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Electrical Engineering and Systems Science > Signal Processing

Title: Co-Designing Statistical MIMO Radar and In-band Full-Duplex Multi-User MIMO Communications

Abstract: We present a spectral co-design of a statistical multiple-input-multiple-output (MIMO) radar and an in-band full-duplex (IBFD) multi-user MIMO (MU-MIMO) communications system both of which concurrently operate within the same frequency band. Prior works on MIMO-radar-MIMO-communications (MRMC) problem either focus on colocated MIMO radars and half-duplex/single-user MIMO communications, seek coexistence solutions, do not jointly design radar codes and receiver processing, or omit practical system constraints. Here, we jointly design statistical MIMO radar waveform, uplink (UL)/downlink (DL) precoders, and receive filters. To this end, we employ a novel performance measure, namely compounded-and-weighted sum mutual information, that is subjected to multiple practical constraints of UL/DL transmit power, UL/DL quality of service, and peak-to-average-power-ratio. We solve the resulting non-convex problem by incorporating block coordinate descent (BCD) and alternating projection (AP) methods in a single algorithmic framework called BCD-AP MRMC. We achieve this by exploiting the relationship between mutual information and weighted minimum mean-squared-error (WMMSE), which allows the use of the Lagrange dual problem in finding closed-form solutions for precoders and radar waveform. Numerical experiments show that our proposed WMMSE-based method quickly achieves monotonic convergence, improves target detection by 9-20% compared to conventional radar coding, and provides an 8.3-30% higher achievable rate in IBFD MU-MIMO system than other precoding strategies.
Comments: 15 pages, 6 figures
Subjects: Signal Processing (eess.SP); Information Retrieval (cs.IR)
Cite as: arXiv:2006.14774 [eess.SP]
  (or arXiv:2006.14774v3 [eess.SP] for this version)

Submission history

From: Kumar Vijay Mishra [view email]
[v1] Fri, 26 Jun 2020 03:22:24 GMT (2074kb,D)
[v2] Thu, 7 Oct 2021 00:54:13 GMT (4207kb,D)
[v3] Mon, 24 Jan 2022 00:34:51 GMT (4484kb,D)
[v4] Fri, 2 Sep 2022 17:24:11 GMT (5228kb,D)
[v5] Thu, 28 Mar 2024 03:24:11 GMT (1447kb,D)

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