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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]

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]

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]

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]

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]

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]

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 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]

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]

Interference alignment (IA) is known to significantly increase sum-throughput at high SNR in the presence of multiple interfering nodes, however, the reliability of IA is little known, which is the subject of this paper. We study the error performance of IA and compare it with conventional orthogonal transmission schemes. Since most IA algorithms require extensive channel state information (CSI), we also investigate the impact of CSI imperfection (uncertainty) on the error performance. Our results show that under identical rates, IA attains a better error performance than the orthogonal scheme for practical signal to noise ratio (SNR) values but is more sensitive to CSI uncertainty. We design bit loading algorithms that significantly improve error performance of the existing IA schemes. Furthermore, we propose an adaptive transmission scheme that not only considerably reduces error probability, but also produces robustness to CSI uncertainty. [ABSTRACT FROM PUBLISHER]

Recent works on multiuser MIMO study have shown that the linear growth of capacity in single user MIMO system can be translated to the multiuser MIMO scenario as well. In this paper, we propose a method pursuing performance gain of vector perturbation in multiuser downlink systems. Instead of employing the maximum number of mobile users for communication, we use small part of them as virtual users for improving reliability of users participating communication. By controlling parameters of the virtual users including information and perturbation vector, we obtain considerable improvement in the effective SNR. Simulation results on the realistic multiuser MISO and MIMO downlink systems show that the proposed method brings substantial performance gain over the standard vector perturbation with marginal overhead in computations. [ABSTRACT FROM AUTHOR]

In this paper, we consider a secrecy relaying communication scenario where all nodes are equipped with multiple antennas. An eavesdropper has the access to the global channel state information (CSI), and all the other nodes only know the CSI not associated with the eavesdropper. A new secrecy transmission protocol is proposed, where the concept of interference alignment is combined with cooperative jamming to ensure that artificial noise from transmitters can be aligned at the destination, but not at the eavesdropper due to the randomness of wireless channels. Analytical results, such as ergodic secrecy rate and outage probability, are developed, from which more insightful understanding of the proposed protocol, such as multiplexing and diversity gains, can be obtained. A few special cases, where outage probability cannot be decreased to zero regardless of SNR, are also discussed. Simulation results are provided to demonstrate the performance of the proposed secrecy transmission protocol. [ABSTRACT FROM AUTHOR]

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLS of the precoder using large-system analysis. We show that the RCI precoder with αLS outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α and the power allocation vector. The jointly optimized precoder outperforms RCI with αLS and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas. [ABSTRACT FROM AUTHOR]

In a cellular-like system, the multiple-input multiple-output (MIMO) mode used by a base station (BS) can be adaptively varied among several candidate MIMO modes, including space-time block coding (STBC), open-loop spatial multiplexing (OLSM), closed-loop spatial multiplexing (CLSM), MIMO beamforming (MBF), and maximal ratio transmission (MRT). In practice, during any one given period of time, when the desired BS performs downlink transmission with a specific MIMO mode, each co-channel interfering BS will use a MIMO mode the same as or different from that used in the desired link and any two co-channel interfering BSs may use different MIMO modes, so that the interference scenario becomes quite complicated. In this paper, considering realistic propagation conditions including both path-loss and Rayleigh fading and considering the existence of unequal-power interferers, the statistical distributions of the post-processing signal-to-interference ratios (SIRs) for either MBF or STBC downlink transmissions are analyzed when co-channel interfering BSs employ arbitrary MIMO modes. In particular, closed-form expressions for the probability density function (PDF) of the interference terms in the post-processing SIRs are derived. Further, the statistical distributions of the post-processing SIRs are analyzed. Simulation results verify the validity of the theoretical analyses. [ABSTRACT FROM PUBLISHER]

For multi-user interference channels (IC), an altruistic approach based on the zero-forcing (ZF) criterion shows the near-optimal performance at high signal-to-noise ratio (SNR), whereas its performance at low SNR becomes poor compared to a simple egoistic algorithm (selfish beamforming). Thus, balancing between the egoism and the altruism has been an important issue to achieve good sum-rate performance at overall SNR regime. In this paper, we propose a new approach for enhancing the performance by regularizing the ZF based transceivers. To this end, we start with investigating efficient ZF transceivers for 2-user and 3-user ICs. First, coordinated spatial multiplexing (CSM) is proposed for 2-user IC. For the 3-user case, it is shown that the enhanced interference alignment (E-IA) introduced in our previous work is the optimal ZF transceivers in terms of the sum-rate performance. Next, to improve the performance of the CSM and E-IA schemes at low SNR, we propose a non-iterative regularization method under the high SNR approximation. The distributed implementation of the proposed regularization method is also presented where each node is able to compute its own precoding or decoding matrix using local channel state information. From simulations, it is observed that the proposed regularized design outperforms the conventional schemes in overall SNR regime. Also, we confirm that our distributed approach provides a substantial performance gain over the conventional distributed scheme with reduced computational complexity. [ABSTRACT FROM PUBLISHER]

The signal to interference plus noise ratio (SINR) feedback has been utilized in random beamforming (RBF) to select users for multiple-input multiple-output (MIMO) systems where a large number of users are required to obtain a multi-user diversity gain. However, if the number of users is not large enough, it may be difficult to obtain the performance gain and be easy to have a performance degradation conversely. To resolve this problem, it is necessary to find orthogonal random beams close to the channel matrix of selected users. In this paper, we present RBF using a non-orthogonal beamforming matrix (RBF NOBM), demonstrating an efficient search of random beams correlated with the channel matrix of selected users over a small number of users. For single user RBF using NOBM (SU-RBF NOBM) with two transmit antennas, the beamforming matrix for user data service is obtained through closed form expressions, and SU-RBF NOBM is then expanded to more than two transmit antennas. We also propose user selection algorithms for SU-RBF NOBM and multi-user RBF using NOBM (MU-RBF NOBM). Via simulation results, we demonstrate that the performances of RBF NOBM represent significant improvements compared to conventional beamforming schemes. [ABSTRACT FROM PUBLISHER]

This paper considers multiple-antenna broadcast channels (BCs) with multi-dimensional space-time modulation schemes, created by various allocations of signal dimensions to transmit antennas. The signal dimensions are divided into disjoint subsets, where one is shared between all users, and each of the others are assigned to different users. This model encompasses several practical single point to multi-point wireless communication systems employing multiple antennas. Assuming space and time dispersive channels, we consider the transmission rates that are achieved by applying dirty paper coding (DPC) at the transmitter, present inner and outer bounds for the DPC rate region, and study the effects of space-time modulation formats. At high SNR, we consider the limit form of these bounds, derive an achievable multiplexing gain region, and study the effects of sharing signal dimensions between users. [ABSTRACT FROM PUBLISHER]

In downlink multiuser multiple-input multiple-output (MIMO) systems, system performance highly depends on the reliability of downlink channel state information (CSI) at the base station (BS). In frequency division duplexing, the most practical solution is to have downlink CSI from the users fed back to the BS. Most work on this feedback design has assumed independent block fading channels. However, this paper proposes a new differential feedback scheme using the observation that the channel realizations are usually temporally correlated. The sum-rate loss assuming differential feedback is analyzed for a system with the number of users K equal to the number of transmit antennas M. When K > M, a user selection algorithm based on an approximated signal-to-interference plus noise ratio (SINR) estimation is proposed. In simulation results, the proposed differential feedback scheme increases the sum-rate compared to previous differential feedback schemes. Moreover, the proposed user selection algorithm outperforms semi-orthogonal user selection in the moderate signal-to-noise ratio (SNR) region, despite requiring less feedback information. In low mobility channels, utilizing the channels' time correlation during quantization is shown to play a bigger role in determining sum-rate performance than multiuser diversity for most SNR regimes when a practical number of users is considered. [ABSTRACT FROM AUTHOR]