Jingjing Cui

A Novel Power Allocation Scheme Under Outage Constraints in NOMA Systems

In this letter, we study a downlink non-orthogonal multiple access (NOMA) transmission system, where only the average channel state information (CSI) is available at the transmitter. Two criteria in terms of transmit power and user fairness for NOMA systems are used to formulate two optimization problems, subjected to outage probabilistic constraints and the optimal decoding order. We first investigate the optimal decoding order when the transmitter knows only the average CSI, and then, we develop the optimal power allocation schemes in closed form by employing the feature of the NOMA principle for the two problems. Furthermore, the power difference between NOMA systems and OMA systems under outage constraints is obtained.

Impact of Factor Graph on Average Sum Rate for Uplink Sparse Code Multiple Access Systems

In this paper, we first study the average sum rate of sparse code multiple access (SCMA) systems, where a general scenario is considered under the assumption that the distances between the mobile users and the base station are not necessarily identical. Closed-form analytical results are derived for the average sum rate based on which an optimal factor graph matrix is designed for maximizing the capacity of the SCMA systems. Moreover, we propose a low-complexity iterative algorithm to facilitate the design of the optimal graph matrix. Finally, Monte Carlo simulations are provided to corroborate the accuracy of the theoretical results and the efficiency of the proposed iterative algorithm.

Optimal User Scheduling and Power Allocation for Millimeter Wave NOMA Systems

This paper investigates the application of non-orthogonal multiple access (NOMA) in millimeter wave (mm-Wave) communications by exploiting beamforming, user scheduling, and power allocation. Random beamforming is invoked for reducing the feedback overhead of the considered system. A non-convex optimization problem for maximizing the sum rate is formulated, which is proved to be NP-hard. The branch and bound approach is invoked to obtain the

Power minimization strategies in downlink MIMO-NOMA systems

\epsilon

Beamforming design for MISO non-orthogonal multiple access systems

-optimal power allocation policy, which is proved to converge to a global optimal solution. To elaborate further, a low-complexity suboptimal approach is developed for striking a good computational complexity-optimality tradeoff, where the matching theory and successive convex approximation techniques are invoked for tackling the user scheduling and power allocation problems, respectively. Simulation results reveal that: 1) the proposed low complexity solution achieves a near-optimal performance and 2) the proposed mm-Wave NOMA system is capable of outperforming conventional mm-Wave orthogonal multiple access systems in terms of sum rate and the number of served users.

User Selection and Power Allocation for mmWave-NOMA Networks

This paper studies the power minimization problem for non-orthogonal multiple access (NOMA) downlink systems, in which nodes are equipped with multiple antennas. We develop a joint power allocation and receive beamforming algorithm using the fixed-point update power allocation method under two types of channel state information (CSI). Particularly, we first assume that perfect CSI is available for the base station (BS) and the users, where a closed-form expression for every receive detection vector is derived. Then, we consider only channel distribution information (CDI) is known to the BS and the users, where one-dimension search and semi-definite programming (SDP) relaxation are used to derive the receive detection vectors.

The Application of Machine Learning in mmWave-NOMA Systems

Non-orthogonal multiple access (NOMA) is a promising multiple access scheme to enhance the spectrum efficiency of fifth generation networks. In this study, the authors study a downlink multiple-input single-output (MISO) system combined with NOMA, where a single beamforming (BF) vector is shared by a group of users. A joint BF and power allocation algorithm is proposed to maximise the sum rate of the users with better channel conditions while guaranteeing the quality of service at the user with poor channel conditions. The formulated problem for sum rate maximisation can be shown as non-deterministic Polynomial-time-hard, and therefore an effective solution based on branch and bound (BB) techniques is proposed. Numerical results are provided to verify that the proposed NOMA-BF system with the BB algorithm improves the sum capacity significantly compared with the NOMA-BF system with zero forcing.