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

Distributed power allocation for D2D communications underlaying/overlaying OFDMA cellular networks

The implementation of device-to-device (D2D) underlaying or overlaying pre-existing cellular networks has received much attention due to the potential of enhancing the total cell throughput, reducing power consumption and increasing the instantaneous data rate. In this paper we propose a distributed power allocation scheme for D2D OFDMA communications and, in particular, we consider the two operating modes amenable to a distributed implementation: dedicated and reuse modes. The proposed schemes address the problem of maximizing the users' sum rate subject to power constraints, which is known to be nonconvex and, as such, extremely difficult to be solved exactly. We propose here a fresh approach to this well-known problem, capitalizing on the fact that the power allocation problem can be modeled as a potential game. Exploiting the potential games property of converging under better response dynamics, we propose two fully distributed iterative algorithms, one for each operation mode considered, where each user updates sequentially and autonomously its power allocation. Numerical results, computed for several different user scenarios, show that the proposed methods, which converge to one of the local maxima of the objective function, exhibit performance close to the maximum achievable optimum and outperform other schemes presented in the literature

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

Adaptive Resource Allocation Based on Factor Graphs in Non-Orthogonal Multiple Access

In this paper, we propose a non-orthogonal multiple access with adaptive resource allocation. The proposed non-orthogonal multiple access assigns multiple frequency resources for each device to send packets. Even if the number of devices is more than that of the available frequency resources, the proposed non-orthogonal access allows all the devices to transmit their packets simultaneously for high capacity massive machine-type communications (mMTC). Furthermore, this paper proposes adaptive resource allocation algorithms based on factor graphs that adaptively allocate the frequency resources to the devices for improvement of the transmission performances. This paper proposes two allocation algorithms for the proposed non-orthogonal multiple access. This paper shows that the proposed non-orthogonal multiple access achieves superior transmission performance when the number of the devices is 50% greater than the amount of the resource, i.e., the overloading ratio of 1.5, even without the adaptive resource allocation. The adaptive resource allocation enables the proposed non-orthogonal access to attain a gain of about 5dB at the BER of 10-4