Performance and Complexity Analysis of Terahertz-Band MIMO Detection
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915568521576448 |
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| author | Jemaa, Hakim Tarboush, Simon Sarieddeen, Hadi Alouini, Mohamed-Slim Al-Naffouri, Tareq Y. |
| author_facet | Jemaa, Hakim Tarboush, Simon Sarieddeen, Hadi Alouini, Mohamed-Slim Al-Naffouri, Tareq Y. |
| contents | Achieving terabit-per-second (Tbps) data rates in terahertz (THz)-band communications requires bridging the complexity gap in baseband transceiver design. This work addresses the signal processing challenges associated with data detection in THz-band multiple-input multiple-output (MIMO) systems. We begin by analyzing the trade-offs between performance and complexity across various detection schemes and THz channel models, demonstrating significant complexity reduction by leveraging spatial parallelism across subspaces of correlated, typically ill-conditioned THz MIMO channels. We also derive accurate theoretical bounds on the detection error probability by incorporating THz-specific channel distributions and accounting for mismatches introduced by subspace decomposition. In addition, we propose a variation of subspace detectors that combines channel-matrix sorting, QR decomposition, and puncturing. Furthermore, under wideband THz UM-MIMO systems, we introduce a channel-matrix reuse strategy that minimizes exhaustive computations while maintaining reliable detection performance within a coherence bandwidth. Simulations over accurate THz channels show that the proposed efficient spatial parallelization schemes yield multi-dB performance gains, while the proposed reuse strategy offers significant computational savings with minimal performance degradation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_05268 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Performance and Complexity Analysis of Terahertz-Band MIMO Detection Jemaa, Hakim Tarboush, Simon Sarieddeen, Hadi Alouini, Mohamed-Slim Al-Naffouri, Tareq Y. Signal Processing Achieving terabit-per-second (Tbps) data rates in terahertz (THz)-band communications requires bridging the complexity gap in baseband transceiver design. This work addresses the signal processing challenges associated with data detection in THz-band multiple-input multiple-output (MIMO) systems. We begin by analyzing the trade-offs between performance and complexity across various detection schemes and THz channel models, demonstrating significant complexity reduction by leveraging spatial parallelism across subspaces of correlated, typically ill-conditioned THz MIMO channels. We also derive accurate theoretical bounds on the detection error probability by incorporating THz-specific channel distributions and accounting for mismatches introduced by subspace decomposition. In addition, we propose a variation of subspace detectors that combines channel-matrix sorting, QR decomposition, and puncturing. Furthermore, under wideband THz UM-MIMO systems, we introduce a channel-matrix reuse strategy that minimizes exhaustive computations while maintaining reliable detection performance within a coherence bandwidth. Simulations over accurate THz channels show that the proposed efficient spatial parallelization schemes yield multi-dB performance gains, while the proposed reuse strategy offers significant computational savings with minimal performance degradation. |
| title | Performance and Complexity Analysis of Terahertz-Band MIMO Detection |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2504.05268 |