A non-orthogonal multiple access (NOMA)-inspired integrated sensing and communication (ISAC) framework is proposed, where a dual-functional base station (BS) transmits the composite communication and sensing signals. In contrast to treating the sensing signal as a harmful interference to communication, in this work, multiple beams of the sensing signal are exploited to convey extra information streams based on the concept of NOMA. Then, each communication user detects the extra information streams and the existing legacy information streams with the aid of successive interference cancellation (SIC). Based on the proposed framework, a multiple-objective optimization problem (MOOP) is formulated to characterize the trade-off between the communication throughput and sensing beampattern accuracy. For the general multiple-user scenario, the formulated MOOP is firstly converted to a single-objective optimization problem via the e-constraint method. Then, a double-layer block coordinate descent (BCD) algorithm is proposed by employing fractional programming and successive convex approximation to find a high-quality sub-optimal solution. For the special single-user scenario, the globally optimal solution can be obtained by transforming the MOOP into a convex quadratic semidefinite program. Moreover, it is rigorously proved that 1) in the multiple-user scenario, the proposed NOMA-inspired ISAC framework always outperforms the state-of-the-art sensing-interference-cancellation (SenIC) ISAC frameworks by further exploiting sensing signals for delivering extra information streams; 2) in the special single-user scenario, the proposed NOMA-inspired ISAC framework achieves the same performance as the existing SenIC ISAC frameworks, which reveals that the coordination of sensing interference is not necessarily required in this case. Numerical results verify the theoretical results.
翻译:提出一个非垂直多重存取(NOMA)激励的综合感知和通信(ISAC)框架,其中提出一个双功能基站(MOOP)传输复合通信和感知信号。与将感知信号视为有害干扰通信的情况相反,在这项工作中,将感知信号的多重光束用于根据NOMA概念传递额外信息流。然后,每个通信用户在连续取消干扰(SIC)的帮助下检测额外信息流和现有遗留信息流。根据拟议的框架,设计了一个多目标优化问题(MOOP),以描述通信传输量和感知感知感知信号之间的交易。对于一般多用户而言,所设计的MOOP首先被利用了基于NOMA概念的概念传递额外信息流。然后,通过使用分级编程和连续的Snvex调控,找到一个高质量的次优化框架。对于特殊的单一用户假设,全球最佳解决方案可以通过将SISOP IMA(ISA) IMA(SIMA) 的性能向当前SISA(SIMA) IMA(S) IMA) IM(S) IMA(SIMA) IMA(S) IMA(S) IMA) IMA(S) IMA(S) IMA) IMA(S) IMA(S) IMA) (S) (S) IMA) IMA) (S) (S) (S) (S) (S) (S) (S) (S) IMA) (S) (S) (SISA) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (I) (I) (I) (S) (I) (S) (I) (I) (I) (I) (I) (I) (S) (I) (S) (I) (S) (I) (I) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S) (S)