This paper proposes a linear interference alignment (IA) scheme which can be used for uplink channels in a general multicell multiuser MIMO cellular network. The proposed scheme aims to align interference caused by signals from a set of transmitters into a subspace which is established by the signals from only a subset of those transmitters, thereby effectively reducing the number of interfering transmitters. The total degrees of freedom (DoF) achievable by the proposed scheme is given in closed-form expression, and a numerical analysis shows that the proposed scheme can achieve the optimal DoF in certain scenarios and provides a higher total DoF than other related schemes in most cases.
For general multicell multiuser uplink channels, @cite_24 proposed a new scheme called unstructured IA scheme which appeared to provide a high DoF performance, but for a given uplink channel the feasibility of the scheme cannot be determined until the scheme is actually applied and checked by a numerical test. On the other hand, the IA scheme in @cite_2 aimed to align ICI into a one-dimensional subspace, and because this IA constraint was too stringent to be satisfied, only a fraction of the ICI could be aligned. This problem was then resolved in @cite_19 by consolidating ICI into a multi-dimensional subspace rather than a one-dimensional subspace. By extending the scheme in @cite_16 , which was designed only for three-cell multiuser uplink channels, the scheme in @cite_10 can be applied to a general uplink channel; however, its DoF performance decreases when the size of the uplink channel increases as the scheme can only suppress the interference caused by one interfering user regardless of the size of the uplink channel.
@cite_24 @cite_19 @cite_2 @cite_16 @cite_10
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We develop an interference alignment (IA) technique for a downlink cellular system. In the uplink, IA schemes need channel-state-information exchange across base-stations of different cells, but our downlink IA technique requires feedback only within a cell. As a result, the proposed scheme can be implemented with a few changes to an existing cellular system where the feedback mechanism (within a cell) is already being considered for supporting multi-user MIMO. Not only is our proposed scheme implementable with little effort, it can in fact provide substantial gain especially when interference from a dominant interferer is significantly stronger than the remaining interference: it is shown that in the two-isolated cell layout, our scheme provides four-fold gain in throughput performance over a standard multi-user MIMO technique. We also show through simulations that our technique provides respectable gain under a more realistic scenario: it gives approximately 28 gain for a 19 hexagonal wrap-around-cell layout. Furthermore, we show that our scheme has the potential to provide substantial gain for macro-pico cellular networks where pico-users can be significantly interfered with by the nearby macro-BS. In this paper, we propose a new way of interference management for cellular networks. We develop the scheme that approaches to interference-free degree-of-freedom (dof) as the number K of users in each cell increases. Also we find the corresponding bandwidth scaling conditions for typical wireless channels: multi-path channels and single-path channels with propagation delay. The scheme is based on interference alignment. Especially for more-than-two-cell cases where there are multiple non-intended BSs, we propose a new version of interference alignment, namely subspace interference alignment. The idea is to align interferences into multi-dimensional subspace (instead of one dimension) for simultaneous alignments at multiple non-intended BSs. The proposed scheme requires finite dimensions growing linearly with K, i.e., O(K). We consider a power control scheme for maximizing the information capacity of the uplink in single-cell multiuser communications with frequency-flat fading, under the assumption that the users attenuations are measured perfectly. Its main characteristics are that only one user transmits over the entire bandwidth at any particular time instant and that the users are allocated more power when their channels are good, and less when they are bad. Moreover, these features are independent of the statistics of the fading. Numerical results are presented for the case of single-path Rayleigh fading. We show that an increase in capacity over a perfectly-power controlled (Gaussian) channel can be achieved, especially if the number of users is large. By examining the bit error-rate with antipodal signalling, we show the inherent diversity in multiuser communications over fading channels. This paper considers the optimal uplink transmission strategy that achieves the sum-capacity in a multiuser multi-antenna wireless system. Assuming an independent identically distributed block-fading model with transmitter channel side information, beamforming for each remote user is shown to be necessary for achieving sum-capacity when there is a large number of users in the system. This result stands even in the case where each user is equipped with a large number of transmit antennas, and it can be readily extended to channels with intersymbol interference if an orthogonal frequency division multiplexing modulation is assumed. This result is obtained by deriving a rank bound on the transmit covariance matrices, and it suggests that all users should cooperate by each user using only a small portion of available dimensions. Based on the result, a suboptimal transmit scheme is proposed for the situation where only partial channel side information is available at each transmitter. Simulations show that the suboptimal scheme is not only able to achieve a sum rate very close to the capacity, but also insensitive to channel estimation error. 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 signifi