Sun Wenbin, Tao Mingliang, Yang Xin, Zhang Tao, Han Chuang, Wang Ling
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China.
China Academy of Launch Vehicle Technology, Beijing 100076, China.
Entropy (Basel). 2021 Sep 29;23(10):1278. doi: 10.3390/e23101278.
Opportunistic beamforming (OBF) is a potential technique in the fifth generation (5G) and beyond 5G (B5G) that can boost the performance of communication systems and encourage high user quality of service (QoS) through multi-user selection gain. However, the achievable rate tends to be saturated with the increased number of users, when the number of users is large. To further improve the achievable rate, we proposed a multi-antenna opportunistic beamforming-based relay (MOBR) system, which can achieve both multi-user and multi-relay selection gains. Then, an optimization problem is formulated to maximize the achievable rate. Nevertheless, the optimization problem is a non-deterministic polynomial (NP)-hard problem, and it is difficult to obtain an optimal solution. In order to solve the proposed optimization problem, we divide it into two suboptimal issues and apply a joint iterative algorithm to consider both the suboptimal issues. Our simulation results indicate that the proposed system achieved a higher achievable rate than the conventional OBF systems and outperformed other beamforming schemes with low feedback information.
机会波束成形(OBF)是第五代(5G)及5G之后(B5G)的一种潜在技术,它可以通过多用户选择增益提高通信系统的性能并提升用户的服务质量(QoS)。然而,当用户数量很大时,随着用户数量的增加,可实现速率趋于饱和。为了进一步提高可实现速率,我们提出了一种基于多天线机会波束成形的中继(MOBR)系统,该系统可以实现多用户和多中继选择增益。然后,制定了一个优化问题以最大化可实现速率。然而,该优化问题是一个非确定性多项式(NP)难题,难以获得最优解。为了解决提出的优化问题,我们将其分为两个次优问题,并应用联合迭代算法来考虑这两个次优问题。我们的仿真结果表明,所提出的系统比传统的OBF系统实现了更高的可实现速率,并且在低反馈信息的情况下优于其他波束成形方案。