Cochannel Interference Mitigation and Cooperative Processing in Downlink Multicell Multiuser MIMO Networks

By Hongyuan Zhang, Huaiyu Dai. EURASIP Journal on Wireless Communications and Networking, 2004

509 citations recorded by the source corpus.

Recently, the remarkable capacity potential of multiple-input multiple-output (MIMO) wireless communication systems was unveiled. The predicted enormous capacity gain of MIMO is nonetheless significantly limited by cochannel interference (CCI) in realistic cellular environments. The previously proposed advanced receiver technique improves the system performance at the cost of increased receiver complexity, and the achieved system capacity is still significantly away from the interference-free capacity upper bound, especially in environments with strong CCI. In this paper, base station cooperative processing is explored to address the CCI mitigation problem in downlink multicell multiuser MIMO networks, and is shown to dramatically increase the capacity with strong CCI. Both information-theoretic dirty paper coding approach and several more practical joint transmission schemes are studied with pooled and practical per-base power constraints, respectively. Besides the CCI mitigation potential, other advantages of cooperative processing including the power gain, channel rank/conditioning advantage, and macrodiversity protection are also addressed. The potential of our proposed joint transmission schemes is verified with both heuristic and realistic cellular MIMO settings.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ac0da1c9815764381f9671f1b0415c1950c8359d

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Citations in the corpus

Relay Architectures for 3GPP LTE-Advanced (2009, result): “To be fair, we also compare with an emerging transmission technique known as base station coordination [34–37].”
Networked MIMO with clustered linear precoding (2008, methodology): “Similar problems with per-antenna power constraints were studied in [45], [46], and the BTS coordination system with PBPC appeared in [13].”
Pilot Contamination and Precoding in Multi-Cell TDD Systems (2009, background): “/pilot reuse factor to maximize system throughput in the presence of pilot contamination. In the multi-cell scenario, there has been signiﬁcant work on utilizing coordination among base stations [12]–[15] when CSI is available. This existing body of work focuses on the gain that can be obtained thro”
Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013, background): “Ideally, all base stations can serve and coordinate interference to all users [125, 233, 321].”
A Dynamic Clustering Approach in Wireless Networks with Multi-Cell Cooperative Processing (2008, background): “An alternative very promising way of facing CCI is Multicell cooperative processing (MCP) [4]-[6].”
Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs (2015, background): “For example, in multicell systems, BS cooperation [131], [194], [210]–[219], also known as joint multicell processing [24], [194], has been advocated for the sake of transforming the MIMO interference channel and X channel to a number of cooperative multiuser MIMO channels.”
Foundations of User-Centric Cell-Free Massive MIMO (2020, methodology): “Cooperative downlink processing with multiantenna APs was studied by Zhang and Dai in [206].”
Multi-Cell MIMO Cooperative Networks: A New Look at Interference (2010, background): “data streams for all the active users or the received signals at all antennas are shared between the BSs via high-capacity backhaul links [113], [114], [115], [116], [117], [118].”
An overview of limited feedback in wireless communication systems (2008, background): “Base station coordination [231], [232], [280], also called network MIMO [107], creates base station coordination clusters to treat the system like a “super” MIMO system, lever-”