Maximum Likelihood Detection and Optimal Code Design for Differential Unitary Space-Time Modulation with Carrier Frequency Offset

Abstract

In this paper, we answer the question that "Can conventional differential unitary space time modulation (DUSTM) be applied when there is an unknown carrier frequency offset (CFO)?" and present a maximum likelihood (ML) detection rule for this scenario. We analyze the asymptotical performance of our ML detection and provide the code design criterion by using the modified diversity product. The analysis also brings the insight that our proposed decision rule is a new differential modulation scheme in both temporal and spatial domains. Various simulations are conducted, and the proposed algorithm is shown to be more robust to the CFO drifting than the existing double temporal differential modulation.

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