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In this paper, we develop an innovative approach to quantitatively characterize the performance of ultra-dense wireless networks in a plethora of propagation environments. The proposed framework has the potential of simplifying the cumbersome procedure of analyzing the coverage probability and allowing the unification of single- and multi-antenna networks through compact analytical representations. By harnessing this key feature, we develop a novel statistical machinery to study the scaling laws of wireless networks densification considering general channel power distributions including small-scale fading and shadowing as well as associated beamforming and array gains due to the use of multiple antenna. We further formulate the relationship between network density, antenna height, antenna array seize and carrier frequency showing how the coverage probability can be maintained with ultra-densification. From a system design perspective, we show that, if multiple antenna base stations are deployed at higher frequencies, monotonically increasing the coverage probability by means of ultra-densification is possible, and this without lowering the antenna height. Simulation results substantiate performance trends leveraging network densification and antenna deployment and configuration against path loss models and signal-to-noise plus interference thresholds. [ABSTRACT FROM AUTHOR]

This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or preprocessed interference-aware operation. This paper presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein. [ABSTRACT FROM AUTHOR]

It is known that superposition signaling in Gaussian interference networks is capable of improving the achievable rate region. However, the problem of maximizing the rate gain offered by superposition signaling is computationally prohibitive, even in the simplest case of two-user single-input single-output interference networks. This paper examines superposition signaling for the general multiple-input multiple-output broadcast Gaussian interference networks. The problem of maximizing either the sum rate or the minimal user’s rate under superposition signaling and dirty paper coding is solved by a computationally efficient path-following procedure, which requires only a convex quadratic program for each iteration but ensures convergence at least to a locally optimal solution. Numerical results demonstrate the substantial performance advantage of the proposed approach. [ABSTRACT FROM AUTHOR]

Precoder optimization with full channel state information for finite alphabet signals over multiple-input multiple-output random channels is investigated in this paper. The precoder is represented by a product of power allocation matrix and constellation-forming matrix. There was an optimal algorithm introduced in the literature to globally maximize the channel mutual information by iteratively optimizing these two matrices. However, the computational complexity of the optimal algorithm is painfully high, especially when it is used with the high-order modulation and the high-data stream number. In this paper, we propose a novel sub-optimal low-complexity precoding algorithm and compare it with the optimal one. The new algorithm proceeds in two steps. First, the constellation-forming matrix is fixed in order to maximize the minimum Euclidean distance between the received symbols, which ensures high channel mutual information. Then, given the constellation-forming matrix, an iterative algorithm searches for the power allocation matrix that maximizes the channel mutual information. Since optimizing only one matrix instead of two, the new algorithm not only achieves a lower computational complexity but also avoids the use of initial values, which must be carefully selected for each channel and signal-to-noise ratio for fast convergence. Another advantage of the new algorithm is that the resulting precoder has a fixed form of received constellation thanks to the fixed constellation-forming matrix. This allows us to optimize the symbol mapping on the received constellation. Simulation results show that the proposed low-complexity precoder achieves error-rate performance that is close to performance of the optimal one when the conventional mapping is used. In addition, the new precoder used with optimized mapping at received constellation shows significant error-rate performance improvement. [ABSTRACT FROM AUTHOR]

Full-duplex (FD) jamming transceivers recently have been shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this paper, we investigate whether FD jamming can also improve the system’s secrecy energy efficiency (SEE) in terms of securely communicated bits per Joule when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high signal-to-noise ratio (SNR), or for a bidirectional FD communication setup. [ABSTRACT FROM AUTHOR]

Combining cache and heterogeneous cellular networks (HetNets) together is proposed to satisfy the increasing capacity requirements in 5G networks. In this paper, we consider the analysis and optimization of random caching in the $K$ -tier multi-antenna multi-user HetNets. We derive the expressions of the cache hit probability and the potential throughput, using tools from stochastic geometry. Limiting to the fully loaded interference-limited scenario, we obtain the closed-form exact expressions and the upper bounds of the metrics. The linear asymptotic expression of the cache hit probability in the high signal to interference and noise ratio (SINR) threshold region is also obtained. Based on analytical results, we consider the potential throughput maximization problem via optimizing the caching distribution. For a general scenario, we obtain a local optimal solution and a simple approximate asymptotic optimal solution in the high SINR threshold region. For a special case where each BS serves the largest number of users per resource block, we numerically solve a non-convex problem and propose a sub-optimal caching strategy by approximation, where a closed-form result is obtained in each iteration. Numerical simulations show that our proposed caching schemes outperform existing caching schemes. Analysis and optimization results provide insightful design guidelines for the cache-enabled multi-antenna HetNets. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the quantization and the feedback of downlink spatial covariance matrix for massive multiple-input multiple-output (MIMO) systems with cascaded precoding. Massive MIMO has gained a lot of attention recently because of its ability to significantly improve the network performance. To reduce the overhead of downlink channel estimation and uplink feedback in frequency-division duplex massive MIMO systems, cascaded precoding has been used to convert high-dimensional physical channels into low-dimensional effective channels. For the cascaded precoding, the inner precoder is determined by the downlink spatial covariance matrix, which is unknown in the base station (BS). To address this issue, we propose a spatial spectrum-based approach for the quantization and the feedback of the spatial covariance matrix. In this manner, the BS can obtain partial information on the downlink spatial covariance matrix. Our result shows that the inner precoder based on the proposed approach can be viewed as modulated discrete prolate spheroidal sequences and thus achieves much smaller spatial leakage than the traditional discrete Fourier transform submatrix-based precoding. Practical issues for the application of the proposed approach are also addressed in this paper. [ABSTRACT FROM PUBLISHER]

Multi-channel (MC) optical wireless communication (OWC) systems employing wave-division multiplexing for outdoors free-space optical communications, or multi-user time-division multiple access for indoors visible-light communications, e.g., can be modeled as parallel channels. Multi-input multi-output OWC systems can also be transformed, possibly with some performance loss, to parallel channels using pre-/post-coding. Studying the performance of such MC-OWC systems requires characterizing the capacity of the underlying parallel channels. In this paper, upper and lower bounds on the capacity of constant parallel OWC channels with a total average intensity constraint are derived. Then, this paper focuses on finding intensity allocations that maximize the lower bounds given channel-state information at the transmitter (CSIT). Due to its nonconvexity, the Karush–Kuhn–Tucker conditions are used to describe a list of candidate allocations. Instead searching exhaustively for the best solution, low-complexity near-optimal algorithms are proposed. The resulting optimized lower bound nearly coincides with capacity at high signal-to-noise ratio (SNR). Under a quasi-static channel model and in the absence of CSIT, outage probability upper and lower bounds are derived. Those bounds also meet at high SNR, thus characterizing the outage capacity in this regime. Finally, the results are extended to a system with both average and peak intensity constraints. [ABSTRACT FROM PUBLISHER]

The optimal weighting matrix design at the relay node for the V-BLAST based amplify-and-forward (AF) MIMO relay transmission scheme has been intensively investigated in literature. However, there are few papers considering the optimal design of the weighting matrix at the relay node for orthogonal space time block codes (OSTBCs) based AF MIMO relay transmission scheme. In this paper, the maximum-SNR weighting matrix at the relay node is designed for the OSTBC based AF MIMO relay scheme, so that for the first time we can quantify the SNR gain by optimizing the weighting matrix at the relay node for the OSTBC based AF MIMO relay scheme. Specifically, the canonical form of the optimal linear weighting matrix is derived by exploiting matrix inequality theory and majorization theory. Furthermore, we propose a simulation based Gamma approximation method for diversity order analysis. The simulation results show that the proposed optimal weighting matrix significantly outperforms the traditional scalar-gain weighting matrix for the OSTBC based AF MIMO relay scheme. [ABSTRACT FROM PUBLISHER]

Characterizing the fundamental energy efficiency (EE) performance of multiple-input–multiple-output interfering broadcast channels (MIMO-IFBC) is important for the design of green wireless system. In this paper, we propose a new network architecture proposition based on EE maximization for Multi-Cell MIMO-IFBC within the context of interference alignment (IA). Particularly, EE is maximized subject to maximum power and minimum throughput constraints. We propose two schemes to optimize EE for different signal-to-noise ratio (SNR) regions. For high-SNR operating regions, we employ a grouping-based IA scheme to jointly cancel intra- and inter-cell interferences and thus transform the MIMO-IFBC to a single-cell MIMO scenario. A gradient-based power adaptation scheme is proposed based on water-filling power adaptation and singular value decomposition to maximize EE for each cell. For moderate SNR cases, we propose an approach using dirty paper coding (DPC) with the principle of multiple access channel and broadcast channel duality to perform IA while maximizing EE in each cell. The algorithm in its dual form is solved using a subgradient method and a bisection searching scheme. Simulation results demonstrate the superior performance of the proposed schemes over several existing approaches. It also shows that interference-nulling-based IA approaches outperform hybrid DPC-IA approach in high-SNR region, and the opposite occurs in low-SNR region. [ABSTRACT FROM PUBLISHER]

The degrees of freedom (DoF) of the 3-user multiple-input multiple-output (MIMO) interference channel (IC) with full channel state information and constant channel coefficients are investigated when $(p,p+1)$ antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al., which conjectured but did not prove the DoF for the antenna settings with $p>1$. Here the achievability of the DoF outer bound is formally proved using linear methods, thereby avoiding the use of the rational dimensions framework. The proposed transmission scheme exploits asymmetric complex signaling together with symbol extensions in time and space interference alignment concepts. While the paper deals with the $p=2,3,\ldots,6$ cases, providing the specific transmit and receive filters, there are also provided the tools needed for proving the achievability of the optimal DoF for $p>6$, whose DoF characterization is conjectured. [ABSTRACT FROM PUBLISHER]

We consider optimal linear precoder and decoder designs in a multi-cell multiple-input multiple-output system, where base stations and mobile users are both operating in full-duplex (FD) mode. Existing works on FD cellular systems focus on the maximization of overall throughput, which can result in unfairness between uplink and downlink channels depending on the self-interference power and inter-user interference levels. Therefore, to introduce fairness, in this paper, we consider the transmit and receive beamforming designs that maximize the harmonic-sum of signal-to-interference-plus-noise ratios (SINRs) in the uplink and downlink channels. We propose a low-complexity alternating optimization algorithm which converges to a stationary point. Moreover, in order to address practical system design aspects, we consider the transceiver design that enforces robustness against imperfect channel state information (CSI) while providing fair performance among the users. To this end, we formulate an optimization problem that maximizes the worst case SINR among all users under norm-bounded CSI errors. We devise a low-complexity iterative algorithm based on alternating optimization and semidefinite relaxation techniques. Numerical results verify the advantages of incorporating FD mode into cellular systems, and practical issues, such as CSI uncertainty and fairness performance. [ABSTRACT FROM PUBLISHER]

In practical massive MIMO systems, a substantial portion of system resources are consumed to acquire channel state information (CSI), leading to a drastically lower system capacity compared with the ideal case, where perfect CSI is available. In this paper, we show that the overhead for CSI acquisition can be largely compensated by the potential gain due to the sparsity of the massive MIMO channel in a certain transformed domain. To this end, we propose a novel blind detection scheme that simultaneously estimates the channel and data by factorizing the received signal matrix. We show that by exploiting the channel sparsity, our proposed scheme can achieve a degree of freedom (DoF) very close to the ideal case, provided that the channel is sufficiently sparse. Specifically, the achievable DoF has a fractional gap of only $1/T$ from the ideal DoF, where $T$ is the channel coherence time. This is a remarkable advance for understanding the performance limit of the massive MIMO system. We further show that the performance advantage of our proposed scheme in the asymptotic SNR regime carries over to the practical SNR regime. Numerical results demonstrate that our proposed scheme significantly outperforms its counterpart schemes in the practical SNR regime under various system configurations. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a system where full-duplex (FD) base-stations (BSs) communicate with half-duplex (HD) downlink (DL) and uplink (UL) users in a multi-user multi-cell network, where all nodes are equipped with multiple antennas. The introduction of FD BSs offers potential to increase spectral efficiency, however, it also causes a surge in the number of interference links compared with the HD network counterpart. Here, we apply linear interference alignment (IA) to manage interference in this network under imperfect channel state information (CSI). First, we characterize the performance losses incurred with respect to the achievable sum rate and degrees of freedom (DoFs). Results show that the general trend in performance loss is mainly determined by how the error scales with the signal-to-noise ratio (SNR). In particular, full UL and DL DoF can be achieved even under imperfect CSI when the channel error is at least inversely proportional to SNR. Moreover, in such cases the sum rate loss is always finite, and either goes to zero or is upper bounded by a derived value. Second, we design two linear IA algorithms applicable to the system under consideration. These are based on minimizing the mean square error (MMSE) and maximizing the signal-to-interference-plus-noise ratio, and consider statistical knowledge of the CSI error for added robustness. The proposed algorithms follow specific design principles that distribute the different interference components amongst the various beamformers and result in unitary receivers and precoders. In addition, we show that under certain conditions both designs result in identical beamforming solutions, even though the MMSE algorithm has lower computational complexity. Finally, we also derive the proper condition for IA feasibility in the multi-cell system under consideration. [ABSTRACT FROM PUBLISHER]

The non-regenerative massive multi-input-multi-output (MIMO) non-orthogonal multiple access (NOMA) relay systems are introduced in this paper. The NOMA is invoked with a superposition coding technique at the transmitter and successive interference cancellation (SIC) technique at the receiver. In addition, a maximum mean square error-SIC receiver design is adopted. With the aid of deterministic equivalent and matrix analysis tools, a closed-form expression of the signal to interference plus noise ratio (SINR) is derived. To characterize the performance of the considered systems, closed-form expressions of the capacity and sum rate are further obtained based on the derived SINR expression. Insights from the derived analytical results demonstrate that the ratio between the transmitter antenna number and the relay number is a dominate factor of the system performance. Afterward, the correctness of the derived expressions are verified by the Monte Carlo simulations with numerical results. Simulation results also illustrate that: 1) the transmitter antenna, averaged power value, and user number display the positive correlations on the capacity and sum rate performances, whereas the relay number displays a negative correlation on the performance and 2) the combined massive-MIMO-NOMA scheme is capable of achieving higher capacity performance compared with the conventional MIMO-NOMA, relay-assisted NOMA, and massive-MIMO orthogonal multiple access (OMA) scheme. [ABSTRACT FROM AUTHOR]

This paper considers the secrecy communication of a wirelessly powered network, where an energy-constrained legitimate transmitter (Alice) sends message to a legitimate receiver (Bob) with the energy harvested from a dedicated power beacon, while an eavesdropper (Eve) intends to intercept the information. A simple time-switching protocol with a time-switching ratio $\alpha $ is used to supply power for the energy-constrained legitimate transmitter. To improve the physical layer security, we first propose a protocol that combines maximum ratio transmission with zero-forcing (ZF) jamming for the case without Eve’s channel state information (CSI), i.e., Alice has access to Bob’s CSI only. Then, we propose a protocol that uses a ZF transmitting strategy to minimize the signal-to-noise ratio (SNR) at Eve for the case that Alice is capable of obtaining partial CSI related to Eve. Closed-form expressions and simple approximations of the connection outage probability and secrecy outage probability are derived for both protocols. Furthermore, the secrecy throughput as well as the diversity orders achieved by our proposed protocols are characterized, and the optimal time-switching ratio $\alpha $ and power allocation coefficient $\beta $ for secrecy throughput maximization are derived in the high SNR regime. Finally, numerical results validate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose a general framework to study the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in massive multiple-input-multiple-output-enabled heterogenous networks while ensuring proportional rate fairness among users and taking into account the backhaul capacity constraint. We aim at jointly optimizing user association, spectrum allocation, power coordination, and the number of activated antennas, which is formulated as a multi-objective optimization problem maximizing EE and SE simultaneously. With the help of weighted Tchebycheff method, it is then transformed into a single-objective optimization problem, which is a mixed-integer non-convex problem and requires unaffordable computational complexity to find the optimum. Hence, a low-complexity effective algorithm is developed based on primal decomposition, where we solve the power coordination and number of antenna optimization problem and the user association and spectrum allocation problem separately. Both theoretical analysis and numerical results demonstrate that our proposed algorithm can fast converge within several iterations and significantly improve both the EE-SE tradeoff performance and rate fairness among users compared with other algorithms. [ABSTRACT FROM AUTHOR]

Channel reciprocity in time-division duplexing (TDD) massive multiple-input multiple-output (MIMO) systems can be exploited to reduce the overhead required for the acquisition of channel state information (CSI). However, perfect reciprocity is unrealistic in practical systems due to random radio-frequency (RF) circuit mismatches in uplink and downlink channels. This can result in a significant degradation in the performance of linear precoding schemes, which are sensitive to the accuracy of the CSI. In this paper, we model and analyse the impact of RF mismatches on the performance of linear precoding in a TDD multi-user massive MIMO system, by taking the channel estimation error into considerations. We use the truncated Gaussian distribution to model the RF mismatch, and derive closed-form expressions of the output signal-to-interference-plus-noise ratio for maximum ratio transmission and zero forcing precoders. We further investigate the asymptotic performance of the derived expressions, to provide valuable insights into the practical system designs, including useful guidelines for the selection of the effective precoding schemes. Simulation results are presented to demonstrate the validity and accuracy of the proposed analytical results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate secure transmission over the large-scale multiple-antenna wiretap channel with finite alphabet inputs. First, we investigate the case where instantaneous channel state information (CSI) of the eavesdropper is known at the transmitter. We show analytically that a generalized singular value decomposition (GSVD)-based design, which is optimal for Gaussian inputs, may exhibit a severe performance loss for finite alphabet inputs in the high signal-to-noise ratio regime. In light of this, we propose a novel Per-Group-GSVD (PG-GSVD) design, which can effectively compensate the performance loss caused by the GSVD design. More importantly, the computational complexity of the PG-GSVD design is by orders of magnitude lower than that of the existing design for finite alphabet inputs while the resulting performance loss is minimal. Then, we extend the PG-GSVD design to the case where only statistical CSI of the eavesdropper is available at the transmitter. Numerical results indicate that the proposed PG-GSVD design can be efficiently implemented in large-scale multiple-antenna systems and achieves significant performance gains compared with the GSVD design. [ABSTRACT FROM PUBLISHER]

Millimeter wave (mmWave) communications use large transmission bandwidth and experience severe propagation conditions. This forces the communication system to operate in the so-called wideband regime, where signals must be increasingly “peaky” in order to attain a large fraction of the peak unconstrained wideband capacity. This paper investigates the capacity of the noncoherent channels as a function of bandwidth for signals with average and peak power constraints operating in the millimeter spectrum. Upper and lower bounds on capacity are provided, and the impact of features peculiar to mmWave channels is investigated. Numerical results for a scenario based on recent experimental campaigns are provided. It is shown that the rate achievable by a typical user in a mmWave cell with “non-peaky” signaling can be bounded away from the peak unconstrained wideband capacity. This suggests to reconsider the role of signaling “peakedness” in future mmWave communications. [ABSTRACT FROM PUBLISHER]

In this paper, we characterize the total degrees of freedom (DoFs) of the full-duplex asymmetric multiple-input multiple- output (MIMO) three-way channel. Each node has a separate-antenna full-duplex MIMO transceiver with a different number of antennas, where each antenna can be configured for either signal transmission or reception. We study this system under two message configurations; the first configuration is when each node has two unicast messages to be delivered to the two other nodes, while the second configuration is when each node has two unicast messages as well as one broadcast message to be delivered to the two other nodes. For each configuration, we first derive upper bounds on the total DoF of the system. Cut-set bounds in conjunction with genie-aided bounds are derived to characterize the achievable total DoF. Afterward, we analytically derive the optimal number of transmit and receive antennas at each node to maximize the total DoF of the system, subject to the total number of antennas at each node. Finally, the achievable schemes for each configuration are constructed. The proposed schemes are mainly based on zero-forcing and null-space transmit beamforming. We show that the derived outer and inner bounds on the total DoF are tight for each message configuration. [ABSTRACT FROM PUBLISHER]

This paper investigates the throughput-reliability tradeoff (TRT) for dual-hop amplify-and-forward relay systems with one source, one destination, and multiple relays, and its relationship with the diversity-multiplexing tradeoff (DMT). The TRT was proposed in the context of MIMO block fading channels to reveal the interplay between the signal-to-noise ratio (SNR), rate R, and outage probability that are not accessible through the DMT. The contributions of this paper include the calculation of the TRT expressions for two classes of amplify-and-forward protocols: the slotted amplify-and-forward and the non-orthogonal amplify-and-forward. Based on the derived expressions, relationships between the SNR, rate and outage probability are explored. The relationship between the TRT and the DMT is investigated. One of the goals of the TRT is to predict the slope and offset of the outage vs. SNR set of curves parameterized by different rates. We verify the accuracy of the TRT predictions in the context of amplify-and-forward relays. [ABSTRACT FROM AUTHOR]

Recently, the Degrees-of-Freedom (DoFs) region of multiple-input-single-output (MISO) networks with imperfect channel state information at the transmitter (CSIT) has attracted significant attention. An achievable scheme, known as rate-splitting (RS), integrates common-message-multicasting and private-message-unicasting. In this paper, focusing on the general $K$ -cell MISO IC with an arbitrary CSIT quality of each interfering link, we first identify the DoF region achieved by RS. Second, we introduce a novel scheme, so called topological RS (TRS), whose novelties compared with RS lie in a multi-layer structure and in transmitting multiple common messages to be decoded by groups of users rather than all users. The design of TRS is motivated by a novel interpretation of the $K$ -cell IC with imperfect CSIT as a weighted sum of a series of partially connected networks. We show that the DoF region achieved by TRS yields the best known result so far, and we find the maximal sum DoF via hypergraph fractional packing. Finally, for a realistic scenario where each user is connected to three dominant transmitters, we identify the sufficient condition where TRS strictly outperforms conventional schemes, and show that TRS is optimal for some CSIT qualities. [ABSTRACT FROM PUBLISHER]

Due to the difficulty in manipulating the distribution of Wishart random matrices, the performance analysis of multiple-input-multiple-output (MIMO) channels has mainly focused on deriving capacity bounds via Jensen’s inequality. However, to the best of our knowledge, the tightness of Jensen’s bounds has not yet been rigorously quantified in the general MIMO context. This paper proposes a new methodology for measuring the tightness of Jensen’s bounds via the sandwich theorem. In particular, we first compare the tightness of two different pairs of upper/lower bounds for a general class of MIMO channels based on the unordered eigenvalue of the instantaneous correlation matrix and for arbitrary numbers of antennas. The tightness of Jensen’s bounds in different channel scenarios is investigated including multiuser MIMO with maximal ratio combining. Our analysis is facilitated by deriving some new results for finite-dimensional Wishart matrices, i.e., for the arbitrary moments of the unordered eigenvalue of central and non-central Wishart matrices. Our results provide very interesting insights into the implications of the system parameters, such as the number of antennas, and signal-to-noise ratio, on the tightness of Jensen’s bounds, and showcase the suitability and limitations of Jensen’s bounds. [ABSTRACT FROM PUBLISHER]

Although there has been a growing interest on the study of diversity-multiplexing tradeoff (DMT), the existing works are mostly restricted to the outcomes reported for Rayleigh, Rician, and Nakagami fading channels. In this paper, we investigate the optimal tradeoff in the presence of log-normal fading, which provides an accurate model for indoor wireless, optical wireless, and ultra-wideband channels. We consider a multiple-input multiple-output (MIMO) log-normal channel, derive the outage probability expression, and then present the asymptotical DMT expression. It is shown that the asymptotical maximum diversity gain tends to infinity with logarithm of signal-to-noise ratio (SNR). To have further insight, we normalize the DMT with that of single-input single-output case and express the relative asymptotical DMT of the MIMO log-normal channel as a function of the number of transmit and receive antennas. We further study DMT for finite SNRs and demonstrate convergence to the asymptotical case. Extensive numerical results are provided to corroborate the analytical derivation. [ABSTRACT FROM AUTHOR]

Optimal data detection of data transmitted over a linear channel can always be implemented through the Viterbi algorithm (VA). However, in many cases of interest the memory of the channel prohibits direct application of the VA. A popular and conceptually simple method in this case, studied since the early 1970s, is to first filter the received signal in order to shorten the memory of the channel, and then to apply a VA that operates with the shorter memory. We shall refer to this general concept as a channel shortening (CS) receiver. Although studied for almost four decades, an information theoretic understanding of what such a simple receiver solution is actually doing is not available. In this paper, we show that an optimized CS receiver has a direct correspondance to the chain rule of mutual information. Furthermore, we show that the tools for analyzing the ensuing achievable rates from an optimized CS receiver are precisely the same as those used for analyzing the achievable rates of a minimum mean-square-error (MMSE) receiver. [ABSTRACT FROM AUTHOR]

This paper is concerned with the spatial modulation (SM), a multiple-input multiple-output (MIMO) transmission technique, that maps information bits not only into the conventional two-dimensional signal points but also into the indices of active transmit antennas. We present a two-layer coded SM scheme, in which the spatial bits carried by the antenna indices and the signal bits carried by the conventional signals are protected separately by two error correction codes. For the ease of decoding process, the code rates are allocated according to the chain rule of the mutual information. We choose block Markov superposition transmission (BMST) codes for each layer, since they are easily designed for any given code rate with a predictable performance lower bound. An iterative sliding-window decoding algorithm is also presented by exchanging messages iteratively between the two BMST decoders and the soft-in soft-out (SISO) demapper of the SM. To reduce the computational complexity, we propose to implement the SISO demapping algorithm by employing only partial soft inputs. Numerical results show that the BMST-SM system performs well over uncorrelated Rayleigh fading channels. [ABSTRACT FROM AUTHOR]

In this paper, we provide a comprehensive analytical framework on the performance of multiple-input multiple-output (MIMO) mutlihop amplify-and-forward relay network employing transmit antenna selection (TAS) with receive maximal ratio combining (MRC) in the presence of randomly located interferers. The channel fading models per hop are assumed to be independent and follow exponential random distribution, and the interference is distributed according to the spatial Poisson point process PPP, which is further known as symmetric alpha stable distribution. The impact of spatial dependence across multiple antennas is facilitated by considering three different network interference models: 1) the isotropic model, where all receive antennas see interference belonging to the same Poisson point process (PPP); 2) the independent model, where each receive antenna sees interference belonging to a different independent PPP; and 3) the mixture model, where each receive antenna sees the superposition of the two previous models. The end-to-end transmission is performed using two TAS modes, which includes signal-to-noise ratio (SNR)-based selection, and signal-to-interference noise ratio (SINR)-based selection. The analysis provides new analytical results for the outage probability and symbol error rates (SER). In addition, the impact of feedback delay on the performance of the proposed system for SNR-based selection is investigated. We further study the optimum resource allocation strategies including power allocation, position allocation, and joint allocation for power and position. The obtained results are clarified through selected numerical and simulated examples. [ABSTRACT FROM AUTHOR]

Secrecy capacity is a fundamental information-theoretic performance metric to predict the maximum data rate of reliable communication, while the intended message is not revealed to the eavesdropper. Motivated by this consideration in this paper, a unified communication-theoretic framework for the analysis of the probability of nonzero secrecy capacity, the secrecy outage probability, and the secrecy capacity of multiple-antenna systems over fading channels is proposed. Specifically, a powerful frequency-domain approach is first developed in which the integrals involved in the evaluation of the probability of nonzero secrecy capacity and secrecy outage probability are transformed into the frequency domain, by employing Parseval’s theorem. A generic approach for the evaluation of the asymptotic secrecy outage probability at high signal-to-noise ratio (SNR) region is also introduced, thus providing useful insight as to the parameters affecting the secrecy performance. Finally, a unified numerical approach for computing the average secrecy capacity of multiple-antenna systems under arbitrary fading environments is developed. The proposed framework is general enough to accommodate any well-known multiantenna transmission technique and fading model. Finally, the secrecy performance of several multiple-antenna system setups is assessed, in the presence of generalized fading conditions and arbitrary antenna correlation, while various numerical and computer simulation results are shown and compared to substantiate the proposed mathematical analysis. [ABSTRACT FROM AUTHOR]

In this paper, we investigate joint beamforming and power allocation in multicell multiple-input single-output (MISO) downlink networks. Our goal is to maximize the utility function defined as the ratio between the system weighted sum rate and the total power consumption subject to the users’ quality of service requirements and per-base-station (BS) power constraints. The considered problem is nonconvex and its objective is in a fractional form. To circumvent this problem, we first resort to an virtual uplink formulations of the the primal problem by introducing an auxiliary variable and applying the uplink-downlink duality theory. By exploiting the analytic structure of the optimal beamformers in the dual uplink problem, an efficient algorithm is then developed to solve the considered problem. Furthermore, to reduce further the exchange overhead between coordinated BSs in a large-scale antenna system, an effective coordinated power allocation solution only based on statistical channel state information is reached by deriving the asymptotic optimization problem, which is used to obtain the power allocation in a long-term timescale. Numerical results validate the effectiveness of our proposed schemes and show that both the spectral efficiency and the energy efficiency can be simultaneously improved over traditional downlink coordinated schemes, especially in the middle-high transmit power region. [ABSTRACT FROM AUTHOR]

This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under a Gaussian Interference compounded broadcast channel scenario. The basic idea is to split up the role of the transmit beamforming matrix according to the type of interference caused by each base station. It will be shown that, for a network of L base stations, the proposed method would result in achieving (L-1) degrees of freedom per user and convert the multi-cell multi-user MIMO channel into a set of single-cell single-user MIMO channels. Finally, we derive the relationship between all the relevant network elements as N_t=(L-d_s+1)K^\primeN_r+1, where N_t and $N_r$ are the numbers of transmit and receive antennas, respectively, L$ and d_s$ denote the number of cells and the number of data streams transmitted from each base station, and is the number of users per cell defined under the proposed system model. Hence, we show that the proposed scheme makes it possible to implement interference alignment using less antenna resources. [ABSTRACT FROM PUBLISHER]

In this paper, we study the problem of per-stream maximum sum-rate joint precoder and minimum mean-squared error equalizer design for the multi-input multi-output interference channel. We consider the general case of more than three users with more than one stream per user. We propose a generalized iterative algorithm which directly maximizes the sum-rate without assuming the signal-to-noise ratio to be infinite. To reduce complexity, which can become prohibitive for large network size, we examine the performance-complexity tradeoffs involved in a sparse equalizer design. Joint precoder and equalizer optimization requires alternation between the forward and reverse links and assumes perfect synchronization between the transmitters and receivers at each network node, resulting in extensive overhead and spectral efficiency loss. To overcome this serious drawback, we propose a new design approach based on weighted-sum-rate maximization assuming a virtual equalizer type at the transmitter to limit the optimization process to the transmitter side. In addition, we quantify the sum-rate loss due to mismatched equalizer types and demonstrate the robustness of our proposed sum-rate weighting strategy to such mismatches with perfect or imperfect channel knowledge. Finally, we derive asymptotic performance expressions and verify their accuracy numerically even for a moderate number of users. [ABSTRACT FROM PUBLISHER]

In this paper, we propose general-order transmit antenna selection to enhance the secrecy performance of multiple-input–multiple-output multieavesdropper channels with outdated channel state information (CSI) at the transmitter. To evaluate the effect of the outdated CSI on the secure transmission of the system, we investigate the secrecy performance for two practical scenarios, i.e., Scenarios I and II, where the eavesdropper's CSI is not available at the transmitter and is available at the transmitter, respectively. For Scenario I, we derive exact and asymptotic closed-form expressions for the secrecy outage probability in Nakagami- m fading channels. In addition, we also derive the probability of nonzero secrecy capacity and the \varepsilon-outage secrecy capacity, respectively. Simple asymptotic expressions for the secrecy outage probability reveal that the secrecy diversity order is reduced when the CSI is outdated at the transmitter, and it is independent of the number of antennas at each eavesdropper N_\textrmE , the fading parameter of the eavesdropper's channel m_\textrmE, and the number of eavesdroppers $M$. For Scenario II, we make a comprehensive analysis of the average secrecy capacity obtained by the system. Specifically, new closed-form expressions for the exact and asymptotic average secrecy capacity are derived, which are valid for general systems with an arbitrary number of antennas, number of eavesdroppers, and fading severity parameters. Resorting to these results, we also determine a high signal-to-noise ratio power offset to explicitly quantify the impact of the main channel and the eavesdropper's channel on the average secrecy capacity. [ABSTRACT FROM PUBLISHER]

With the increase of cell density and explosive growth of data traffic, user centric is becoming one of the design principles of next-generation cellular networks. One meaning of user centric lies in that no matter where a user is located, its demand in quality of service (QoS) will be guaranteed in high probability. One approach to achieve such an ambitious goal is allowing each user to select several preferred base stations to transmit cooperatively. In this paper, we propose a user-centric downlink cooperative transmission scheme with orthogonal beamforming based limited feedback, where the cooperative clusters of multiple users may overlap and per-cell codebooks are considered. To assist the central unit (CU) for scheduling users with guaranteed QoS and performing adaptive transmission, a method for each user to estimate its signal-to-noise-and-interference ratio is derived. Targeting to ensure the required QoS of multiple users, we propose a method to select the cooperative cluster at each user and provide a method to schedule users based on their service priorities and channel conditions at the CU, where the clusters are selected semidynamically. Simulation results show that the proposed scheme significantly increases the percentage of users with satisfactory QoS demands. [ABSTRACT FROM PUBLISHER]

This paper presents a joint space–frequency user scheduling approach to enhance the random beamforming (RBF) with limited feedback in multiple-input –multiple-output (MIMO) broadcast channels. Such scheme was shown to obtain the optimal scaling law of sum rate in the large number of user regime. However, for a small number of user cases, the system degrees-of-freedom cannot be well exploited, and the accuracy of predicting users' signal-to-interference-plus-noise ratios (SINRs) is also degraded. Motivated by these, two strategies are proposed to solve the problems. Specifically, the conventional spatial domain RBF is first extended to the space–frequency domain. The first strategy aims to maximize the number of active users based on users' initially predicted SINRs; the second strategy is to schedule the maximum number of users, whose preferred beams can coexist with each others, with more accurate users' SINRs prediction method. Computer simulations are carried out to examine the proposed strategies in terms of the sum rate and the number of active users. It is shown that the first strategy achieves close performance to the corresponding brute-force search with lower complexity. Moreover, the second strategy improves the performance by accurately predicting users' SINRs at the price of relatively increased complexity and feedback overhead. [ABSTRACT FROM PUBLISHER]

Optimal signaling for secrecy rate maximization in Gaussian MIMO wiretap channels is considered. While this channel has attracted a significant attention recently and a number of results have been obtained, including the proof of the optimality of Gaussian signalling, an optimal transmit covariance matrix is known for some special cases only and the general case remains an open problem. An iterative custom-made algorithm to find a globally-optimal transmit covariance matrix in the general case is developed in this paper, with guaranteed convergence to a global optimum. While the original optimization problem is not convex and hence difficult to solve, its minimax reformulation can be solved via the convex optimization tools, which is exploited here. The proposed algorithm is based on the barrier method extended to deal with a minimax problem at hand. Its convergence to a global optimum is proved for the general case (degraded or not) and a bound for the optimality gap is given for each step of the barrier method. The performance of the algorithm is demonstrated via numerical examples. In particular, 20 to 40 Newton steps are already sufficient to solve the sufficient optimality conditions with very high precision (up to the machine precision level), even for large systems. Even fewer steps are required if the secrecy capacity is the only quantity of interest. The algorithm can be significantly simplified for the degraded channel case and can also be adopted to include the per-antenna power constraints (instead or in addition to the total power constraint). It also solves the dual problem of minimizing the total power subject to the secrecy rate constraint. [ABSTRACT FROM PUBLISHER]

Studies of the MISO Broadcast Channel (BC) with delayed Channel State Information at the Transmitter (CSIT) have so far focused on the sum-rate and Degrees-of-Freedom (DoF) region analysis. In this paper, we investigate for the first time, the error rate performance at finite SNR and the diversity-multiplexing tradeoff (DMT) at infinite SNR of a space-time encoded transmission over a two-user MISO BC with delayed CSIT. We consider the so-called MAT protocol obtained by Maddah-Ali and Tse, which was shown to provide 33% DoF enhancement over TDMA. While the asymptotic DMT analysis shows that MAT is always preferable to TDMA, the Pairwise Error Probability analysis at finite SNR shows that MAT is in fact not always a better alternative to TDMA. Benefits can be obtained over TDMA only at a very high rate or once concatenated with a full-rate full-diversity space-time code. The analysis is also extended to spatially correlated channels, and the influence of transmit correlation matrices and user pairing strategies on the performance are discussed. Relying on statistical CSIT, signal constellations are further optimized to improve the error rate performance of MAT and make it insensitive to user orthogonality. Finally, other transmission strategies relying on delayed CSIT are discussed. [ABSTRACT FROM PUBLISHER]

This paper addresses achievable rates and related link adaptation for precoded Multiple-Input Multiple-Output transmission in an orthogonal frequency division multiple access system with uncompensated frequency flat transceiver I/Q imbalance. Precoder selection on the mirror subcarrier induces variations of the signal quality on the subcarrier of interest and causes outage. We consider link adaptation strategies with infinite rate granularity for block and ergodic fading models where the transmitter knows the statistics of the induced interference and has perfect channel state information of the wanted link. An optimal I/Q aware transmission method is used for these fading models. Performance of I/Q aware methods is compared with blind back-off selection. [ABSTRACT FROM PUBLISHER]

This paper proposes a semianalytical performance prediction method for an iterative receiver that processes signals arriving through a frequency-selective multiple-input multiple-output radio channel. Earlier results provide a distribution of the signal-to-interference-plus-noise ratio at the output of a frequency domain soft interference cancellation minimum mean square error equalizer, which is used to approximate the distribution of the log-likelihood ratios (LLRs) of the demapped bits. Mutual information transfer charts establish a bijective relationship between the variance of the LLRs and the mutual information. We assume a 3rd Generation Partnership Project compliant turbo code, whose transfer charts are simulated in advance. By approximating the LLR variance distribution of the demapped equalizer output, we can evaluate the probability of an intersection between an equalizer chart associated with a random channel realization and a fixed decoder chart. This probability provides the frame error rate. Our proposed prediction method allows horizontally and vertically encoded spatial multiplexing schemes. The vertically encoded scheme is complemented by the inclusion of the Chase combining hybrid automatic repeat request protocol. The proposed method allows reasonable receive antenna correlation. [ABSTRACT FROM AUTHOR]

In this paper, we propose transmit antenna selection with maximal ratio combining (TAS/MRC) in dual-hop decode-and-forward spectrum-sharing relaying networks with the primary user's interference and outdated channel state information (CSI). In this network, a single antenna that maximizes the received SNR is selected at the secondary transmitter, and the MRC is adopted at the secondary receiver. To efficiently evaluate the impact of key parameters on the system performance, we derive the exact analytical expression for the outage probability of the secondary network in a Rayleigh fading channel. Moreover, we present simple asymptotic expressions for the outage probability in a high SNR regime, which reveal practical insights on the achievable diversity order and coding gain. The findings suggest that whether the outdated CSI concerning the secondary transmission links has significant impact on the outage probability of the system depends on the interference power constraint at primary receivers. Specifically, under the proportional interference power constraint, the achievable diversity order is affected by imperfect CSI regarding the secondary transmission links, and the diversity–multiplexing tradeoff is independent of the primary network. However, under the fixed interference power constraint, the error floor is displayed, and the achievable diversity order reduces to zero regardless of the CSI concerning the secondary transmission links. [ABSTRACT FROM AUTHOR]

The channel capacity for the multiple-input multiple-output (MIMO) relay channel is still an open problem. In view of this gap, upper and lower bounds were found by Wang et al., 2005. This paper presents an extensive study of mutual information and outage probability of Rayleigh fading MIMO relay channels based on the eigenvalues distribution for the sum of complex Wishart matrices. Interestingly, for certain scenarios, upper and lower bounds are coincident providing the real channel capacity. To compute outage probability, a Gaussian approximation for mutual information has been used. Furthermore, it was proposed an equivalent distribution for the sum of Wishart matrices, which proves to be excellent in all scenarios. Closed-form expressions for probability density function and outage probability have been found for the general case of any number of antennas and any SNR values. Analytical expressions have been validated by means of Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

Modern communications systems use multiple-input multiple-output (MIMO) and high-order QAM constellations for maximizing spectral efficiency. However, as the number of antennas and the order of the constellation grow, the design of efficient and low-complexity MIMO receivers possesses big technical challenges. For example, symbol detection can no longer rely on maximum likelihood detection or sphere-decoding methods, as their complexity increases exponentially with the number of transmitters/receivers. In this paper, we propose a low-complexity high-accuracy MIMO symbol detector based on the Expectation Propagation (EP) algorithm. EP allows approximating iteratively at polynomial-time the posterior distribution of the transmitted symbols. We also show that our EP MIMO detector outperforms classic and state-of-the-art solutions reducing the symbol error rate at a reduced computational complexity. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new beamforming technique that maximizes the end-to-end signal-to-noise ratio (SNR) foramplify-and-forward multiple-input–multiple-output cooperative relaying systems with direct link between thesource and the destination. Instead of conventional schemes resorting to an iterative method, such as a gradient ascentalgorithm, our scheme provides a simple closed-form solution for source-relay joint beamformer designs. To this end, wefirst derive a new expression of the end-to-end SNR for the cooperative relaying systems and its lower bound, which isgiven as the harmonic mean of two individual SNRs. Then, a new beamforming scheme, which adaptively optimizes one of thetwo SNRs depending on the channel condition, is proposed. In addition, we perform a diversity order analysis of theproposed scheme and show that our scheme achieves a full diversity order of relaying systems with direct link. It isconfirmed by simulation results that the proposed technique obtains almost identical performance to the gradient ascentalgorithm with much reduced complexity, and our analytical work accurately predicts the numerical results. [ABSTRACT FROM AUTHOR]

This paper analyzes the performance of an optimal single stream beamforming scheme for a multiple-input multiple-output (MIMO) relay network with dual-hop fixed-gain amplify-and-forward (AF) relaying. The source-relay and relay-destination channels undergo Rayleigh and Rician fading respectively. Different Rician fading scenarios are considered for relay-destination channel, depending on the rank of the Rician channel matrix. The channel state information is only available at the destination, and the destination computes the optimal transmit and receive beamforming vectors to maximize the instantaneous signal-to-noise ratio (SNR). The optimal transmit beamforming vector is sent back to the transmitter via a dedicated feedback link. We derive new analytical expressions for the cumulative distribution function, probability density function, and moments to statistically characterize the properties of the instantaneous SNR. These statistical properties are used to analyze the system performance in terms of the outage probability, average bit error rate, and the ergodic capacity. The performance analysis investigates the effects of the Rician factor, rank of the line-of-sight component, and number of antennas at the nodes on the system performance. The results reveal that the optimal single stream beamforming system provides better performance than an orthogonal space-time block coded based AF MIMO system. [ABSTRACT FROM PUBLISHER]

We present bounds and a closed-form high-SNR expression for the capacity of multiple-antenna systems affected by Wiener phase noise. Our results are developed for the scenario where a single oscillator drives all the radio-frequency circuitries at each transceiver (common oscillator setup), the input signal is subject to a peak-power constraint, and the channel matrix is deterministic. This scenario is relevant for line-of-sight multiple-antenna microwave backhaul links with sufficiently small antenna spacing at the transceivers. For the 2x 2 multiple-antenna case, for a Wiener phase-noise process with standard deviation equal to 6^°, and at the medium/high SNR values at which microwave backhaul links operate, the upper bound reported in the paper exhibits a 3\dB gap from a lower bound obtained using 64-QAM. Furthermore, in this SNR regime the closed-form high-SNR expression is shown to be accurate. [ABSTRACT FROM PUBLISHER]

In this paper, we propose clustered quantization techniques for multiuser multi-input/multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) using constellation based codebooks. Constellation based codebooks provide scalability and efficient codeword search capability, which are key features for practical multiuser MIMO-OFDM systems with a large number of antennas. The proposed clustered quantization scheme quantizes consecutive subcarriers into a single codeword that minimizes aggregated quantization errors. We base our new clustering techniques on two constellation based quantization methods, namely equal-magnitude angular quantization (EMAQ) and squared-lattice angular quantization. New efficient codebook search algorithms are proposed for the clustered quantization. In addition, we propose new constellations to guarantee different users quantize channels into distinct codewords. One is a rotated M-PSK constellation suitable for randomly-distributed user scenarios, and the other is a random phase equal-magnitude (RPEM) constellation suitable for ill-conditioned user scenarios. Thus, full spatial multiplexing gain can be achievable even with small number of users. Finally, a near-sphere codeword search algorithm is proposed for the RPEM. In simulations, the proposed clustered quantization shows up to 50% higher throughput compared to conventional fixed-pilot channel quantization. Also, we show our new constellations for EMAQ improve throughput almost 35% compared to the standard EMAQ. [ABSTRACT FROM PUBLISHER]

This paper considers joint linear processing at multi-antenna sources and one multiple-input multiple-output (MIMO) relay station for both one-way and two-way relay-assisted wireless communications. The one-way relaying is applicable in the scenario of downlink transmission by a multi-antenna base station to multiple single-antenna users with the help of one MIMO relay. In such a scenario, the objective of join linear processing is to maximize the information throughput to users. The design problem is equivalently formulated as the maximization of the worst signal-to-interference-plus-noise ratio (SINR) among all users subject to various transmission power constraints. Such a program of nonconvex objective minimization under nonconvex constraints is transformed to a canonical d.c. (difference of convex functions/sets) program of d.c. function optimization under convex constraints through nonconvex duality with zero duality gap. An efficient iterative algorithm is then applied to solve this canonical d.c program. For the scenario of using one MIMO relay to assist two sources exchanging their information in two-way relying manner, the joint linear processing aims at either minimizing the maximum mean square error (MSE) or maximizing the total information throughput of the two sources. By applying tractable optimization for the linear minimum MSE estimator and d.c. programming, an iterative algorithm is developed to solve these two optimization problems. Extensive simulation results demonstrate that the proposed methods substantially outperform previously-known joint optimization methods. [ABSTRACT FROM PUBLISHER]

In this paper, we analyze a multiple-input multiple-output (MIMO) interference channel where nodes are randomly distributed on a plane as a spatial Poisson cluster point process. A Poisson cluster point process consists of clusters with fixed number of points randomly distributed as with the cluster centers distributed randomly on the plane. The nodes in each cluster use interference alignment (IA) to suppress intra-cluster interference but unlike most work on IA, we do not neglect inter-cluster interference. We also connect the accuracy of channel state information to the distance between the nodes, i.e., the quality of CSI degrades with increasing distance. Accounting for the training and feedback overhead, we derive the transmission capacity of this MIMO IA ad hoc network and then compare it to open-loop (interference-blind) spatial multiplexing. Finally, we present exemplary system setups where spatial multiplexing outperforms IA due to the imperfect channel state information or the non-aligned inter-cluster interference. [ABSTRACT FROM PUBLISHER]

This paper investigates the linear precoder design for K-user interference channels of multiple-input multiple-output (MIMO) transceivers under finite alphabet inputs. We first obtain general explicit expressions of the achievable rate for users in the MIMO interference channel systems. We study optimal transmission strategies in both low and high signal-to-noise ratio (SNR) regions. Given finite alphabet inputs, we show that a simple power allocation design achieves optimal performance at high SNR whereas the well-known interference alignment technique for Gaussian inputs only utilizes a partial interference-free signal space for transmission and leads to a constant rate loss when applied naively to finite-alphabet inputs. Moreover, we establish necessary conditions for the linear precoder design to achieve weighted sum-rate maximization. We also present an efficient iterative algorithm for determining precoding matrices of all the users. Our numerical results demonstrate that the proposed iterative algorithm achieves considerably higher sum-rate under practical QAM inputs than other known methods. [ABSTRACT FROM AUTHOR]

In this paper, we start by investigating the impact of joint transmit-receive I/Q imbalance on the performance of direct-conversion beamforming OFDM transceivers. We derive a new analytical expression for the average subcarrier SINR of the I/Q imbalance-ignorant beamformer in terms of the I/Q imbalance level at both the transmit and receive sides, the size of the beamforming array, and the input SNR level. This expression motivates the need for I/Q imbalance compensation and provides valuable design insights when examining several special and limiting cases. Next, we derive the throughput-maximizing multiple beamforming transmit/receive coefficients under a general system model with an asymmetric frequency-dependent (FD) joint transmit-receive I/Q imbalance. In addition, we propose a low-complexity pilot-aided scheme for the estimation of the channel and I/Q imbalance parameters. Our simulation results demonstrate that the proposed generalized multiple beamforming scheme is highly effective in mitigating I/Q imbalance effects at practical complexity levels. [ABSTRACT FROM AUTHOR]