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

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

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

Radio resource allocation for multicarrier-low density spreading multiple access

Multicarrier-low density spreading multiple access (MC-LDSMA) is a promising multiple access technique that enables near optimum multiuser detection. In MC-LDSMA, each user’s symbol spread on a small set of subcarriers, and each subcarrier is shared by multiple users. The unique structure of MC-LDSMA makes the radio resource allocation more challenging comparing to some well-known multiple access techniques. In this paper, we study the radio resource allocation for single-cell MC-LDSMA system. Firstly, we consider the single-user case, and derive the optimal power allocation and subcarriers partitioning schemes. Then, by capitalizing on the optimal power allocation of the Gaussian multiple access channel, we provide an optimal solution for MC-LDSMA that maximizes the users’ weighted sum-rate under relaxed constraints. Due to the prohibitive complexity of the optimal solution, suboptimal algorithms are proposed based on the guidelines inferred by the optimal solution. The performance of the proposed algorithms and the effect of subcarrier loading and spreading are evaluated through Monte Carlo simulations. Numerical results show that the proposed algorithms significantly outperform conventional static resource allocation, and MC-LDSMA can improve the system performance in terms of spectral efficiency and fairness in comparison with OFDMA

Power and Channel Allocation for Non-orthogonal Multiple Access in 5G Systems: Tractability and Computation

Network capacity calls for significant increase for 5G cellular systems. A promising multi-user access scheme, non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC), is currently under consideration. In NOMA, spectrum efficiency is improved by allowing more than one user to simultaneously access the same frequency-time resource and separating multi-user signals by SIC at the receiver. These render resource allocation and optimization in NOMA different from orthogonal multiple access in 4G. In this paper, we provide theoretical insights and algorithmic solutions to jointly optimize power and channel allocation in NOMA. For utility maximization, we mathematically formulate NOMA resource allocation problems. We characterize and analyze the problems' tractability under a range of constraints and utility functions. For tractable cases, we provide polynomial-time solutions for global optimality. For intractable cases, we prove the NP-hardness and propose an algorithmic framework combining Lagrangian duality and dynamic programming (LDDP) to deliver near-optimal solutions. To gauge the performance of the obtained solutions, we also provide optimality bounds on the global optimum. Numerical results demonstrate that the proposed algorithmic solution can significantly improve the system performance in both throughput and fairness over orthogonal multiple access as well as over a previous NOMA resource allocation scheme.Comment: IEEE Transactions on Wireless Communications, revisio

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

A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning

In this tutorial paper, a comprehensive survey is given on several major systematic approaches in dealing with delay-aware control problems, namely the equivalent rate constraint approach, the Lyapunov stability drift approach and the approximate Markov Decision Process (MDP) approach using stochastic learning. These approaches essentially embrace most of the existing literature regarding delay-aware resource control in wireless systems. They have their relative pros and cons in terms of performance, complexity and implementation issues. For each of the approaches, the problem setup, the general solution and the design methodology are discussed. Applications of these approaches to delay-aware resource allocation are illustrated with examples in single-hop wireless networks. Furthermore, recent results regarding delay-aware multi-hop routing designs in general multi-hop networks are elaborated. Finally, the delay performance of the various approaches are compared through simulations using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201

Optimal Joint Subcarrier and Power Allocation in NOMA is Strongly NP-Hard

International audienceNon-orthogonal multiple access (NOMA) is a promising radio access technology for 5G. It allows several users to transmit on the same frequency and time resource by performing power-domain multiplexing. At the receiver side, successive interference cancellation (SIC) is applied to mitigate interference among the multiplexed signals. In this way, NOMA can outperform orthogonal multiple access schemes used in conventional cellular networks in terms of spectral efficiency and allows more simultaneous users. This paper investigates the computational complexity of joint subcarrier and power allocation problems in multi-carrier NOMA systems. We prove that these problems are strongly NP-hard for a large class of objective functions, namely the weighted generalized means of the individual data rates. This class covers the popular weighted sum-rate, proportional fairness, harmonic mean and max-min fairness utilities. Our results show that the optimal power and subcarrier allocation cannot be computed in polynomial time in the general case, unless P = NP. Nevertheless, we present some tractable special cases and we show that they can be solved efficiently