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arXiv 2302.09196eess.SP
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NOMA辅助的共生反向散射:不完美SIC下的新型波束成形设计

NOMA-Assisted Symbiotic Backscatter: Novel Beamforming Designs Under Imperfect SIC

Fatemeh Rezaei, Diluka Galappaththige, Chintha Tellambura, Sanjeewa Herath

AI总结:

针对NOMA主用户与二级环境标签的共生网络,本文提出两种不完美SIC下的发射波束成形与功率分配设计,通过交替优化等非凸求解算法,实现了最大化加权和速率或最小化发射功率,并显著提升了系统的收集功率与数据速率。

摘要:

针对NOMA主用户与二级环境标签的共生网络,此前一直缺乏在不完美连续干扰消除(SIC)解码条件下的最优波束成形设计。本文解决了这一问题。该网络中,主基站(BS)同时服务NOMA用户和无源标签。我们开发了两种发射波束成形设计,以满足用户和标签需求,同时减轻不完美SIC的影响。具体而言,我们设计了最优的BS发射波束成形和功率分配,以在满足标签最低能量要求的前提下,最大化NOMA用户与标签的加权和速率,或最小化BS发射功率。由于这两个问题均为非凸问题,我们提出了使用交替优化、分数规划与半定松弛技术的算法,并分析了其计算复杂度。最后,我们给出了广泛的数值结果来验证所提方案,并展示了在保持标签设计不变的情况下的显著性能增益。例如,与随机波束成形相比,所提数字波束成形使收集功率和数据速率分别提高了2.16e3%和314.5%。

英文摘要:

Optimal beamforming designs under imperfect successive interference cancellation (SIC) decoding for a symbiotic network of non-orthogonal multiple access (NOMA) primary users and a secondary ambient tag have been lacking. We address that issue here. The primary base station (BS) serves NOMA users and a passive tag simultaneously in this network. We develop two transmit beamforming designs to meet the user and tag requirements while mitigating the effect of imperfect SIC. Specifically, we design optimal BS transmit beamforming and power allocation to either maximize the weighted sum rate of NOMA users and the tag or minimize the BS transmit power under the minimum rate requirements while satisfying the tag minimum energy requirement. Because both these problems are non-convex, we propose algorithms using alternative optimization, fractional programming, and semi-definite relaxation techniques. We also analyze their computational complexity. Finally, we present extensive numerical results to validate the proposed schemes and to show significant performance gains while keeping the tag design intact. For example, the proposed digital beamforming increases the harvested power and data rate by 2.16e3 % and 314.5 % compared to random beamforming.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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