Mohammed Al-Imari

On Receiver Design for Uplink Low Density Signature OFDM (LDS-OFDM)

Low density signature orthogonal frequency division multiplexing (LDS-OFDM) is an uplink multi-carrier multiple access scheme that uses low density signatures (LDS) for spreading the symbols in the frequency domain. In this paper, we introduce an effective receiver for the LDS-OFDM scheme. We propose a framework to analyze and design this iterative receiver using extrinsic information transfer (EXIT) charts. Furthermore, a turbo multi-user detector/decoder (MUDD) is proposed for the LDS-OFDM receiver. We show how the turbo MUDD is tuned using EXIT charts analysis. By tuning the turbo-style processing, the turbo MUDD can approach the performance of optimum MUDD with a smaller number of inner iterations. Using the suggested design guidelines in this paper, we show that the proposed structure brings about 2.3 dB performance improvement at a bit error rate (BER) equal to 10-5 over conventional LDS-OFDM while keeping the complexity affordable. Simulations for different scenarios also show that the LDS-OFDM outperforms similar well-known multiple access techniques such as multi-carrier code division multiple access (MC-CDMA) and group-orthogonal MC-CDMA.

Low complexity subcarrier and power allocation algorithm for uplink OFDMA systems

In this article, we consider the joint subcarrier and power allocation problem for uplink orthogonal frequency division multiple access system with the objective of weighted sum-rate maximization. Since the resource allocation problem is not convex due to the discrete nature of subcarrier allocation, the complexity of finding the optimal solution is extremely high. We use the optimality conditions for this problem to propose a suboptimal allocation algorithm. A simplified implementation of the proposed algorithm has been provided, which significantly reduced the algorithm complexity. Numerical results show that the presented algorithm outperforms the existing algorithms and achieves performance very close to the optimal solution.

Game Theory Based Radio Resource Allocation for Full-Duplex Systems

Full-duplex transceivers enable transmission and reception at the same time on the same frequency, and have the potential to double the wireless system spectral efficiency. Recent studies have shown the feasibility of full-duplex transceivers. In this paper, we address the radio resource allocation problem for full-duplex system. Due to the self-interference and inter-user interference, the problem is coupled between uplink and downlink channels, and can be formulated as joint uplink and downlink sum-rate maximization. As the problem is non-convex, an iterative algorithm is proposed based on game theory by modelling the problem as a noncooperative game between the uplink and downlink channels. The algorithm iteratively carries out optimal uplink and downlink resource allocation until a Nash equilibrium is achieved. Simulation results show that the algorithm achieves fast convergence, and can significantly improve the full-duplex performance comparing to the equal resource allocation approach. Furthermore, the full-duplex system with the proposed algorithm can achieve considerable gains in spectral efficiency, that reach up to 40%, comparing to half-duplex system.

Performance evaluation of Low Density Spreading Multiple Access

In this paper, we evaluate the performance of Multicarrier-Low Density Spreading Multiple Access (MC-LDSMA) as a multiple access technique for mobile communication systems. The MC-LDSMA technique is compared with current multiple access techniques, OFDMA and SC-FDMA. The performance is evaluated in terms of cubic metric, block error rate, spectral efficiency and fairness. The aim is to investigate the expected gains of using MC-LDSMA in the uplink for next generation cellular systems. The simulation results of the link and system-level performance evaluation show that MC-LDSMA has significant performance improvements over SC-FDMA and OFDMA. It is shown that using MC-LDSMA can considerably reduce the required transmission power and increase the spectral efficiency and fairness among the users.

Radio Resource Allocation for Uplink OFDMA Systems With Finite Symbol Alphabet Inputs

In this paper, we consider the radio resource allocation problem for uplink orthogonal frequency-division multiple-access (OFDMA) systems. The existing algorithms have been derived under the assumption of Gaussian inputs due to its closed-form expression of mutual information. For the sake of practicality, we consider the system with finite symbol alphabet (FSA) inputs and solve the problem by capitalizing on the recently revealed relationship between mutual information and minimum mean square error (MMSE). We first relax the problem to formulate it as a convex optimization problem, and then, we derive the optimal solution via decomposition methods. The optimal solution serves as an upper bound on the system performance. Due to the complexity of the optimal solution, a low-complexity suboptimal algorithm is proposed. Numerical results show that the presented suboptimal algorithm can achieve performance very close to the optimal solution and that it outperforms the existing suboptimal algorithms. Furthermore, using our proposed algorithm, significant power saving can be achieved in comparison to the case when a Gaussian input is assumed.

Optimal power allocation for MIMO-OFDM based Cognitive Radio systems with arbitrary input distributions

In Cognitive Radio (CR) systems, the data rate of the Secondary User (SU) can be maximized by optimizing the transmit power, given a threshold for the interference caused to the Primary User (PU). In conventional power optimization algorithms, the Gaussian input distribution is assumed, which is unrealistic, whereas the Finite Symbol Alphabet (FSA) input distribution, (i.e., M-QAM) is more applicable to practical systems. In this paper, we consider the power optimization problem in multiple input multiple output orthogonal frequency division multiplexing based CR systems given FSA inputs, and derive an optimal power allocation scheme by capitalizing on the relationship between mutual information and minimum mean square error. The proposed scheme is shown to save transmit power compared to its conventional counterpart. Furthermore, our proposed scheme achieves higher data rate compared to the Gaussian optimized power due to fewer number of subcarriers being nulled. The proposed optimal power algorithm is evaluated and compared with the conventional power allocation algorithms using Monte Carlo simulations. Numerical results reveal that, for distances between the SU transmitter and the PU receiver ranging between 50m to 85m, the transmit power saving with the proposed algorithm is in the range 13-90%, whereas the rate gain is in the range 5-31% depending on the modulation scheme (i.e., BPSK, QPSK and 16-QAM) used.

Low Density Spreading for next generation multicarrier cellular systems

Multicarrier-Low Density Spreading Multiple Access (MC-LDSMA) is a promising technique for high data rate mobile communications. In this paper, the suitability of using MC-LDSMA in the uplink for next generation cellular systems is investigated. The performance of MC-LDSMA is evaluated and compared with current multiple access techniques, OFDMA and SC-FDMA. Specifically, Peak to Average Power Ratio (PAPR), Bit Error Rate (BER), spectral efficiency and fairness are considered as performance metrics. The link and system-level simulation results show that MC-LDSMA has significant performance improvements over SC-FDMA and OFDMA. It is shown that using MC-LDSMA can significantly improve the system performance in terms of required transmission power, spectral efficiency and fairness among the users.

Subcarrier and Power Allocation for LDS-OFDM System

Low Density Signature-Orthogonal Frequency Division Multiplexing (LDS-OFDM) has been introduced recently as an efficient multiple access technique. In this paper, we focus on the subcarrier and power allocation scheme for uplink LDS-OFDM system. Since the resource allocation problem is not convex due to the discrete nature of subcarrier allocation, the complexity of finding the optimal solutions is extremely high. We propose a heuristic subcarrier and power allocation algorithm to maximize the weighted sum-rate. The simulation results show that the proposed algorithm can significantly increase the spectral efficiency of the system. Furthermore, it is shown that LDS-OFDM system can achieve an outage probability much less than that for OFDMA system.

Radio resource allocation for full-duplex multicarrier wireless systems

Full-duplex technology has the potential to double the wireless system spectral efficiency by enabling simultaneous transmission and reception at the same time on the same frequency. In this paper, we address the subcarrier and power allocation problem for full-duplex system. The problem is coupled between uplink and downlink channels due to the self-interference and inter-user interference. As the problem is non-convex, a suboptimal algorithm is proposed based on the Frank-Wolfe approach. To this end, a subcarrier and power allocation is first performed for the downlink channel, and then the uplink resource allocation is represented as a D.C. (difference of two convex functions) problem. An approximation is used to convert the D.C. problem into two convex sub-problems, which are solved iteratively to produce a lower bound approximation for the non-convex objective. Simulation results show that the algorithm achieves fast convergence regardless of different initialization points, and can significantly improve the full-duplex performance comparing to the equal resource allocation approach. Furthermore, the full-duplex system with the proposed algorithm can achieve significant gains in spectral efficiency, that reach up to 48%, comparing to half-duplex system.

Radio resource allocation and system-level evaluation for full-duplex systems

Recent studies have shown the feasibility of full-duplex transceivers, which have the potential to double the system spectral efficiency by allowing transmission and reception at the same time on the same frequency. In this paper, we consider the radio resource allocation problem for full-duplex systems that jointly maximize the uplink and downlink sum-rate. The problem is coupled between uplink and downlink channels due to the self-interference. An iterative algorithm is proposed based on game theory by modelling the problem as a non-cooperative game between the uplink and downlink channels. The algorithm iteratively carries out optimal uplink and downlink resource allocation until a Nash equilibrium is achieved. Simulation results show that the algorithm can significantly improve the full-duplex performance comparing to the equal resource allocation approach. Furthermore, the full-duplex system performance is evaluated under different system settings, and it is shown that the superiority of the full-duplex technique over half-duplex is more prominent in cells with lower transmission power and smaller coverage area.