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Worst-Case Robust Training Design for Correlated MIMO Channels in the Presence of Colored Interference

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  • Jae-Mo Kang

    (Department of Artificial Intelligence, Kyungpook National University, Daegu 41566, Republic of Korea)

  • Sangseok Yun

    (Department of Information and Communications Engineering, Pukyong National University, Busan 48513, Republic of Korea)

Abstract

The covariance information at the transmitter side is often subject to mismatches due to various impairments. This paper considers a training design problem for multiple-input multiple-output (MIMO) systems when both channel and interference covariance matrices are imperfect at the transmitter side. We first derive the structure of the optimal training signal, minimizing the worst-case mean square error (MSE). With the training structure, the original problem becomes a simple power allocation problem. We propose a numerical optimal power allocation scheme and a closed-form suboptimal power allocation scheme. Simulation results show that the proposed schemes considerably outperform the conventional schemes in terms of the worst-case MSE and bit error rate (BER) performances, and the proposed closed-form training scheme has comparable performance to that of the optimal one. For example, the proposed schemes yield more than 2.5 dB signal-to-interference ratio (SIR) gains at a BER of 10 − 4 .

Suggested Citation

  • Jae-Mo Kang & Sangseok Yun, 2025. "Worst-Case Robust Training Design for Correlated MIMO Channels in the Presence of Colored Interference," Mathematics, MDPI, vol. 13(13), pages 1-24, July.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:13:p:2168-:d:1693423
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