Joint interference alignment and power allocation for NOMA-based multi-user MIMO systems

Abstract

Interference alignment (IA) and non-orthogonal multiple access (NOMA) are key technologies for achieving the capacity scaling required by next generation networks to overcome the unprecedented growth of data network traffic. Each of these technologies was proved to present excellent performance for MIMO systems. In this article, we propose a joint IA and power allocation (PA) framework for NOMA-based multiuser MIMO (MU-MIMO) systems. Different approaches for applying IA in downlink NOMA-based MU-MIMO systems will be addressed while implementing a PA technique that fully exploits the characteristics of NOMA-based systems. The proposed framework aims to maximize the sum-rate of the NOMA-based MU-MIMO system through combining IA with PA. The process begins by initially grouping the system users into clusters for optimum implementation of NOMA. The sum-rate maximization is carried out under cluster power budget, user quality-of-service (QoS), and robust successive interference cancellation (SIC) constraints. Meanwhile, it uses the power domain multiplexing strategy to allow the users within each cluster to share the data streams without exerting interference to one another. Three iterative joint IA and PA algorithms are proposed for NOMA-based MU-MIMO systems. Moreover, these algorithms are compared with orthogonal multiple access (OMA)-based MU-MIMO counterpart as well as the state-of-the-art techniques presented for NOMA-based MU-MIMO systems. Numerical simulations verify that the proposed framework can greatly improve the performance of NOMA-based MU-MIMO systems in terms of the achievable sum-rate when compared with OMA-based MU-MIMO and the state-of-the-art NOMA-based MU-MIMO systems.

Symbol Detection Based on Back Tracking Search Algorithm in MIMO-NOMA Systems

“…For this scheme, each user uses the same time and frequency where they are selected considering the power levels. In NOMA, the successive interference cancellation (SIC) is used to reserve the users both in the downlink and uplink [1][2][3][4][5][6][7].…”

“…( 6) received signal is a combination of desired and interference signal [2][3]. Interference signals consist of two parts called intra-cluster interference and inter-cluster interference [4]…”

“…One of the most important ways to deal with these destructive effects is to use a multi-antenna transceiver. By using NOMA combined with multiple antenna structures, not only high-rate data transmission is provided but also the destructive effects caused by fading are minimized [2][3][4][5][6][7]. However, symbol detection is a crucial process to detect symbols coherently in wireless communication systems [8][9][10][11][12][13][14][15][16][17][18][19][20][21].…”

5G Technology: Towards Dynamic Spectrum Sharing Using Cognitive Radio Networks

“…The authors also presented the challenges in implementing a massive number of IoT devices in 5G cellular networks, such as BS and traffic estimation, channel estimation, interference management, power allocation and management of device synchronisation. For NOMA-based multi-user MIMO, [41] presented a joint interference alignment with the power allocation framework to overcome the immense increase in traffic in the data network. The framework utilises the sum rate to provide QoS and guarantee an effective SIC constraint whilst managing the power to reduce interference within a cluster.…”

An Overview of Key Technologies in Physical Layer Security

“…The concept of the IA technique is that the transmitted signals are directed to concentrate the interference in the particular sub-spaces at the unintended receivers, thus opening up interference-free sub-spaces to transmit the desired signal to the intended user. Following the proposal, several research works in [ 64 , 67 , 68 , 69 ] have been conducted to develop IA algorithms for directing the interference in a manner that is detrimental to the illegitimate receiver while ensuring that the legitimate receiver is not severely affected. To enhance the desired signal gain and suppress the undesired interference and the noise signal, authors in [ 63 ] employed spatial degrees of freedom.…”