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In this paper, orthogonal frequency-division multiple-access (OFDMA) systems with dynamic deterministic (as opposed to pseudorandom) allocation of subcarriers to users to exploit multiuser diversity are investigated. Previously published work on dynamic multiuser subcarrrier allocation for OFDMA systems with single-input--single-output (SISO) channels are surveyed. A near-optimal low-complexity algorithm tier SISO systems, which is structurally similar to the algorithm by Rhee and Cioffi, is extended to the case of multiple-input--multiple-output (MIMO) systems in this paper. The optimality and adaptability of this algorithm are analyzed by formulating an assignment problem and comparing with one optimal and two extended suboptimal strategies proposed based on previous work. Consideration of a MIMO channel creates further issues for the subcarrier-allocation process. In particular, methods whereby an appropriate subcarrier allocation may be exploited to minimize the effects of correlation in MIMO channels are of considerable interest. Several novel variants of the algorithm (referred to as 'schemes') are proposed and evaluated for MIMO systems employing both space-time block coding (STBC) and spatial multiplexing (SM) in both uncorrelated and correlated fading channels. Simulation results identify the most suitable schemes for both STBC and SM and, in particular, show that substantial improvements in performance tin terms of bit-error rate) in correlated channels can be achieved by means of suitable subcarrier allocation. In uncorrelated channels, the best scheme can tilter approximately 7-dB gain over the conventional MIMO channel; in highly correlated channels, even more substantial improvements (> 11-dB gain for STBC, > 20-dB gain for SM) in performance can also he achieved, demonstrating the ability of a well-designed subcarrier-allocation scheme to mitigate the debilitating effects of correlation on MIMO systems. Index Terms--Multiple input multiple output (MIMO), orthogonal frequency-division multiple access (OFDMA), single input single output (SISO), space-time block coding (STBC), spatial multiplexing (SM), subcarrier allocation.

The growing demand for high-speed data, quality of service (QoS) assurance, and energy efficiency has triggered the evolution of fourth-generation (4G) Long-Term Evolution-Advanced (LTE-A) networks to fifth generation (5G) and beyond. Interference is still a major performance bottleneck. This paper studies the application of physical-layer network coding (PNC), which is a technique that exploits interference, in heterogeneous cellular networks. In particular, we propose a rate-maximizing relay selection algorithm for a single cell with multiple relays assuming the decode-and-forward (DF) strategy. With nodes transmitting at different powers, the proposed algorithm adapts the resource allocation according to the differing link rates, and we prove theoretically that the optimization problem is log-concave. The proposed technique is shown to perform significantly better than the widely studied selection-cooperation technique. We then undertake an experimental study—on a software radio platform—of the decoding performance of PNC with unbalanced signal-to-noise ratios (SNRs) in the multiple-access transmissions. This problem is inherent in cellular networks, and it is shown that, with channel coding and decoders based on multiuser detection and successive interference cancellation, the performance is better with power imbalance. This paper paves the way for further research on multicell PNC, resource allocation, and the implementation of PNC with higher order modulations and advanced coding techniques. [ABSTRACT FROM PUBLISHER]

This paper proposes a linear transmit filter design to maximize weighted sum capacity (WSC) in multiuser multiple-input–multiple-output (MU-MIMO) systems. The proposed scheme is based on a modified signal-to-leakage-plus-noise ratio (SLNR) criterion, which integrates receiver structures and power allocations into the precoder design and can efficiently exploit unused receiver subspaces. Based on the proposed transmitter (TX) design with receive matched filters (MFs), the WSC maximization problem can be simplified to power-allocation and data-stream selection problems. A power-allocation algorithm for finding a local optimal solution is also proposed and is shown to be obtained by the iteration of closed-form water-filling (WF) solutions. Furthermore, a low-complexity user and substream selection is proposed as an alternative solution to maximize WSC. Simulation results show that the proposed algorithms outperform the conventional scheme and achieve comparable performance to a joint transceiver design, despite requiring simpler receiver structures. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of efficiently allocating wireless resources to support multiple scalable video sequences over a downlink cognitive radio network is addressed. We consider the coarse grain scalable (CGS) and medium grain scalable (MGS) extension of the H.264 standard as the encoding method and propose to perform a per-subcarrier transmit antenna selection such that spatial diversity is exploited. We formulate the problem of optimally allocating subcarriers and antennas among secondary users as a binary integer program, where optimality is defined in terms of the aggregate visual quality of received video sequences of all cognitive users. The proposed formulation caters to the staircase rate-distortion characteristics of CGS/MGS sequences and avoids allocating more resources than are necessary to attain a given visual quality. However, due to the high computational complexity involved in solving this hard integer program using discrete programming solvers, we reduce the resource allocation problem to a subset-sum problem. Although it remains \cal NP -hard in general, we present two efficient methods to solve this subset-sum problem based on its structure. Simulation results demonstrate that the methods proposed lead to a solution that is close to the optimal. Moreover, we demonstrate that having multiple antennas at the cognitive base station reduces the outage probability of secondary users. [ABSTRACT FROM PUBLISHER]

In this paper, orthogonal frequency-division multiple-access (OFDMA) systems with dynamic deterministic (as opposed to pseudorandom) allocation of subcarriers to users to exploit multiuser diversity are investigated. Previously published work on dynamic multiuser subcarrrier allocation for OFDMA systems with single-input-single-output (SISO) channels are surveyed. A near-optimal low-complexity algorithm for SISO systems, which is structurally similar to the algorithm by Rhee and Cioffi, is extended to the case of multiple-input-multiple-output (MIMO) systems in this paper. The optimality and adaptability of this algorithm are analyzed by formulating an assignment problem and comparing with one optimal and two extended suboptimal strategies proposed based on previous work. Consideration of a MIMO channel creates further issues for the subcarrier-allocation process. In particular, methods whereby an appropriate subcarrier allocation may be exploited to minimize the effects of correlation in MIMO channels are of considerable interest. Several novel variants of the algorithm (referred to as "schemes") are proposed and evaluated for MIMO systems employing both space-time block coding (STBC) and spatial multiplexing (SM) in both uncorrelated and correlated fading channels. Simulation results identify the most suitable schemes for both STBC and SM and, in particular, show that substantial improvements in performance (in terms of bit-error rate) in correlated channels can be achieved by means of suitable subcarrier allocation. In uncorrelated channels, the best scheme can offer approximately 7-dB gain over the conventional MIMO channel; in highly correlated channels, even more substantial improvements (> 11-dB gain for STBC, > 20-dB gain for SM) in performance can also be achieved, demonstrating the ability of a well-designed subcarrier-allocation scheme to mitigate the debilitating effects of correlation on MIMO systems. [ABSTRACT FROM AUTHOR]