Performance Analysis of OTFS-based Uplink Massive MIMO with ZF Receivers

Feng, Junjuan; Ngo, Hien Quoc; Flanagan, Mark F.; Matthaiou, Michail

doi:10.1109/iccworkshops50388.2021.9473699

Cited by 10 publications

(5 citation statements)

References 16 publications

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“…We start by presenting some characteristics of the DD domain channel representation in (8), which will facilitate the ensuing achievable rate analysis.…”

Section: Performance Analysismentioning

confidence: 99%

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When Cell-Free Massive MIMO Meets OTFS Modulation: The Downlink Case

Mohammadi¹,

Ngo²,

Matthaiou³

2022

Preprint

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We provide a performance evaluation of orthogonal time frequency space (OTFS) modulation in cell-free massive MIMO (multiple-input multiple-output) systems. By leveraging the inherent sparsity of the delay-Doppler (DD) representation of time-varying channels, we apply the embedded pilot-aided channel estimation method with reduced guard intervals and derive the minimum mean-square error estimate of the channel gains from received uplink pilots at the access points (APs). Each AP applies conjugate beamforming to transmit data to the users. We derive a closed-form expression for the individual user downlink throughput as a function of the numbers of APs, users and DD channel estimate parameters. We compare the OTFS performance with that of orthogonal frequency division multiplexing (OFDM) at high-mobility conditions. Our findings reveal that with uncorrelated shadowing, cell-free massive MIMO with OTFS modulation achieves up to 35% gain in 95%-likely peruser throughput, compared with the OFDM counterpart. Finally, the increase in the per user throughput is more pronounced at the median rates over the correlated shadowing scenarios.

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“…We start by presenting some characteristics of the DD domain channel representation in (8), which will facilitate the ensuing achievable rate analysis.…”

Section: Performance Analysismentioning

confidence: 99%

“…RVs. By using (8), and noticing that channel gains of different path are zero-mean i.i.d RVs, i.e., E ĥ * pq,i ĥpq,j = 0, ∀i = j, and then applying Lemma 1 we get E x d,q 2 = ρ d…”

Section: Performance Analysismentioning

confidence: 99%

When Cell-Free Massive MIMO Meets OTFS Modulation: The Downlink Case

Mohammadi¹,

Ngo²,

Matthaiou³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…From Theorem 2, the key terms are the diagonal elements of the diagonal matrix Ω q,q given in (21). Looking at (21) and recalling the vector a(θ q,i ) in (2), with [15], we have…”

Section: Mn−1 V=0mentioning

confidence: 99%

OTFS-Based Massive MIMO with Fractional Delay and Doppler Shift: The URLLC Case

Feng

Ngo

Matthaiou

2022

2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

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This paper considers orthogonal time frequency space (OTFS)-based uplink multiuser multiple-input multipleoutput (MU-MIMO) systems in the ultra-reliable-and-low-latency communication (URLLC) space. The maximum-ratio-combining (MRC) scheme is first applied at the base station (BS) to combine all the received symbols and then the maximum likelihood (ML) decoding metric is employed to decode the intended symbols. To better characterize the system performance, we consider the ideal pulse shape functions at both users and BS side while the effect of fractional delay and Doppler shift (FDDS) is also taken into account. Based on this, we first derive the theoretical refined achievable coding rate under short-packet transmission for both joint and individual decoding at the BS. Subsequently, the corresponding asymptotic results under massive MIMO are presented. Capitalizing on these results, we draw a series of interesting insights: i) when the sampling resolution along the delay domain is not high enough, the achievable coding rate is more accurate than the channel capacity as the performance metric; ii) almost no diversity gain is obtained for the FDDS under the case considered in this paper; iii) the achievable coding rate is agnostic to the users' speed.

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“…We recall that the pulse shape functions that are commonly utilized in OTFS, vary from the ideal bi-orthogonal waveforms as defined in [6] to the more practical rectangular pulses [6]- [9]. Specifically, for the ideal bi-orthogonal pulses, [7] considered the integer delay and Doppler shift scenario. It was shown that the output signal is a linear combination of the shifted versions of the input symbols caused by the delay and Doppler taps.…”

Section: Introductionmentioning

confidence: 99%

Rectangular Pulse-Shaped OTFS with Fractional Delay and Doppler Shift for MU-MIMO Systems

Feng,

Ngo,

Matthaiou

2023

2023 IEEE International Conference on Communications Workshops (ICC Workshops)

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We consider the uplink of an orthogonal time frequency space (OTFS)-based multiuser multiple-input multipleoutput (MU-MIMO) system. For this setup, we consider, for the first time ever, the more practical rectangular pulse-shaped functions along with the fractional delay and Doppler shift. We first provide the exact OTFS-based input-output relationship. Subsequently, the orthogonal frequency division multiplexing (OFDM)-based OTFS input-output approximation is derived by reconstructing the continuous time domain signal via a sincfunction. Based on these two results, an important performance metric, namely, the pairwise error probability (PEP) with maximum-likelihood (ML) and nearest-neighbor (NN) decoding rules, is analyzed. A series of interesting insights are obtained from the analysis: i) for our system setting, the effective channel matrix is not doubly-block circulant or sparse structured anymore, while the OFDM-based approximation result consists of a block-Toeplitz with Toeplitz block (BTTB) structured matrix; ii) the practical rectangular pulses suffer from a significant perfomance degradation.

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Performance Analysis of OTFS-based Uplink Massive MIMO with ZF Receivers

Cited by 10 publications

References 16 publications

When Cell-Free Massive MIMO Meets OTFS Modulation: The Downlink Case

When Cell-Free Massive MIMO Meets OTFS Modulation: The Downlink Case

OTFS-Based Massive MIMO with Fractional Delay and Doppler Shift: The URLLC Case

Rectangular Pulse-Shaped OTFS with Fractional Delay and Doppler Shift for MU-MIMO Systems

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