Abstract
In a real communication scenario, it is very difficult to obtain the real-time Channel State Information(CSI) accurately, so the communication systems with statistical CSI have been researched. In order to maximize the throughput of the downlink Non-Orthogonal Multiple Access (NOMA) system with statistical CSI, the formula of system throughput is derived at first. Then, according to the combinatorial characteristics of the original optimization problem, it is divided into two subproblems, that is user grouping and power allocation. At last, a joint optimization scheme is proposed. Genetic algorithm is introduced to solve the subproblem of power allocation, and Hungarian algorithm is introduced to solve the subproblem of user grouping. By comparing the ergodic data rate of NOMA users with statistical CSI and perfect CSI, the effectiveness of the statistical CSI sorting is verified. Compared with the Orthogonal Multiple Access (OMA) scheme, the NOMA scheme with the fixed user grouping scheme and the random user grouping scheme, the proposed scheme can effectively improve the system throughput.
Highlights
Non-Orthogonal Multiple Access (NOMA) technology has recently attracted tremendous attention due to its simple design and superior spectrum efficiency, which is recognized as a promising multiple access scheme in the generation mobile communication networks[1]
Many of the existing works about NOMA have assumed the perfect Channel State Information (CSI) at transmitter side, which are nearly impractical for many communication scenarios
In [3], the performance of two NOMA system with partial CSI has been evaluated, and the research results show that statistical CSI based on second order statistics is always better than the incomplete CSI
Summary
Non-Orthogonal Multiple Access (NOMA) technology has recently attracted tremendous attention due to its simple design and superior spectrum efficiency, which is recognized as a promising multiple access scheme in the generation mobile communication networks[1]. In [5], a dynamic power allocation scheme and a user grouping algorithm are proposed, users are divided into to two sets according to their statistic CSI, and the users, in different sets and with the same sort number, are matched into one group. This grouping method is simple to implement, but it cannot guarantee the overall performance of the system. Effective user grouping and power allocation schemes can provide feasibility for improving the performance of the downlink NOMA system with statistical CSI. The symbols used in this paper are defined as follows: E (·) represents the mean operator, f (·) and F (·) represent the Probability Density Function (PDF) and the Cumulative Distribution Function (CDF), respectively. and U represents the uniform distribution
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
