Determining the feasibility conditions for vector space interference alignment in the K-user MIMO interference channel with constant channel coefficients has attracted much recent attention yet remains unsolved. The main result of this paper is restricted to the symmetric square case where all transmitters and receivers have N antennas, and each user desires d transmit dimensions. We prove that alignment is possible if and only if the number of antennas satisfies N>= d(K+1) 2. We also show a necessary condition for feasibility of alignment with arbitrary system parameters. An algebraic geometry approach is central to the results.
The problem we consider, of maximizing dof using vector space strategies for the @math -user MIMO IC with finite number of transmit and receive antennas, has received significant attention in the last several years. Cadambe and Jafar @cite_2 considered the problem for @math users and @math antennas, and showed that @math dof was achievable. For more than @math users or @math they assumed an infinite number of parallel channels and applied their main @math result. @cite_10 posed the problem of determining feasibility of alignment, but left the problem unanswered and proposed a heuristic iterative numerical algorithm.
@cite_10 @cite_2
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This paper investigates the symmetric degrees of freedom (DoF) of MIMO cellular networks with G cells and K users per cell, having N antennas at each base station and M antennas at each user. In particular, we investigate achievability techniques based on either decomposition with asymptotic interference alignment (IA) or linear beamforming schemes, and show that there are distinct regimes of (G,K,M,N) where one outperforms the other. We first note that both one-sided and two-sided decomposition with asymptotic IA achieve the same degrees of freedom. We then establish specific antenna configurations under which the DoF achieved using decomposition based schemes is optimal by deriving a set of outer bounds on the symmetric DoF. For linear beamforming schemes, we first focus on small networks and propose a structured approach to linear beamforming based on a notion called packing ratios. Packing ratio describes the interference footprint or shadow cast by a set of transmit beamformers and enables us to identify the underlying structures for aligning interference. Such a structured beamforming design can be shown to achieve the optimal spatially normalized DoF (sDoF) of two-cell two-user cell network and the two-cell three-user cell network. For larger networks, we develop an unstructured approach to linear interference alignment, where transmit beamformers are designed to satisfy conditions for IA without explicitly identifying the underlying structures for IA. The main numerical insight of this paper is that such an approach appears to be capable of achieving the optimal sDoF for MIMO cellular networks in regimes where linear beamforming dominates asymptotic decomposition, and a significant portion of sDoF elsewhere. Remarkably, polynomial identity test appears to play a key role in identifying the boundary of the achievable sDoF region in the former case. Consider a MIMO interference channel whereby each transmitter and receiver are equipped with multiple antennas. The basic problem is to design optimal linear transceivers (or beamformers) that can maximize system throughput. The recent work [13] suggests that optimal beamformers should maximize the total degrees of freedom and achieve interference alignment in high SNR. In this paper we first consider the interference alignment problem in spatial domain and prove that the problem of maximizing the total degrees of freedom for a given MIMO interference channel is NP-hard. Furthermore, we show that even checking the achievability of a given tuple of degrees of freedom for all receivers is NP-hard when each receiver is equipped with at least three antennas. Moreover, in case where each transmitter and receiver use at most two antennas, the same problem is polynomial time solvable. Finally, we propose a distributed algorithm for transmit covariance matrix design, while assuming each receiver uses a linear MMSE beamformer. The simulation results show that the proposed algorithm outperforms the existing interference alignment algorithms in terms of system throughput. The feasibility condition of interference alignment (IA) for full-duplex (FD) multiple-input multiple-output (MIMO) cellular networks is considered. A necessary condition and a sufficient condition on the IA feasibility are established, characterizing the optimal sum degrees of freedom (DoF) for a broad class of network topologies. The necessary and sufficient condition is shown specially for a class of symmetric network topologies. The results demonstrate that FD operation at the base station with appropriate IA is able to improve the sum DoF than the conventional half-duplex operation. In this correspondence, we show that the exact number of spatial degrees of freedom (DOF) for a two user nondegenerate (full rank channel matrices) multiple-input-multiple-output (MIMO) Gaussian interference channel with M1, M2 antennas at transmitters 1, 2 and N1, N2 antennas at the corresponding receivers, and perfect channel knowledge at all transmitters and receivers, is min M1 + M2, N1 + M2, max(M1, N2), max(M2, N1) . A constructive achievability proof shows that zero forcing is sufficient to achieve all the available DOF on the two user MIMO interference channel. We also show through an example of a share-and-transmit scheme how the gains of transmitter cooperation may be entirely offset by the cost of enabling that cooperation so that the available DOF are not increased.