Adaptive Pilot Clustering in Heterogeneous Massive MIMO Networks
Rami Mochaourab, Emil Bj\"ornson, Mats Bengtsson

TL;DR
This paper introduces a distributed coalition formation approach using game theory to optimize pilot reuse in massive MIMO networks, significantly improving spectral efficiency in asymmetric deployments.
Contribution
It proposes a novel low-complexity, distributed coalition formation algorithm for adaptive pilot clustering based on individual stability in heterogeneous massive MIMO networks.
Findings
Fast convergence of the coalition formation algorithm
Substantial spectral efficiency gains over baseline schemes
Effective control of message exchange overhead
Abstract
We consider the uplink of a cellular massive MIMO network. Acquiring channel state information at the base stations (BSs) requires uplink pilot signaling. Since the number of orthogonal pilot sequences is limited by the channel coherence, pilot reuse across cells is necessary to achieve high spectral efficiency. However, finding efficient pilot reuse patterns is non-trivial especially in practical asymmetric BS deployments. We approach this problem using coalitional game theory. Each BS has a few unique pilots and can form coalitions with other BSs to gain access to more pilots. The BSs in a coalition thus benefit from serving more users in their cells, at the expense of higher pilot contamination and interference. Given that a cell's average spectral efficiency depends on the overall pilot reuse pattern, the suitable coalitional game model is in partition form. We develop a…
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