A Coordinated Approach to Channel Estimation in Large-Scale Multiple-Antenna Systems

By Haifan Yin, David Gesbert, Miltiades Filippou, Yingzhuang Liu. IEEE Journal on Selected Areas in Communications, 2012

1,164 citations recorded by the source corpus.

This paper addresses the problem of channel estimation in multi-cell interference-limited cellular networks. We consider systems employing multiple antennas and are interested in both the finite and large-scale antenna number regimes (so-called "massive MIMO"). Such systems deal with the multi-cell interference by way of per-cell beamforming applied at each base station. Channel estimation in such networks, which is known to be hampered by the pilot contamination effect, constitutes a major bottleneck for overall performance. We present a novel approach which tackles this problem by enabling a low-rate coordination between cells during the channel estimation phase itself. The coordination makes use of the additional second-order statistical information about the user channels, which are shown to offer a powerful way of discriminating across interfering users with even strongly correlated pilot sequences. Importantly, we demonstrate analytically that in the large-number-of-antennas regime, the pilot contamination effect is made to vanish completely under certain conditions on the channel covariance. Gains over the conventional channel estimation framework are confirmed by our simulations for even small antenna array sizes.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/d817d35d4dd8a79d7453b6ea400cc513249202a9

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Citations in the corpus

RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials (2021, background): “With the increase in the number of elements, such vectors can be well approximated by the columns of the DFT matrix [37], [38].”
Millimeter-Wave Massive MIMO Communication for Future Wireless Systems: A Survey (2018, background): “As a critical factor with substantial impact on the performance of cellular networks [38], the fronthaul must provide high-capacity, high rate and low-latency connection between the small cells and the macrocells to support the explosive data traffic expected in 5G ultra-dense cellular networks [138”
What Will 5G Be? (2014, background): “We begin with the most fundamental aspect of the physical layer—the waveform—and then consider the evolution of cloud-based and virtualized network architectures, latency and control signaling, and energy efﬁciency.”
Pilot Reuse for Massive MIMO Transmission over Spatially Correlated Rayleigh Fading Channels (2015, methodology): “Similar channel covariance matrix decomposition for the ULA case was derived in [11] and [21], however, the result in Lemma 1 applies to the more general BS array conﬁgurations.”
Joint Spatial Division and Multiplexing for mm-Wave Channels (2013, methodology): “2 An approach that exploits the same directional structure of the channel covariance matrix used by JSDM, in order to eliminate pilot contamination in a multi-cell massive MIMO setting, was proposed concurrently and independently in [10].”
Channel Hardening and Favorable Propagation in Cell-Free Massive MIMO With Stochastic Geometry (2017, methodology): “The capacity of Massive MIMO systems with spatially correlated channels and imperfect CSI has been extensively analyzed in [17], [19]–[21].”
A Unified Transmission Strategy for TDD/FDD Massive MIMO Systems With Spatial Basis Expansion Model (2017, methodology): “By contrast, FDD reciprocity has not been reported either from covariance-based methods [18], [20] or CS-based methods [17], [21].”
Distributed Compressive CSIT Estimation and Feedback for FDD Multi-User Massive MIMO Systems (2014, background): “There is one important observation for massive MIMO systems, which can help to address the above issues.”
Massive MIMO: An Introduction (2015, neutral): “Considerable research is underway to mitigate these limitations [23–30].”
Millimeter Wave MIMO With Lens Antenna Array: A New Path Division Multiplexing Paradigm (2015, background): “For example, by utilizing the fact that there is limited angular spread for signals sent from the mobile users, the authors in [41] propose a channel covariance-based pilot assignment strategy to mitigate the pilot contamination problem in multi-cell massive MIMO systems.”
A Comprehensive Survey of Pilot Contamination in Massive MIMO—5G System (2016, methodology): “ACRONYMS AND TERMS 3GPP - 3rd generation partnership project AoA - angle-of-arrival BS - base station CP - conventional time-multiplexed pilot scheme CCI - co-channel interference CE - channel estimation CSI - channel state information DoA - direction-of-arrival DL - downlink EE - energy efficiency ”
Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, background): “angular spread and a user-location dependent mean angle in practice [32].”
Learning the MMSE Channel Estimator (2017, background): “The conditional MMSE estimate of the channel vector ht is [7], [15] E[ht |Y , δ] = W δyt (6)”
Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination (2019, methodology): “While this condition is unlikely to hold in practice (as explained earlier) a good rule-of-thumb is to assign pilots to the UEs such that tr(RjjkR j lk) is rather small for all pilot-sharing UEs [23].”
Spatial- and Frequency-Wideband Effects in Millimeter-Wave Massive MIMO Systems (2017, background): “Note that the proposed soft grouping strategy is different from the conventional hard grouping one [11], [15], [31] in that the latter requires users with overlapped signature to transmit over completely non-overlapped time intervals while ours allows users to transmit in an “interlock” way by purpo”