Abstract
In this paper, we design receivers for filter bank multicarrier-based (FBMC-based) massive MIMO considering practical aspects such as channel estimation and equalization. In particular, we propose a spectrally efficient pilot structure and a channel estimation technique in the uplink to jointly estimate all the users’ channel impulse responses. We mathematically analyze our proposed channel estimator and find the statistics of the channel estimation errors. These statistics are incorporated into our proposed equalizers to deal with the imperfect channel state information (CSI) effect. We revisit the channel equalization problem for FBMC-based massive MIMO, address the shortcomings of the existing equalizers in the literature, and make them more applicable to practical scenarios. The proposed receiver in this paper consists of two stages. In the first stage, a linear combining of the received signals at the base station (BS) antennas provides a coarse channel equalization and removes any multiuser interference. In the second stage, a per subcarrier fractionally spaced equalizer (FSE) takes care of any residual distortion of the channel for the user of interest. We propose an FSE design based on the equivalent channel at the linear combiner output. This enables the applicability of our proposed technique to small and/or distributed antenna setups such as cell-free massive MIMO. Finally, the efficacy of the proposed techniques is corroborated through numerical analysis.
Highlights
T HE emergence of new applications and technologies such as high data rate holographic communications and low latency high mobility communications for autonomous driving, as well as massive machine-type communications, has marked a new era in communications, [1]
The main contributions of this paper are the following; (i) We propose a joint multiuser and spectrally efficient channel estimation technique for the uplink of FBMCbased networks that is applicable to massive MIMO with both co-located and distributed antennas; (ii) We revisit the channel equalization problem in filter bank multicarrier (FBMC)-based massive MIMO and propose a practical two-stage equalization technique that is highly effective in massive MIMO with both co-located and distributed antenna setups; (iii) We derive the statistical characteristics of the estimation errors of our proposed channel estimator and incorporate them into our proposed equalizers to tackle the imperfect channel state information (CSI) effects
In the minimum mean square error (MMSE) combiner case, we argue that as N grows large, ση2 will become negligible when compared to N + N σe2f and, MMSE combiner will converge to the zero forcing (ZF) combiner which in the asymptotic regime is similar to the maximum ratio combining (MRC)
Summary
T HE emergence of new applications and technologies such as high data rate holographic communications and low latency high mobility communications for autonomous driving, as well as massive machine-type communications, has marked a new era in communications, [1]. The authors in [11] and [12] propose time domain channel estimation techniques where guard symbols are required to separate different users’ pilots This leads to a spectral efficiency loss and limitations in terms of latency, especially as the number of users scales up. To address the aforementioned issues for channel estimation and meet the stringent latency requirements of future networks, in this paper, we propose a pilot structure and a time domain channel estimation method for FBMC-based massive MIMO.
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