Joint Beam-Forming, User Clustering and Power Allocation for MIMO-NOMA Systems

Abstract

In this paper, we consider the optimal resource allocation problem for multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems, which consists of beam-forming, user clustering and power allocation, respectively. Users can be divided into different clusters, and the users in the same cluster are served by the same beam vector. Inter-cluster orthogonality can be guaranteed based on multi-user detection (MUD). In this paper, we propose a three-step framework to solve the multi-dimensional resource allocation problem. In step 1, we propose a beam-forming algorithm for a given user cluster. Specifically, fractional transmitting power control (FTPC) is applied for intra-cluster power allocation. The considered beam-forming problem can be transformed into a non-constrained one and the limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) method is applied to obtain the optimal solution. In step 2, optimal user clustering is further considered. Channel differences and correlations are both involved in the design of user clustering. By assigning different weights to the two factors, we can produce multiple candidate clustering schemes. Based on the proposed beam-forming algorithm, beam-forming can be done for each candidate clustering scheme to compare their performances. Moreover, based on the optimal user clustering and beam-forming schemes, in step 3, power allocation can be further optimized. Specifically, it can be formalized as a difference of convex (DC) programming problem, which is solved by successive convex approximation (SCA) with strong robustness. Simulations results show that the proposed scheme can effectively improve spectral efficiency (SE) and edge users’ data rates.

Power Allocation in NOMA-CR for 5G Enabled IoT Networks

“…As can be seen from Fig. 11, the spectral efficiency of the proposed algorithms is better than reference [31] algorithm for every user which indicates that the proposed algorithms have superior performance and provide better QoS to the users. This research focuses on the power allocation problem in NOMA downlink systems and proposes a novel power allocation scheme with lower complexity, and conducts simulation analysis under two propagation models.…”

“…In order to further validate the effectiveness of the proposed algorithm, we compared the spectral efficiency with reference [31] for different number of users (Fig. 11).…”

Joint resource allocation and power allocation scheme forMIMOassistedNOMAsystem

“…Finally, the energy efficiency was improved by the interference cancelation technique as an alternating direction method of multipliers concerning fronthaul link capacity constraints. Wang et al 24 proposed a three-step process for optimal resource allocation in the MIMO-NOMA system. A fractional transmitting power control model does the intra-cluster power allocation without constraints.…”

Efficient Distributed Dynamic Power Allocation and Beam-Forming In Underlay Cognitive Radio Networks

“…MIMO NOMA system with beam forming, power allocation and user clustering is done in [19] to provide spectrum sharing method with both CBS and PBS employing huge array of antennas to gain good transmission rate and power efficiency of the system, analog beam forming is employed to analyze the spectral and energy efficiencies of the downlink multiple users with NOMA network employing massive array of base station antennas. The harmful interference introduced due to imperfect CSI is also reduced significantly in this method of zero forcing beam forming and power allocation technique with strong intra cluster user scenario.…”