Non-orthogonal multiple access (NOMA), which has attracted a lot of attention recently due to its superior spectral efficiency, could play a vital role in improving the capacity of future networks. In this paper, a resource allocation scheme is developed for a downlink multi-user NOMA system. An optimization problem is formulated to maximize the sum rate under the total power and proportional rate constraints. Due to the complexity of computing the optimal solution, we develop a low complexity sub-optimal solution for a two-user scenario and then extend it to the multi-user case by proposing a user-pairing approach as well as a number of power allocation techniques that facilitate dealing with a large number of users in NOMA system. Simulation results support the effectiveness of the proposed approaches and show the close performance to the optimal one. In addition, we propose a new hybrid multiple access technique that combines the properties of NOMA and the orthogonal frequency division multiple access. Simulation results show that the proposed hybrid method provides better performance than NOMA in terms of the overall achievable sum rate and the coverage probability.

Non-orthogonal multiple access (NOMA) is a promising multiple access scheme for next generation wireless networks. This paper investigates the sum rate maximization problem for NOMA system over a frequency selective fading channel with its users being paired according to their channel powers. A hierarchical power allocation process is proposed, whereby the users are divided into two groups such that a closed form power allocation solution can be applied. This divide-and allocate approach is repeated until all users are allocated with a transmission power. The proposed architecture facilitates a large number of users for NOMA system. Simulation results show that the proposed scheme achieves comparable performances to the optimal one based on numerical solution, and outperforms other approaches.

Non-orthogonal multiple access (NOMA) can increase the spectral efficiency and could play an important role in improving the capacity of 5G networks. In this paper, an optimization problem is formulated to maximize the overall sum rate in a sub-carrier based NOMA system. The optimal transmission power of each user is obtained based on the users' instantaneous channel state information under the total power and the minimum rate constraints. Moreover, two closed-form suboptimal solutions are also proposed for a two-user scenario to reduce the complexity of the optimal solution. The suboptimal approaches are also extended to multiuser scenario by pairing users for subbands transmission. Simulation results show that the derived sub-optimal solutions provide better performance than the orthogonal frequency division multiple access (OFDMA) in terms of coverage probability and sum rate. Moreover, the results show that the proposed sub-optimal solutions achieve a comparable results to the optimal one with lower complexity.

Non-orthogonal multiple access (NOMA) has attracted a lot of attention recently due to its superior spectral efficiency and could play a vital role in improving the capacity of future networks. This paper considers resource allocation for a downlink, multi-user (MU) MIMO-NOMA system that aims at maximizing the sum rate with interference alignment (IA) technique. Using singular decomposition value (SVD) based IA, we propose IA based NOMA system in which a number of users are grouped together while the others are aligned to the null space as interference. The targeted group of users employ NOMA with a low complexity hierarchical power allocation scheme for sum rate maximization. In addition, an optimization problem is formulated to maximize the sum rate under the total power and proportional fairness constraints. A low complexity sub-optimal solution for two-user scenario is obtained and then extended to the multi-user case by a hierarchical pairing scheme. Another approach is proposed to allocate the transmission power of each user using an iterative subgradient method. Simulation results show that the proposed schemes provide better performance than an existing scheme and perform close to the optimal one. In addition, the simulation scenario considers the case where two users share the data streams while performing IA as compared to the case where all users are sharing it without IA. Simulation results verify that applying IA with NOMA could improve the achievable sum rate and offers simplicity in terms of successive interference cancellation (SIC) application.

Non-orthogonal multiple access (NOMA) is increasingly becoming very attractive in cloud radio access networks (CRANs) to further boost the overall spectral efficiency, connectivity and, capacity of such networks. This paper addresses optimizing the energy efficiency (EE) for the downlink of a NOMA-based two tiers CRAN. The stochastic geometry represented by Poisson Point Process (PPP) distribution is used to decide the number and locations of the base stations (BSs) in each tier within the coverage area. A numerical optimal solution is obtained and compared against a proposed subgradient solution, as well as another proposed unoptimized solution based on the false positioning method. For comparison purposes, two other power allocation techniques are presented to allocate different powers to various BS categories; one allocates the power to each BS based on their relative distances to the cloud-based central station and the other is the bisection based scheme. Two simulation scenarios are presented to examine the performance of the two-tier NOMA-CRANs with NOMA is adopted as the multiple access of each tier in both cases. The first scenario considers heterogeneous CRAN (NOMA-HCRAN) case by using two different BS categories in each tier, namely, the macro-BSs and the RRHs. The second scenario considers a homogeneous CRAN (NOMA-CRAN) case by using the RRHs in both tiers but each tier has different frequency layer to prevent cross tier interference. Simulation results show the promising performance gain can be achieved with the proposed techniques relative to the existing approaches. More specifically, it was illustrated that the proposed subgradient based NOMA CRAN offers better performance than the proposed false positioning based NOMA CRAN, which is in turn better than the existing techniques, in particular, the bisection and the distance based NOMA-CRAN.