Steven W. Peters

Interference alignment via alternating minimization

Using interference alignment, it has been shown that the number of degrees of freedom in the interference channel scales linearly with the number of users. Unfortunately, closed-form solutions for interference alignment over constant-coefficient channels with more than 3 users are difficult to derive. This paper proposes an algorithm for interference alignment in the MIMO interference channel with an arbitrary number of users, antennas, or spatial streams. The algorithm is an alternating minimization over the precoding matrices at the transmitters and the interference subspaces at the receivers, and is proven to converge. Numerical results show how the algorithm is useful for simulation and can give insight into the limitations of interference alignment.

The future of WiMAX: Multihop relaying with IEEE 802.16j

Relaying and cooperation have re-emerged as important research topics in wireless communication over the past half-decade. Although multihop relaying for coverage extension in wireless networks is an old concept, it became practical only recently. Nowhere is this better illustrated than in the IEEE 802.16 working group, which has devoted a task group to incorporating relay capabilities in the foundation of mobile WiMAX-IEEE 802.16e-2005. Currently, this task group is in the process of finishing IEEE 802.16j, the multihop relay specification for 802.16. This amendment will be fully compatible with 802.16e-2005 mobile and subscriber stations, but a BS specific to 802.16j will be required for relays to operate. This article presents an introduction to the upcoming IEEE 802.16j amendment and provides insight about the obstacles that practical system designers face when incorporating relaying into a wireless broadband network.

Cooperative Algorithms for MIMO Interference Channels

Interference alignment (IA) is a transmission technique for exploiting all available degrees of freedom in the frequency- or time-selective interference channel with an arbitrary number of users. Most prior work on IA, however, neglects interference from other nodes in the network that are not participating in the alignment operation. This paper proposes three generalizations of IA for the multiple-antenna interference channel with multiple users that account for colored noise, which models uncoordinated interference. First, a minimum interference-plus-noise leakage (INL) algorithm is presented and shown to be equivalent to previous subspace methods when noise is spatially white or negligible. This algorithm results in orthonormal precoders that are desirable for practical implementation with limited feedback. A joint minimum mean square error design that jointly optimizes the transmit precoders and receive spatial filters is then proposed, whereas previous designs neglect the receive spatial filter. Finally, a maximum signal-to-interference-plus-noise ratio (SINR) algorithm is developed and proven to converge, unlike previous maximum SINR algorithms. The sum throughput of these algorithms is simulated in the context of a network with uncoordinated cochannel interferers that are not participating in the alignment protocol. It is found that a network with cochannel interference can benefit from employing precoders that are designed to consider that interference, but in extreme cases, such as when only one receiver has a large amount of interference, ignoring that the cochannel interference is advantageous.

Relay architectures for 3GPP LTE-advanced

The Third Generation Partnership Projects Long Term Evolution-Advanced is considering relaying for cost-effective throughput enhancement and coverage extension. While analog repeaters have been used to enhance coverage in commercial cellular networks, the use of more sophisticated fixed relays is relatively new. The main challenge faced by relay deployments in cellular systems is overcoming the extra interference added by the presence of relays. Most prior work on relaying does not consider interference, however. This paper analyzes the performance of several emerging half-duplex relay strategies in interference-limited cellular systems: one-way, two-way, and shared relays. The performance of each strategy as a function of location, sectoring, and frequency reuse are compared with localized base station coordination. One-way relaying is shown to provide modest gains over single-hop cellular networks in some regimes. Shared relaying is shown to approach the gains of local base station coordination at reduced complexity, while two-way relaying further reduces complexity but only works well when the relay is close to the handset. Frequency reuse of one, where each sector uses the same spectrum, is shown to have the highest network throughput. Simulations with realistic channel models provide performance comparisons that reveal the importance of interference mitigation in multihop cellular networks.

Maximum Sum-Rate Interference Alignment Algorithms for MIMO Channels

Alternating minimization algorithms are typically used to find interference alignment (IA) solutions for multiple-input multiple-output (MIMO) interference channels with more than K=3 users. For these scenarios many IA solutions exit, and the initial point determines which one is obtained upon convergence. In this paper, we propose a new iterative algorithm that aims at finding the IA solution that maximizes the average sum-rate. At each step of the alternating minimization algorithm, either the precoders or the decoders are moved along the direction given by the gradient of the sum-rate. Since IA solutions are defined by a set of subspaces, the gradient optimization is performed on the Grassmann manifold. The step size of the gradient ascent algorithm is annealed to zero over the iterations in such a way that during the last iterations only the interference leakage is being minimized and a perfect alignment solution is finally reached. Simulation examples are provided showing that the proposed algorithm obtains IA solutions with significant higher throughputs than the conventional IA algorithms.

The practical challenges of interference alignment

Interference alignment is a revolutionary wireless transmission strategy that reduces the impact of interference. The idea of interference alignment is to coordinate multiple transmitters so that their mutual interference aligns at the receivers, facilitating simple interference cancellation techniques. Since interference alignments inception, researchers have investigated its performance and proposed several improvements. Research efforts have been primarily focused on verifying interference alignments ability to achieve the maximum degrees of freedom (an approximation of sum capacity), developing algorithms for determining alignment solutions, and designing transmission strategies that relax the need for perfect alignment but yield better performance. This article provides an overview of the concept of interference alignment as well as an assessment of practical issues including performance in realistic propagation environments, the role of channel state information at the transmitter, and the practicality of interference alignment in large networks.

Nonregenerative MIMO Relaying With Optimal Transmit Antenna Selection

We derive optimal SNR-based transmit antenna selection rules at the source and relay for the nonregenerative half-duplex MIMO relay channel. While antenna selection is a suboptimal form of beamforming, it has the advantage that the optimization is tractable and can be implemented with only a few bits of feedback from the destination to the source and relay. We compare the bit error rate of optimal antenna selection at both the source and relay to other proposed beamforming techniques and propose methods for performing the necessary limited feedback.

The Feasibility of Interference Alignment Over Measured MIMO-OFDM Channels

Interference alignment (IA) has been shown to achieve the maximum achievable degrees of freedom in the interference channel. This results in sum rate scaling linearly with the number of users in the high signal-to-noise-ratio (SNR) regime. Linear scaling is achieved by precoding the transmitted signals to align interference subspaces at the receivers given channel knowledge of all transmit-receive pairs, effectively reducing the number of discernible interferers. The theory of IA was derived under assumptions about the richness of scattering in the propagation channel; practical channels do not guarantee such ideal characteristics. This paper presents the first experimental study of IA in measured multiple-input-multiple-output orthogonal frequency-division-multiplexing (MIMO-OFDM) interference channels. Our measurement campaign includes a variety of indoor and outdoor measurement scenarios at The University of Texas at Austin. We show that IA achieves the claimed scaling factors, or degrees of freedom, in several measured channel settings for a three-user two-antenna-per-node setup. In addition to verifying the claimed performance, we characterize the effect of Kronecker spatial correlation on sum rate and present two other correlation measures, which we show to be more tightly related to the achieved sum rate.

A current perspective on distributed antenna systems for the downlink of cellular systems

Providing uniformly high capacity in cellular systems is challenging due to fading, path loss, and interference. A partial solution to this problem is the deployment of distributed antenna systems, where transmission points are distributed throughout the cell using coax cable or fiber, instead of being centrally located on a single tower. This article reviews how distributed antenna systems are evolving to provide higher performance on the downlink in cellular systems. Research trends in distributed antennas for the downlink of cellular systems are described along with current progress on their integration into commercial wireless cellular standards. A key observation is that distributed antenna systems are tightly integrated into the cellular architecture, and incorporate physical layer technologies like MIMO communication and multiuser MIMO to provide higher data rates.

User Partitioning for Less Overhead in MIMO Interference Channels

This paper presents a study on multiple-antenna interference channels, accounting for general overhead as a function of the number of users and antennas in the network. The model includes both perfect and imperfect channel state information based on channel estimation in the presence of noise. Three low-complexity methods are proposed for reducing the impact of overhead in the sum network throughput by partitioning users into orthogonal groups. The first method allocates spectrum to the groups equally, creating an imbalance in the sum rate of each group. The second proposed method allocates spectrum unequally among the groups to provide rate fairness. Finally, geographic grouping is proposed for cases where some receivers do not observe significant interference from other transmitters. For each partitioning method, the optimal solution not only requires a brute force search over all possible partitions, but also requires full channel state information, thereby defeating the purpose of partitioning. We therefore propose greedy methods to solve the problems, requiring no instantaneous channel knowledge. Simulations show that the proposed greedy methods switch from time-division to interference alignment as the coherence time of the channel increases, and have a small loss relative to optimal partitioning only at moderate coherence times.