulation results show that our proposed algorithm can converge quickly and provide satisfactory performance for mobile UEs. At the same time, our proposed algorithm reduces the frequency of updating the beamforming matrices effectively both at the BS and at the IRS. [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]

This paper considers multicell scheduling for coordinated multiple-input multiple-output cellular networks. In a multicell scenario, intercell interference, which is the major challenge degrading system performance, can be suppressed via multicell coordination. However, when the number of users is larger than that can be served, user/multimode selection is necessary, and can significantly enhance the performance in such interference-limited environment. Nevertheless, user selection in a multicell scenario incurs high computational complexity and overhead signalling. To this end, in this paper, low complexity greedy algorithms are proposed for user selection. The algorithms are based on the concept of angle between subspaces and intersection of null spaces, and work in partially distributed fashion with limited information exchange. By these algorithms, channel feedback can be greatly reduced with reasonable computational complexity. In addition, multimode scheduling schemes are proposed for this multicell set up, where the spatial streams are adaptively selected. The proposed algorithms are analysed and compared with the optimal solution obtained by exhaustive search. Simulation results show that the algorithms achieve most of the throughput achievable by the optimal solution. [ABSTRACT FROM AUTHOR]

Multi-numerology transmission is a promising multiple access scheme for flexible communication systems, which can simultaneously support users with different service requirements. To this end, both inter- and intra-numerology interference (inter-NI and intra-NI) should be suppressed, which is not straightforward. This paper proposes a novel zero-forcing (ZF) precoding design, which perfectly eliminates all the interference, for massive multiple-input multiple-output (MIMO) systems with multi-numerology. First of all, we express the signal-to-interference-plus-noise ratio (SINR) of the multi-numerology system with spectrum sharing. From the SINR representation, we identify the channels that precoders must nullify to suppress inter-NI. After that, we propose a ZF precoder suppressing both inter-NI and intra-NI perfectly. The lower bound of ergodic achievable rate with perfect channel state information at the transmitter (CSIT) is analyzed. Based on the lower bound of ergodic achievable rate, we present the feasible rate region. Also, we propose two power allocation schemes: user fairness and the ergodic sum rate maximization. The simulation results demonstrate the advantage of the proposed precoding design and verify our analysis results. [ABSTRACT FROM AUTHOR]

This paper considers limited feedback for a two-cell interfering multiple-input–multiple-output multiple-access channel (MIMO-MAC). We propose a QR decomposition-based interference alignment (QRD-IA) scheme for efficient limited feedback and investigate the conditions for the antenna configuration. We characterize the interference leakage caused by quantization error as a function of the number of feedback bits. To minimize the interference leakage, we further propose a quantized-precoder-based IA (QP-IA) scheme by modifying the proposed QRD-IA scheme. By characterizing the interference leakage of the QP-IA scheme, we investigate the number of feedback bits to maintain the degrees of freedom (DOFs) in the two-cell interfering MIMO-MAC and a feedback bit allocation algorithm to improve the sum rate. From simulation results, we demonstrate that our proposed schemes can provide better sum-rate performance than the existing scheme using the same number of feedback bits, and our feedback bit allocation algorithm provides a higher sum rate compared with equal feedback bit allocation. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the problem of spectrum leasing in cognitive radio (CR) networks, while incorporating two advanced physical-layer technologies, i.e., multiple-input multiple-output (MIMO) and distributed interference alignment. We present a cooperative spectrum leasing scheme for primary and secondary users to balance the tension between data transmission and revenue collection/payment. A Stackelberg game is formulated, where the primary user is the leader, and secondary users are followers. With backward induction, we derive the optimal strategies for primary and secondary users that can achieve the unique Stackelberg equilibrium, where no player can gain by a unilaterally changing strategy. We find that spectrum leasing is always beneficial to enhancing the utilities of primary and secondary users. The proposed scheme outperforms a no-spectrum-leasing scheme and a cooperative scheme presented in the literature with considerable gains, which demonstrate the benefits of spectrum leasing and distributed interference alignment and validates the efficacy of the proposed scheme. [ABSTRACT FROM PUBLISHER]

This correspondence paper addresses linear precoding design for sum rate maximization in low-latency orthogonal frequency-division multiplexing systems. In order to mitigate the overhead of cyclic prefix (CP) originating from shortened symbol duration for low-latency communications, 5G wireless systems need to adopt short CP lengths. As channel delay spread must be less than the CP length, we first derive the effective root-mean-square (RMS) delay spread and the achievable rate using the zero-forcing assumption. We construct a sum rate optimization problem for each user subject to delay spread constraints and then convert the problem into a solvable convex problem along with a semi-definite relaxation technique. The precoding matrix is finally obtained by solving optimization problems for all users. Numerical results reveal that the proposed scheme attains superior performance to the conventional sum rate optimization, as well as small RMS delay spread. [ABSTRACT FROM AUTHOR]

This paper studies the degrees of freedom (DoF) of two-way $2\times 2\times 2$ MIMO interference networks, a class of two-way four-unicast networks. We first provide upper and lower bounds on the sum DoF of general two-way $2\times 2\times 2$ MIMO interference networks with any number of antennas in each node. We then investigate the special case where all user nodes have $M$ antennas and relay nodes have $N$ antennas, and provide the simplified bounds on the sum DoF. We show that our proposed achievable rate for this special case is higher than the achievable rates recently proposed in. Moreover, for this special case, we obtain the exact DoF $=4M$ when $N \geq 2M$ , and DoF $=4N$ when $M \leq 2N$. [ABSTRACT FROM AUTHOR]

This paper considers a two-cell uplink cochannel multiple-input–multiple-output (MIMO) network with users sequentially arriving at the network. We study the problem of sequential base-station (BS) selection for the users, with the selection criterion based on the degrees of freedom (DoFs) available for the new arriving user. We find that different sequential BS selections affect individual and network performance in terms of the individual and network sum DoF, as well as the number of admissible users in the network. We propose a method to build the tree structure for sequential BS selection, which carries trellis information for individual and system-wide selections. The properties of the tree are analytically studied. It turns out that by adopting an interference coordination strategy based on the concept of interference alignment (IA), better individual and network performance can be achieved. Simulation compares the proposed DoF-based BS selection and traditional BS selection schemes and highlights the advantages of the proposed scheme. [ABSTRACT FROM PUBLISHER]

Achieving a good tradeoff between spectral efficiency (SE) and energy efficiency (EE) is important for the emerging wireless communication systems. Motivated by this, we study multiuser downlink beamforming in massive multiple-input multiple-output systems for maximizing a new metric of resource efficiency (RE), which is defined as a weighted combination of EE and SE. The new measure has more flexibility in striking the balance between SE and EE, but brings enormous difficulties in solving the resulting problem. To this end, we first investigate an uplink–downlink duality for the RE maximization. The conventional uplink–downlink duality only applies in the SE or the capacity region, and has yet not been explicitly established for the EE or the RE. In this paper, we prove with rigorous derivation that the duality has a more general form, which can be directly used to tackle the EE or RE beamforming optimization problem. Based on the duality, we then develop an optimization algorithm to realize spectral and energy efficient multiuser beamforming with either instantaneous or statistical channel state information (CSI). Numerical results finally verify that the design based on statistical CSI is able to asymptotically achieve the performance obtained with instantaneous CSI, but with much lower complexity. [ABSTRACT FROM AUTHOR]

A multicell massive multiple-input multiple-output (MIMO) system, which utilizes a large number of base-station antennas to simultaneously serve a set of users, suffers from pilot contamination (PC) due to unavoidable reuse of pilots in adjacent cells. In this paper, a weighted-graph-coloring-based pilot decontamination (WGC-PD) scheme is proposed to mitigate PC for multicell massive MIMO systems. Specifically, based on limited cooperation among cells, an edge-weighted interference graph (EWIG) is first constructed to depict the potential PC relationship among users, whereby two users in different cells are connected by a weighted edge, indicating the strength of potential PC when they reuse the same pilot. Then, inspired by classical graph coloring algorithms, we develop the WGC-PD scheme by denoting each color as a pilot and each vertex as a user in the EWIG, which is able to mitigate PC by assigning different pilots to connected users with a large weight in a greedy way with insufficient pilot resource. Compared with exhaustive search among numerous pilot assignment solutions, the proposed WGC-PD scheme is able to mitigate PC with significantly reduced complexity, which is verified by numerical results. [ABSTRACT FROM PUBLISHER]

In this paper, resilient transmission in a multicell multiple-input multiple-output (MIMO) interference wiretap channel model is studied. Each base station (BS) transmits confidential messages to its intended legitimate user with multiple antennas in the presence of eavesdroppers that can overhear the transmission. We study the problem of finding the optimal transmit covariance matrices at the BSs to maximize the secrecy sum rate, which is typically nonconvex and intractable to obtain a globally optimal solution. A distributed iterative optimization algorithm based on a novel decomposition framework across all users is proposed. The decomposition framework preserves the convexity of the objective function and linearizes the nonconvex part. At each iteration, the BSs simultaneously solve a sequence of problems that are decoupled convex approximations of the original secrecy sum-rate function. Moreover, the complexity of the algorithm is analyzed. Numerical results are presented to validate the effectiveness of the proposed distributed algorithm. [ABSTRACT FROM PUBLISHER]

Millimeter wave (mmWave) has been widely considered as a promising technology in the next generation wireless communication systems. Various beam-based directional transmission techniques have been proposed to compensate high pathloss caused by mmWave properties. However, mobility effect of users potentially causes severe inter-beam interferences, which has not been fully-investigated in existing studies. In this paper, we have analyzed different types of mobility-aware beam interference models. Additionally, the theoretical SINR is derived based on channel statistics and the trajectories of users. We propose a mobility-aware subband and beam resource allocation (MSBA) scheme for the mmWave subband-beam massive multi-input multi-output (SB-MMIMO) systems. The proposed MSBA benefits from reduced computation complexity for maximizing system throughput constrained by quality-of-service (QoS) demands of users. The first phase of MSBA scheme is responsible for resource block assignment; while the second phase allocates beamwidth and beam directions according to the analytical derivations. Numerical results show that the proposed MSBA scheme can effectively achieve the highest system throughput and the lowest complexity compared to existing schemes in open literatures. [ABSTRACT FROM AUTHOR]

Multiuser orthogonal frequency-division multiplexing (OFDM) and multiple-output multiple-output (MIMO) have been widely adopted to enhance the system throughput and combat the detrimental effects of wireless channels. Interference alignment has been proposed to exploit interference to enable concurrent transmissions of multiple signals. In this paper, we investigate how to combine these techniques to further enhance the system throughput. We first reveal the unique characteristics and challenges brought about by using interference alignment in diagonal channels. We then derive a performance bound for the multiuser (MIMO) OFDM interference alignment system under practical constraints and show how to achieve this bound with a decomposition approach. The superior performance of the proposed scheme is validated with simulations. [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 develop beamforming (BF) schemes to minimize the total transmitted power of both uplink (UL) and downlink (DL) in two-tier network with in-band wireless backhaul (WB) while the target rates of user equipment (UE) are satisfied under the backhaul constraints. We propose a centralized BF scheme with an alternate update algorithm optimizing the BF matrices and power allocation vectors. Then the UL-DL feasible target rate region of the proposed scheme is analyzed, which can be enlarged in both UL and DL by increasing the number of antennas of small cell base stations (SBSs). Simulation results show that the proposed in-band WB system for two-tier network can save the power consumption by 33.5% and 82.1% compared with the out-of-band WB system and conventional one-tier network, respectively, at the UE target rates of 80 Mb/s in DL and 40 Mb/s in UL. In addition, we propose a distributed BF scheme to locally optimize the variables at each SBS, which can achieve above 90% of the feasible target rate region of the centralized scheme without the instantaneous information exchange. [ABSTRACT FROM AUTHOR]

In this paper, a novel unified transmission framework in the context of both decode-and-forward (DF) and amplify-and-forward (AF) protocols was proposed for a two-hop multiple-input–multiple-output (MIMO) alternate half-duplex (HD) relaying system with $M$ antennas for each node, which can achieve the maximum M$ degrees of freedom (DoFs) of the system, compared with the existing interference alignment (IA) schemes that can only get \3M/\4 DoF. Furthermore, the proposed schemes require only two relays against three relays invoked in the existing IA schemes. Moreover, the proposed schemes are valid for the cases where the number of antennas $M$ can be either even or odd, whereas the existing IA schemes can only apply for an even number of antennas $M$. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new three-user network information flow model, referred to as the triangular multiple-input–multiple-output (MIMO) relay (TMR) channel, which consists of three users and three relays equipped with nU and nR antennas, respectively. Each user sends two independent messages to the other two users via the adjacent relays in two time slots, which are referred to as the multiple-access and broadcast stages. We derive a novel simultaneous signal and interference alignment for the proposed TMR channel in a scenario where there are fewer antennas at each relay than at each user (nR < nU ) . An optimized pseudo-inverse scheme based on an efficient gradient projection algorithm is proposed to solve the simultaneous alignment problem. By deriving a gradient over weighted sum-rate maximization and applying a gradient descent method, the optimal beamforming vectors are obtained to maximize the effective signal-to-noise ratios. Furthermore, to obtain rapid convergence speed and reduce computational complexity, we introduce a quasi-Newton method, which is referred to as the Broyden–Fletcher–Goldfarb–Shanno algorithm, by approximating the Hessian matrix of a pure Newton method. The convergence of the proposed gradient algorithm is guaranteed by proposing a line search algorithm. Finally, a performance evaluation shows that the proposed scheme offers a higher sum rate, produces a better outage probability, and achieves a higher multiplexing gain than the existing schemes. [ABSTRACT FROM PUBLISHER]

Recently, a new paradigm for cognitive radio networks has been advocated, where primary users (PUs) recruit secondary users (SUs) to cooperatively relay the primary traffic and in return grant the SUs the right to access the channel. However, all existing studies on such cooperative cognitive radio networks (CCRNs) operate in the temporal domain only, which limits the performance of both PUs and SUs. On the other hand, multiple-input–multiple-output (MIMO) enables transmission of multiple independent data streams in the spatial domain to improve capacity. Taking advantage of the MIMO technique in CCRNs is an unexplored area that we investigate in this paper. We propose a novel MIMO-CCRN framework, which enables the SUs to utilize MIMO techniques to cooperatively relay the traffic for the PUs, while concurrently accessing the same channel to transmit their own traffic. Specifically, we consider two typical network scenarios. For the case of a general PU link and multiple SUs, we provide theoretical analysis for the link rates and then formulate an optimization model based on a Stackelberg game to maximize the utilities of PUs and SUs. In addition, we extend our analysis to a practical cellular network with multiple MIMO-empowered femtocells, and provide an algorithm to find a stable matching of the PUs and SUs. Evaluation results show that high utility gains are achieved by both PUs and SUs by leveraging MIMO spatial cooperation in our proposed framework. [ABSTRACT FROM PUBLISHER]

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]

This paper presents a generalized closed-form beamforming technique that can achieve the maximum degrees of freedom in compounded multiple-input multiple-output (MIMO) broadcast channels with mixed classes of multiple-antenna users. The contribution is first described within the context of a three-cell network and later extended to the general multicell scenario where we also show how to determine the conditions required to align the interference in a subspace that is orthogonal to the one reserved for the desired signals. This is then followed by an analysis of the impact of antenna correlation for different channel state information acquisition models. The proposed scheme is examined under both conventional and large-scale MIMO systems. It will be shown that the proposed technique enables networks with any combination of user classes to achieve superior performance even under significant antenna correlation, particularly in the case of the large-scale MIMO systems. [ABSTRACT FROM AUTHOR]

Full-duplex (FD) multiple-input multiple-output relaying has been considered an effective scheme to increase the spectral efficiency for wireless communications. As known, the main problem for the FD system is the cancellation of loop interference (LI). In this paper, we propose using the joint source/relay precoding to reduce the influence of LI. Therein, linear precoders are used at the source and relay, while the minimum mean-squared-error receiver is adopted at the destination. The joint precoder design is complicated when spatial multiplexing is exploited for signal transmission. To solve the problem, we propose an iterative method in which the original problem is split into two subproblems. With some matrix properties, we then show that each subproblem can be formulated as a convex optimization. Finally, a closed-form solution can be obtained with the Karush–Kuhn–Tucker conditions. Using a mean-squared-error upper bound, we also propose a low-complexity method to reduce the computational complexity. The proposed precoders have closed-form expressions, which is a great advantage in real-world implementation. Simulation results show that the proposed methods significantly outperform existing ones. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of a dual-hop multiple-input–multiple-output (MIMO) amplify-and-forward (AF) relay network, where the source, relay, and destination are all equipped with multiple antennas. By using maximum ratio transmission (MRT) at the transmitter and maximum ratio combining (MRC) at the receiver, we first obtain the output signal-to-interference-plus-noise ratio (SINR) of the dual-hop AF relay system, considering multiple cochannel interferences (CCIs), as well as noise at the relay. Then, we derive an exact closed-form expression for the outage probability (OP), and the asymptotic result of OP at high SNR, which can be used to calculate the array gain and diversity order. Finally, computer simulations are conducted to validate the performance analysis. Our new analytical expressions not only provide a fast and efficient method to evaluate the system performance but enable us to gain valuable insights into the effects of key parameters on the MIMO AF relaying network performance that benefits from implementing multiple antennas at each of the three nodes as well. [ABSTRACT FROM PUBLISHER]

Multiple-input multiple-output (MIMO) relays can improve cell coverage and data throughput for wireless networks. The key challenge for the success of MIMO relay networks is effectively managing the intersymbol interference (ISI) and multiantenna interference (MAI) in multipath channels. In this paper, equalize-and-forward (EF) relaying strategies are employed to mitigate the interference by jointly optimizing equalizer weights and power allocation for dual-hop MIMO relay networks. Two scenarios with different channel state information (CSI) knowledge are investigated: 1) full CSI at the relays and 2) only backward CSI at the relays and the destination. By considering CSI availability and using the minimum-mean-square-error (MMSE) criterion, iterative algorithms are proposed for the joint design of equalizer weights and power allocation to resolve the interference problem. We then extend the design to a more general case, in which the direct link between the source and the destination is taken into account. Furthermore, two relay selection algorithms based on allocated power and MSE performance are investigated for the two scenarios, which attain a performance that is comparable to that of cases with brute-force search or without relay selection. The design framework can capture the impact of the available CSI at the relays and the destination on the performance of MIMO multirelay networks with multipath receptions. [ABSTRACT FROM AUTHOR]

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 first study the design of network coding for the generalized multiple-input–multiple-output (MIMO) Y channels, where K users wish to exchange information with each other within two time slots. Precoding at each user and the relay is carefully constructed to ensure that the signals from the same user pair are grouped together and that cross-pair interference can be canceled. In addition, a simple mapping function is proposed to ensure low-complexity detection at the relay. Exact expressions of symbol error rate (SER) are then developed to establish the explicit relationship between the diversity gain and the number of node antennas. Monte Carlo simulation is also provided to demonstrate the performance of the proposed scheme. [ABSTRACT FROM PUBLISHER]

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 study the impact of phase noise on the downlink performance of a multiuser multiple-input–multiple-output (MIMO) system, where the base station (BS) employs a large number of transmit antennas M. We consider a setup where the BS employs M_{\mathrm{osc}} free-running oscillators, and M/M_{\mathrm{osc}} antennas are connected to each oscillator. For this configuration, we analyze the impact of phase noise on the performance of zero forcing (ZF), regularized ZF, and matched filter precoders when M and the number of users K are asymptotically large, whereas the ratio M/K=\beta increases, the SINR performance of all considered precoders degrades. On the other hand, the variance of the random phase variations caused by the BS oscillators reduces with increasing M\mathrm{osc}. Through Monte Carlo simulations, we verify our analytical results and compare the performance of the precoders for different phase noise and channel noise variances. For all considered precoders, we show that when \beta is small, the performance of the setup where all BS antennas are connected to a single oscillator is superior to that of the setup where each BS antenna has its own oscillator. However, the opposite is true when $\beta$ is large and the signal-to-noise ratio (SNR) at the users is low. [ABSTRACT FROM AUTHOR]

It is known that interference alignment (IA) plays an important role in improving the degree of freedom (DoF) of multi-input and multi-output (MIMO) systems. However, most of the traditional IA schemes suffer from the high computational complexity and require the global and instantaneous channel state information (CSI), both of which make them difficult to be extended to cellular MIMO systems. To handle these issues, two new IA schemes, i.e., the retrospective interference regeneration (RIR) scheme and the beamforming based distributed retrospective interference alignment (B-DRIA) scheme, are proposed for cellular $K$ -user MIMO downlink networks. For the RIR scheme, it adopts interference elimination algorithm to erase redundant symbols in inter-cell interference (ICI) signals, and then uses interference regeneration algorithm to avoid secondary interference. The RIR scheme obtains greater DoF gain than the retrospective interference alignment (RIA) scheme, but incurs performance degradation when the transceiver antennas ratio (TAR) approaches 1. Therefore, the B-DRIA scheme is further proposed. For the B-DRIA scheme, the cellular beamforming matrix is introduced to eliminate the ICI, and meanwhile distributed RIA algorithm is adopted to align inter-user interference (IUI). The simulation results show that the B-DRIA scheme obtains larger DoF than the RIR scheme locally. Specifically, when TAR approaches 1, two schemes obtain the same DoF. While TAR approaches 2, the DoF of the B-DRIA scheme is superior than the RIR scheme. [ABSTRACT FROM AUTHOR]

As the demand to alleviate the high cost and energy consumption problem in cellular communication systems grows, research on ways to compensate the hardware impairments for introducing low-cost devices into multi-input multi-output (MIMO) systems is becoming important. In particular, the nonlinearity of power amplifiers may severely degrade the performance of MIMO systems by distorting the precoded signals. In this work, we study the performance and precoding strategy of downlink multiuser MIMO systems with nonlinear power amplifiers. First, we analyze the signal-to-interference-plus-noise ratio (SINR) of nonlinear systems to establish the relationship between the transmit power and SINR. We find that the condition for maximizing the SINR depends on the average channel gain. Specifically, the maximum SINR is determined by the uncorrelated distortion when the average channel gain is large and by the distortion of precoding vector when the average channel gain is small. Motivated by the analysis, we propose an iterative algorithm, which alternately updates the precoding and power allocation by resolving the complicated coupling factors in the SINR expressions of nonlinear system. Furthermore, the proposed algorithm implicitly controls the total transmit power so that the desired signal, interference, and distortion are properly balanced. By the simulation results, we verify the analysis results and show that the proposed scheme outperforms the conventional schemes and achieves a near-optimal sum rate. [ABSTRACT FROM AUTHOR]

A multiple relay-aided downlink (DL) multi-user massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) system is investigated to support simultaneous connectivity to cell-edge users. The estimated uplink channel state information (CSI) is used for precoder designs, and statistical DL CSI is adopted for successive interference cancellation (SIC) at the users. The achievable rates are derived, and thereby, the deleterious effects of CSI uncertainty, imperfect SIC, inter-relay interference and intra-cluster pilot contamination are quantified. Fundamental trade-offs between the achievable sum rate and system scalability are explored via two pilot assignment schemes. The performance of the proposed system is compared with that of the orthogonal multiple access (OMA) counterpart. We reveal that the latter performs better in low-user regime because the former's achievable rates are hindered by intra-cluster pilot contamination and imperfect SIC.However, the proposed model provides better system scalability and outperforms OMA in the large-user regime. The performance of zero-forcing (ZF)/null-space (NS) precoding is compared with maximum ratio transmission (MRT). We show that NS-based ZF precoding can boost the sum rate by mitigating inter-cluster interference at the expense of a higher computational complexity than that of MRT. [ABSTRACT FROM AUTHOR]

We present analytical expressions for the expected per-user signal power and interference in a multi-user multiple input multiple output system with analog maximal ratio combining (MRC) on the uplink and with matched filtering precoding on the downlink. This leads to a closed-form approximation of expected per-user signal-to-interference-plus-noise ratio (SINR). The analysis is carried out for different base station layouts, including a centralized collocated array and a distributed system with arbitrarily correlated Rayleigh fading. Unlike the digital MRC system, where the performance improves for a more distributed system, we show that analog MRC performs best in a centralized configuration. Furthermore, numerical results show that both analog and digital MRC benefit from a strong line-of-sight (LoS) presence in Ricean fading channels as the Rice K factor reduces the interference power. We show that in a centralized system, the performance of analog and digital MRC converge with increasing K factor, because strong LoS reduces the diversity of incoming signal power utilized by digital MRC. On the other hand, in a distributed system, the performance gap between these two techniques will remain due to the diversity of signal powers. Our closed-form approximation of the expected per-user SINR is general and appropriate for moderate to large numbers of antennas and arbitrary correlation models. [ABSTRACT FROM AUTHOR]

In this correspondence, we propose an efficient hybrid beamforming algorithm for multipair two-way relaying systems with a large number of antenna elements. We first investigate an asymptotic behavior of the fully digital (FD) case where the number of radio frequency (RF) chains equals that of antenna elements. Our analysis reveals that the optimal RF filters can be determined by the array response vectors in the asymptotic region without consideration of the baseband (BB) filters. From this observation, we provide a new RF filter design based on the Gram–Schmidt process. Also, in order to manage interpair interference, we design BB filters based on the weighted sum minimum mean square error for given RF filters. Our simulation results demonstrate that as the number of antenna elements grows, our method achieves the optimal FD performance with much reduced computational complexity. [ABSTRACT FROM AUTHOR]