Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks

The traditional orthogonal multiple access(OMA)is unable to satisfy the needs of large number of smart devices.To increase the transmission rate in the limited spectrum resource,implementation of both non-orthogonal multiple access(NOMA)and successive interference cancelation(SIC)is essential.In this paper,an optimal resource allocation algorithm in NOMA is proposed to maximize the total system rate in a multi-sector multi-subcarrier relay-assisted communication network.Since the original problem is a non-convex problem with mixed integer programming which is non-deterministic polynomial-time(NP)-hard,a three-step solution is proposed to solve the primal problem.Firstly,we determine the optimal power allocation of the outer users by using the approach of monotonic discrimination,and then the optimal user pairing is determined.Secondly,the successive convex approximation(SCA)method is introduced to transform the non-convex problem involving central users into convex one,and the Lagrangian dual method is used to determine the optimal solution.Finally,the standard Hungarian algorithm is utilized to determine the optimal subcarrier matching.The simulation results show that resource allocation algorithm is able to meet the user performance requirements with NOMA,and the total system rate is improved compared to the existing algorithms.

Efficient User Pairing for Performance Enhancement of Downlink NOMA Systems

In this paper,the resource allocation problem for user pairing(UP)in downlink non-orthogonal multiple access(NOMA)systems is investigated.NOMA allows the use of one subcarrier for more than one user at the same time,thus increases the total capacity of the wireless communication system.However,users pairing is a challenging task in the NOMA systems,because a good channel quality subcarrier should be selected and allocated for the user to enhance the performance of NOMA systems.The proposed UP algorithm aims to enhance the sum rate of the paired users per subcarrier and consequently enhance the total sum rate of downlink NOMA systems.Moreover,the proposed UP algorithm target to improve the fairness of the users.The proposed UP algorithm is based on a simple search for the subcarrier with the minimum average channel gains to be assigned its paired users and then excluding it from the next searching process.The proposed scheme ensures the higher channel gain for users by giving the priority to the subcarrier with the minimum average channel gains during the user pairing process.The simulation results demonstrate that the proposed UP algorithm can not only enhance the total sum rate compared with the random UP and conventional UP but also can enhance the fairness of the users.Moreover,it is clearly seen that the proposed UP algorithm provides the lowest outage probability.

Joint user pairing and power allocation in uplink virtual MIMO with imperfect CSI

User pairing strategy for virtual multi-input multi-output （VMIMO） has been widely studied to improve system throughput, but most studies are based on perfect channel state information （CSI） and uniform power allocation. However, perfect CSI is very difficult or even impossible to obtain in practical system. Moreover power allocation has significant impact on algorithm performance. Therefore, in this paper, a low-complex joint user pairing and power allocation algorithm based on aggressive discrete stochastic optimization and Lagrangian dual solution is proposed for uplink VMIMO with imperfect CSI. Simulation results show that the proposed algorithm can achieve desirable throughput performance, and restrict inter-user interference （IUI） efficiently.

Group-based user pairing for virtual MIMO in LTE

A user pairing method is proposed to improve the throughput gain of virtual multiple input multiple output （virtual MIMO） in 3G long-term evolution（LTE）. The approach taken in this study separated the user pairing into four steps： 1） the users are divided into two groups according to their signal-to-noise ratio （SNR）, and different user pairing metrics are proposed for each group; 2） the scheduler chooses a user for transmitting by a given rule; 3） the scheduler searches the pairing candidate for the selected user in each group; 4） the scheduler chooses the final pairing user from the co-group and crossover-group candidates by using a marginal utility function, to balance fairness and efficiency. The method can improve the throughput of users with high SNR, and guarantee fairness for users with low SNR, so it can be used in 3G LTE systems. The article provides both theoretical analysis and simulation results to support the idea.

Joint user pairing and power allocation in multi-slicing NOMA system

Joint user pairing and power allocation approach is investigated to meet the rate requirement of enhanced mobile broadband(eMBB)slicing and delay constraint of ultra-reliable low-latency communication(URLLC)slicing simultaneously in downlink non-orthogonal multiple access(NOMA)system.For maximizing the proportional fairness among mobile terminals,a two-step algorithm is proposed.For a given user sets,the optimal user pairing sets and the factor of the power allocation in a group were obtained to ensure the quality of service(QoS)and the isolation between different types of slicings.Simulation results show that the proposed joint algorithm can provide better throughput than orthogonal multiple access(OMA).

3D-MIMO codebook aided multiple user pairing scheme in LTE-Advanced systems

Two-dimensional（2D） multiple-input multiple-output（MIMO） is currently concentrated on propagation in horizontal plane, but the impact of elevation angle is not considered. However, due to the three-dimensional（3D） character of the real MIMO channel, 2D MIMO cannot achieve the optimal system throughput. A multiple-user MIMO（MU-MIMO） user pairing scheme was proposed, in which the vertical dimension was taken into consideration. In the proposed scheme, a 3D codebook based on full dimension MIMO channel was designed; then two 3D MU-MIMO user＇s pairing schemes are proposed combining the proposed joint and separate 3D codebook. Simulation evaluates the proposed 3D codebook aided user pairing scheme and compares with the previous 2D MU-MIMO user pairing technology. Owing to the additional spatial degree of freedom in vertical dimension, the proposed 3D MU-MIMO user pairing schemes can effectively improve the overall system performance.

Capacity and Fairness Maximization-Based Resource Allocation for Downlink NOMA Networks

Non-orthogonal multiple access(NOMA)is one of the leading technologies for 5G communication.User pairing(UP)and power allocation(PA)are the key controlling mechanisms for the optimization of the performance of NOMA systems.This paper presents a novel UP and PA(UPPA)technique for capacity and fairness maximization in NOMA called(CFM-UPPA).The impact of the power allocation coefficient and the ratio between the channel gains of the paired users on the sum-rate capacity and the fairness in NOMA is firstly investigated.Then,based on this investigation,the PA and UP algorithms of the CFM-UPPA technique are proposed.The power allocation coefficient of the proposed PA is formulated as an exponentially decaying function of the ratio between the channel gains of the paired users to maximize the capacity and the fairness,and its maximum value is adjusted to guarantee the successive interference cancellation(SIC)constraints.The proposed UP is based on selecting the user that has the highest channel gain per subcarrier as the strong user to maximize the capacity and selecting the user that has the closest lower channel gain to the strong user’s channel gain as the weak user to improve the fairness and capacity.The performance evaluation of the proposed CFM-UPPA technique in terms of capacity,fairness,and outage probability demonstrates that its performance significantly outperforms that of the orthogonal multiple access(OMA)system and that of the NOMA system with random UP.Also,the simulation results demonstrate the efficiency of the proposed PA in improving the performance of other UP algorithms,such as the random UP algorithm.