Cross Far- and Near-field Wireless Communications in Terahertz Ultra-large Antenna Array Systems

Abstract

Terahertz (THz) band owning the abundant multiten-GHz bandwidth is capable to support Terabit-per-second wireless communications, which is a pillar technology for 6G and beyond systems. With sub-millimeter-long antennas, ultramassive (UM) MIMO and intelligent surface (IS) systems with thousands of array elements are exploited to effectively combat the distance limitation and blockage problems, which compose a promising THz ultra-large antenna array (ULAA) system. As a combined effect of wavelength and array aperture, the resulting coverage of THz systems ranges from near-field to far-field, leading to a new paradigm of cross-field communications. Although channel models, communications theories, and networking strategies have been studied for far-field and nearfield separately, the unified design of cross-field communications that achieve high spectral efficiency and low complexity is still missing. In this article, the challenges and features of THz ULAA cross-field communications are investigated. Furthermore, crossfield solutions in three perspectives are presented, including a hybrid spherical-and planar-wave channel model, cross-field channel estimation, and widely-spaced multi-subarray hybrid beamforming, where a subarray as a basic unit in THz ULAA systems is exploited. The approximation error of channel modeling accuracy, spectral efficiency, and estimation error of these designs are numerically evaluated. Finally, as a roadmap of THz ULAA cross-field communications, multiple open problems and potential research directions are elaborated.

TeraMIMO: A Channel Simulator for Wideband Ultra-Massive MIMO Terahertz Communications

“…To the best of the authors' knowledge, this is the first article to solve the cross-field channel estimation problem. Though [16] mentions the term "cross-field channel estimation", it uses HSPWM regardless of the distance. This is equivalent to assuming intermediate-field for all distances and makes [16] akin to other work on HSPWM channel estimation e.g., [18], [27], [28].…”

“…In this architecture, the Tx and Rx UM-MIMO arrays are divided into subarrays (SAs), where each SA is connected to one radio frequency (RF)-chain exclusively. This provides several advantages, e.g., reduced complexity and power consumption, and also makes channel estimation simpler [1], [16]. On the downside, some spectral efficiency is lost compared to the fully-connected structures.…”

“…Though SWM is accurate for channel modeling, it makes the channel estimation more complex [17]. A simpler alternative to SWM is a hybrid sphericalplanar wave model (HSPWM) [9], [16]. The HSPWM captures only the phase variation across the nearby AEs, but captures both the phase and magnitude variation across more separated AEs.…”

“…The HSPWM captures only the phase variation across the nearby AEs, but captures both the phase and magnitude variation across more separated AEs. Thus, compared to PWM and SWM, the HSPWM provides a good trade-off in modeling accuracy and complexity [9], [16]. HSPWM is particularly suitable for partially-connected hybrid beamforming AoSA architecture, where the elements within a SA can be considered nearby AEs, whereas array elements across the SAs can be considered more separated.…”

“…HSPWM is particularly suitable for partially-connected hybrid beamforming AoSA architecture, where the elements within a SA can be considered nearby AEs, whereas array elements across the SAs can be considered more separated. Thus based on an HSPWM, a PWM within a SA and an SWM across SAs are used [9], [16]. Specifically, the prior work [9], [18] has shown that the HSPWM approximates the SWM with an approximation error of less than −10 dB, for a wide range of communication distances, array apertures, and carrier frequencies.…”