Abstract:Harnessing diversity is fundamental to wireless communication systems, particularly in the terahertz (THz) band, where severe path loss and small-scale fading pose significant challenges to system reliability and performance. In this paper, we present a comprehensive diversity analysis for indoor THz communication systems, accounting for the combined effects of path loss and small-scale fading, with the latter modeled as an $\alpha-\mu$ distribution to reflect THz indoor channel conditions. We derive closed-form expressions for the bit error rate (BER) as a function of the reciprocal of the signal-to-noise ratio (SNR) and propose an asymptotic expression. Furthermore, we validate these expressions through extensive simulations, which show strong agreement with the theoretical analysis, confirming the accuracy and robustness of the proposed methods. Our results show that the diversity order in THz systems is primarily determined by the combined effects of the number of independent paths, the severity of fading, and the degree of channel frequency selectivity, providing clear insights into how diversity gains can be optimized in high-frequency wireless networks.
Abstract: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 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 parallelizability over subspaces of correlated THz MIMO channels. We derive accurate detection error probability bounds by accounting for THz-specific channel models and mismatches introduced by subspace decomposition. Building on this, we propose a subspace detector that integrates layer sorting, QR decomposition, and channel-matrix puncturing to balance performance loss and parallelizability. Furthermore, we introduce a channel-matrix reuse strategy for wideband THz MIMO detection. Simulations over accurate, ill-conditioned THz channels show that efficient parallelizability achieves multi-dB performance gains, while wideband reuse strategies offer computational savings with minimal performance degradation.
Abstract:As advancements close the gap between current device capabilities and the requirements for terahertz (THz)-band communications, the demand for terabit-per-second (Tbps) circuits is on the rise. This paper addresses the challenge of achieving Tbps data rates in THz-band communications by focusing on the baseband computation bottleneck. We propose leveraging parallel processing and pseudo-soft information (PSI) across multicarrier THz channels for efficient channel code decoding. We map bits to transmission resources using shorter code-words to enhance parallelizability and reduce complexity. Additionally, we integrate channel state information into PSI to alleviate the processing overhead of soft decoding. Results demonstrate that PSI-aided decoding of 64-bit code-words halves the complexity of 128-bit hard decoding under comparable effective rates, while introducing a 4 dB gain at a $10^{-3}$ block error rate. The proposed scheme approximates soft decoding with significant complexity reduction at a graceful performance cost.
Abstract:The precision of link-level theoretical performance analysis for emerging wireless communication paradigms is critical. Recent studies have demonstrated the excellent fitting capabilities of the mixture gamma (MG) distribution in representing small-scale fading in outdoor terahertz (THz)-band scenarios. Our study establishes an in-depth performance analysis for outdoor point-to-point THz links under realistic configurations, incorporating MG small-scale fading combined with the misalignment effect. We derive closed-form expressions for the bit-error probability, outage probability, and ergodic capacity. Furthermore, we conduct an asymptotic analysis of these metrics at high signal-to-noise ratios and derive the necessary convergence conditions. Simulation results, leveraging precise measurement-based channel parameters in various configurations, closely align with the derived analytical equations.
Abstract:Recent advances in electronic and photonic technologies have allowed efficient signal generation and transmission at terahertz (THz) frequencies. However, as the gap in THz-operating devices narrows, the demand for terabit-per-second (Tbps)-achieving circuits is increasing. Translating the available hundreds of gigahertz (GHz) of bandwidth into a Tbps data rate requires processing thousands of information bits per clock cycle at state-of-the-art clock frequencies of digital baseband processing circuitry of a few GHz. This paper addresses these constraints and emphasizes the importance of parallelization in signal processing, particularly for channel code decoding. By leveraging structured sub-spaces of THz channels, we propose mapping bits to transmission resources using shorter code words, extending parallelizability across all baseband processing blocks. THz channels exhibit quasi-deterministic frequency, time, and space structures that enable efficient parallel bit mapping at the source and provide pseudo-soft bit reliability information for efficient detection and decoding at the receiver.