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

A Novel Network NOMA Scheme for Downlink Coordinated Three-Point Systems

In this paper, we propose a network non-orthogonal multiple access (N-NOMA) technique for the downlink coordinated multipoint (CoMP) communication scenario of a cellular network, with randomly deployed users. In the considered N-NOMA scheme, superposition coding (SC) is employed to serve cell-edge users as well as users close to base stations (BSs) simultaneously, and distributed analog beamforming by the BSs to meet the cell-edge user's quality of service (QoS) requirements. The combination of SC and distributed analog beamforming significantly complicates the expressions for the signal-to-interference-plus-noise ratio (SINR) at the reveiver, which makes the performance analysis particularly challenging. However, by using rational approximations, insightful analytical results are obtained in order to characterize the outage performance of the considered N-NOMA scheme. Computer simulation results are provided to show the superior performance of the proposed scheme as well as to demonstrate the accuracy of the analytical results

A Survey of Downlink Non-orthogonal Multiple Access for 5G Wireless Communication Networks

Accepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsNon-orthogonal multiple access (NOMA) has been recognized as a promising multiple access technique for the next generation cellular communication networks. In this paper, we first discuss a simple NOMA model with two users served by a single-carrier simultaneously to illustrate its basic principles. Then, a more general model with multicarrier serving an arbitrary number of users on each subcarrier is also discussed. An overview of existing works on performance analysis, resource allocation, and multiple-input multiple-output NOMA are summarized and discussed. Furthermore, we discuss the key features of NOMA and its potential research challenges

Highly Efficient Resource Allocation Techniques in 5G for NOMA-based Massive MIMO and Relaying Systems

The explosive proliferation of smart devices in the 5-th generation (5G) network expects 1,000-fold capacity enhancement, leading to the urgent need of highly resource-efficient technologies. Non-orthogonal multiple access (NOMA), a promising spectral efficient technology for 5G to serve multiple users concurrently, can be combined with massive multiple input multiple output (MIMO) and relaying technology, to achieve highly efficient communications. Hence, this thesis studies the design and resource allocation of NOMA-based massive MIMO and relaying systems. Due to hardware constraints and channel condition variation, the first topic of the thesis develops efficient antenna selection and user scheduling algorithms for sum rate maximization in two MIMO-NOMA scenarios. In the single-band scenario, the proposed algorithm improves antenna search efficiency by limiting the candidate antennas to those are beneficial to the relevant users. In the multi-band scenario, the proposed algorithm selects the antennas and users with the highest contribution total channel gain. Numerical results show that our proposed algorithms achieve similar performance to other algorithms with reduced complexity. The second part of the thesis proposes the relaying and power allocation scheme for the NOMA-assisted relaying system to serve multiple cell-edge users. The relay node decodes its own message from the source NOMA signal and transmits the remaining part of signal to cell-edge users. The power allocation scheme is developed by minimizing the system outage probability. To further evaluate the system performance, the ergodic capacity is approximated by analyzing the interference at cell-edge users. Numerical results proves the performance improvement of the proposed system over conventional orthogonal multiple access mechanism

Resource allocation for NOMA wireless systems

Power-domain non-orthogonal multiple access (NOMA) has been widely recognized as a promising candidate for the next generation of wireless communication systems. By applying superposition coding at the transmitter and successive interference cancellation at the receiver, NOMA allows multiple users to access the same time-frequency resource in power domain. This way, NOMA not only increases the system’s spectral and energy efficiencies, but also supports more users when compared with the conventional orthogonal multiple access (OMA). Meanwhile, improved user fairness can be achieved by NOMA. Nonetheless, the promised advantages of NOMA cannot be realized without proper resource allocation. The main resources in wireless communication systems include time, frequency, space, code and power. In NOMA systems, multiple users are accommodated in each time/frequency/code resource block (RB), forming a NOMA cluster. As a result, how to group the users into NOMA clusters and allocate the power is of significance. A large number of studies have been carried out for developing efficient power allocation (PA) algorithms in single-input single-output (SISO) scenarios with fixed user clustering. To fully reap the gain of NOMA, the design of joint PA and user clustering is required. Moreover, the study of PA under multiple-input multiple-output (MIMO) systems still remains at an incipient stage. In this dissertation, we develop novel algorithms to allocate resource for both SISO-NOMA and MIMO-NOMA systems. More specifically, Chapter 2 compares the system capacity of MIMO-NOMA with MIMO-OMA. It is proved analytically that MIMO-NOMA outperforms MIMO-OMA in terms of both sum channel capacity and ergodic sum capacity when there are multiple users in a cluster. Furthermore, it is demonstrated that the more users are admitted to a cluster, the lower is the achieved sum rate, which illustrates the tradeoff between the sum rate and maximum number of admitted users. Chapter 3 addresses the PA problem for a general multi-cluster multi-user MIMONOMA system to maximize the system energy efficiency (EE). First, a closed-form solution is derived for the corresponding sum rate (SE) maximization problem. Then, the EE maximization problem is solved by applying non-convex fractional programming. Chapter 4 investigates the energy-efficient joint user-RB association and PA problem for an uplink hybrid NOMA-OMA system. The considered problem requires to jointly optimize the user clustering, channel assignment and power allocation. To address this hard problem, a many-to-one bipartite graph is first constructed considering the users and RBs as the two sets of nodes. Based on swap matching, a joint user-RB association and power allocation scheme is proposed, which converges within a limited number of iterations. Moreover, for the power allocation under a given user-RB association, a low complexity optimal PA algorithm is proposed. Furthermore, Chapter 5 focuses on securing the confidential information of massive MIMO-NOMA networks by exploiting artificial noise (AN). An uplink training scheme is first proposed, and on this basis, the base station precodes the confidential information and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission. Additionally, PA algorithms are proposed to maximize the SE and EE of the system. Finally, conclusions are drawn and possible extensions to resource allocation in NOMA systems are discussed in Chapter 6