Homotopy Continuation for Spatial Interference Alignment in Arbitrary MIMO X Networks

Abstract

In this paper we propose an algorithm to design interference alignment (IA) precoding and decoding matrices for arbitrary MIMO X networks. The proposed algorithm is rooted in the homotopy continuation techniques commonly used to solve systems of nonlinear equations. Homotopy methods find the solution of a target system by smoothly deforming the solution of a start system which can be trivially solved. Unlike previously proposed IA algorithms, the homotopy continuation technique allows us to solve the IA problem for both unstructured (i.e., generic) and structured channels such as those that arise when time or frequency symbol extensions are jointly employed with the spatial dimension. To this end, we consider an extended system of bilinear equations that include the standard alignment equations to cancel the interference, and a new set of bilinear equations that preserve the desired dimensionality of the signal spaces at the intended receivers. We propose a simple method to obtain the start system by randomly choosing a set of precoders and decoders, and then finding a set of channels satisfying the system equations, which is a linear problem. Once the start system is available, standard prediction and correction techniques are applied to track the solution all the way to the target system. We analyze the convergence of the proposed algorithm and prove that, for many feasible systems and a sufficiently small continuation parameter, the algorithm converges with probability one to a perfect IA solution. The simulation results show that the proposed algorithm is able to consistently find solutions achieving the maximum number of degrees of freedom (DoF) in a variety of MIMO X networks with or without symbol extensions. Further, the algorithm provides insights into the feasibility of IA in MIMO X networks for which theoretical results are scarce.

Homotopy Continuation for Sensor Networks Self-Calibration

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Experimental evaluation of flexible duplexing in multi-tier MIMO networks

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Power Minimization in Multi-tier Networks with Flexible Duplexing

“…Several studies on the benefits of flexible duplexing have been recently carried out, relying on different figures of merit. Most of the existing works assume that a fixed UL/DL combination is given, and present an analysis in terms of multiplexing gain [4][5][6], or in terms of throughput [7][8][9][10][11]. A frame structure for interference mitigation can be found in [12], and flexible duplexing is further proposed as a candidate for evaluation in real deployments in [13].…”