Wideband Millimeter-Wave Massive MIMO Channel Training via Compressed Sensing

Chou, Tzu-Hsuan; Michelusi, Nicolò; Love, David J.; Krogmeier, James V.

doi:10.1109/globecom46510.2021.9685901

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…where each level has its sub-codebook with G sub = 3. Due to the narrow beam property of massive MIMO, the sub-codebook size G sub should be selected to guarantee the beam coverage of G (1) on all possible spatial angles.…”

Section: E Sequential Search Methods With Hierarchical Codebookmentioning

confidence: 99%

“…4, an example of the channel support evolution is illustrated, where the colored and white elements denote the dominant (non-zero) and negligible (zero) beamspace channel elements, respectively. Given a slowly-varying channel with L = 4 paths, the consecutive channel supports 1) and Ω (F ) share L cm = 3 common elements (shown in green), so that only one path may change from one frame to the next (shown in red). This structure enables the use of the LS-CS approach [43], [44] to reduce the channel training overhead, discussed in Section III.…”

Section: Extended Virtual Representation Of the Mimo Channelmentioning

confidence: 99%

“…To guarantee the beam coverage of the sub-codebook G (1) on all possible spatial angles, the sub-codebook resolution G sub −1 is required to be at least finer than the beamwidth N −1 . Therefore, we choose the sub-codebook size as G sub ≥ N .…”

mentioning

confidence: 99%

“…In Fig. 7a, we illustrate the beamforming gain of the effective dictionary vectors W H k a N (ψ i ; f k ) with ψ i ∈ G (1) (as in (31)), given N = G sub = 16, Q = 30, B = 8 GHz, f c = 142 GHz, and k = 50 among K o = 128 subcarriers. The expected beamforming gain is shown in Fig.…”

mentioning

confidence: 99%

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Compressed Training for Dual-Wideband Time-Varying Sub-Terahertz Massive MIMO

Chou¹,

Michelusi²,

Love³

et al. 2022

Preprint

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Designers of beyond-5G systems are planning to use new frequencies in the millimeter wave (mmWave) and sub-terahertz (sub-THz) bands to meet ever-increasing demand for wireless broadband access. Sub-THz communication, however, will come with many challenges of mmWave communication and new challenges associated with the wider bandwidths, larger numbers of antennas and harsher propagation characteristics. Notably the frequency-and spatial-wideband (dual-wideband) effects are significant at sub-THz. To address these challenges, this paper presents a compressed training framework to estimate the sub-THz time-varying MIMO-OFDM channels. A set of frequency-dependent array response matrices are constructed, enabling the channel recovery from multiple observations across subcarriers via multiple measurement vectors (MMV). Capitalizing on the temporal correlation, MMV least squares (MMV-LS) is designed to estimate the channel on the previous beam index support, followed by MMV compressed sensing (MMV-CS) on the residual signal to estimate the time-varying channel components. Furthermore, a channel refinement algorithm is proposed to estimate the path coefficients and time delays of the dominant paths. To reduce the computational complexity, a sequential search method using hierarchical codebooks is proposed for greedy beam selection. Numerical results show that MMV-LS-CS achieves a more accurate and robust channel estimation than state-of-the-art algorithms on time-varying dual-wideband MIMO-OFDM.

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Section: E Sequential Search Methods With Hierarchical Codebookmentioning

confidence: 99%