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PreprintarXiv licencearXiv

On the Communication-Sensing Tradeoff in DMT-Optimal Space-time-Coded ISAC Systems

Abstract

Integrated sensing and communications (ISAC) has been extensively studied from the perspective of communication-sensing performance tradeoffs. In MIMO communication systems, the diversity-multiplexing tradeoff (DMT) fundamentally characterizes the tradeoff between communication reliability and multiplexing gain, and DMT-optimal space-time codes achieve this optimal tradeoff without instantaneous channel state information at the transmitter (CSIT), making them particularly attractive for ISAC scenarios where accurate CSIT is difficult to acquire or maintain. In this work, we propose an analytical framework for characterizing the sensing behavior and communication-sensing gain tradeoff of DMT-optimal space-time codes in ISAC systems. Under a single-target detection model, we propose the sensing diversity order as the high-SNR sensing reliability metric. We further show that a class of DMT-optimal space-time codes, exemplified by Perfect codes, eliminates sensing blind spots for all nonzero codewords, thereby achieving joint DMT-sensing-diversity (DMTS) optimality. Furthermore, using the Perfect code as a representative DMT-optimal construction, we show that its isotropic average transmit covariance limits the achievable sensing gain when the target angular region is narrow. We therefore develop a full-rank spatial precoding framework and a low-complexity surrogate precoder that preserve joint DMTS optimality while shaping the transmit beampattern. Simulation results show that, for a target angular region of θ∈[−π/10,π/10], the proposed design achieves approximately 3 dB sensing-gain improvement over the unprecoded Perfect code.

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BibTeX
@misc{chen2026communicationsensing,
  title = {{On the Communication-Sensing Tradeoff in DMT-Optimal Space-time-Coded ISAC Systems}},
  author = {Wei-Chen Chen and Yu-Chih Huang and Ming-Chun Lee},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.41144},
  eprint = {2610.41144},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.41144},
}
RIS
TY  - UNPB
TI  - On the Communication-Sensing Tradeoff in DMT-Optimal Space-time-Coded ISAC Systems
AU  - Wei-Chen Chen
AU  - Yu-Chih Huang
AU  - Ming-Chun Lee
PY  - 2026
DA  - 2026/10/30
PB  - arXiv
DO  - 10.48550/arxiv.2610.41144
UR  - https://arxiv.org/abs/2610.41144
AB  - Integrated sensing and communications (ISAC) has been extensively studied from the perspective of communication-sensing performance tradeoffs. In MIMO communication systems, the diversity-multiplexing tradeoff (DMT) fundamentally characterizes the tradeoff between communication reliability and multiplexing gain, and DMT-optimal space-time codes achieve this optimal tradeoff without instantaneous channel state information at the transmitter (CSIT), making them particularly attractive for ISAC scenarios where accurate CSIT is difficult to acquire or maintain. In this work, we propose an analytical framework for characterizing the sensing behavior and communication-sensing gain tradeoff of DMT-optimal space-time codes in ISAC systems. Under a single-target detection model, we propose the sensing diversity order as the high-SNR sensing reliability metric. We further show that a class of DMT-optimal space-time codes, exemplified by Perfect codes, eliminates sensing blind spots for all nonzero codewords, thereby achieving joint DMT-sensing-diversity (DMTS) optimality. Furthermore, using the Perfect code as a representative DMT-optimal construction, we show that its isotropic average transmit covariance limits the achievable sensing gain when the target angular region is narrow. We therefore develop a full-rank spatial precoding framework and a low-complexity surrogate precoder that preserve joint DMTS optimality while shaping the transmit beampattern. Simulation results show that, for a target angular region of θ∈[−π/10,π/10], the proposed design achieves approximately 3 dB sensing-gain improvement over the unprecoded Perfect code.
ER  -