Ergodic Interference Alignment

This paper develops a new communication strategy, ergodic interference alignment, for the K-user interference channel with time-varying fading. At any particular time, each receiver will see a superposition of the transmitted signals plus noise. The standard approach to such a scenario results in each transmitter-receiver pair achieving a rate proportional to 1/K its interference-free ergodic capacity. However, given two well-chosen time indices, the channel coefficients from interfering users can be made to exactly cancel. By adding up these two observations, each receiver can obtain its desired signal without any interference. If the channel gains have independent, uniform phases, this technique allows each user to achieve at least 1/2 its interference-free ergodic capacity at any signal-to-noise ratio. Prior interference alignment techniques were only able to attain this performance as the signal-to-noise ratio tended to infinity. Extensions are given for the case where each receiver wants a message from more than one transmitter as well as the "X channel" case (with two receivers) where each transmitter has an independent message for each receiver. Finally, it is shown how to generalize this strategy beyond Gaussian channel models. For a class of finite field interference channels, this approach yields the ergodic capacity region.Comment: 16 pages, 6 figure, To appear in IEEE Transactions on Information Theor

Interference management for Interference Channels: Performance improvement and lattice techniques

This thesis focuses on interference management methods for interference channels, in particular on interference alignment. The aim is to contribute to the understanding of issues such as the performance of the interference alignment scheme and lattice codes for interference channels. Interference alignment is studied from two perspectives. One is the signal space perspective where precoding methods are designed to align the interference in half of the received subspace. Cadambe and Jafar found precoding matrices to achieve the theoretical degrees of freedom. However, using an interference suppression technique over the Cadambe and Jafar scheme, yields poor performance. Thus, in this thesis precoding methods such as singular value decomposition and Tomlinson-Harashima precoding are proposed to improve performance. The second perspective is on the signal scale, where structured codes are used to align interference. For this, lattice codes are suitable. In this research, the problem was initially approached with a many-to-one interference channel. Using lattices, joint maximum-likelihood decoding of the desired signal and the sum of the interference signals is used, and the union bound of the error probability for user 1 is derived, in terms of the theta series. Later, a symmetric interference channel is studied. Jafar built a scheme for every level of interference, where interference was aligned and could be cancelled. In this thesis, Barnes-Wall lattices are used since they have a similar structure to the scheme proposed by Jafar, and it is shown to be possible to improve the performance of the technique using codes constructed with Barnes-Wall lattices. Finally, previous work has found the generalized degrees of freedom for a two-user symmetric interference channel using random codes. Here, we obtain the generalized degrees of freedom for that channel setting using lattice Gaussian distribution.Open Acces

Integer-forcing in multiterminal coding: uplink-downlink duality and source-channel duality

Interference is considered to be a major obstacle to wireless communication. Popular approaches, such as the zero-forcing receiver in MIMO (multiple-input and multiple-output) multiple-access channel (MAC) and zero-forcing (ZF) beamforming in MIMO broadcast channel (BC), eliminate the interference first and decode each codeword separately using a conventional single-user decoder. Recently, a transceiver architecture called integer-forcing (IF) has been proposed in the context of the MIMO Gaussian multiple-access channel to exploit integer-linear combinations of the codewords. Instead of treating other codewords as interference, the integer-forcing approach decodes linear combinations of the codewords from different users and solves for desired codewords. Integer-forcing can closely approach the performance of the optimal joint maximum likelihood decoder. An advanced version called successive integer-forcing can achieve the sum capacity of the MIMO MAC channel. Several extensions of integer-forcing have been developed in various scenarios, such as integer-forcing for the Gaussian MIMO broadcast channel, integer-forcing for Gaussian distributed source coding and integer-forcing interference alignment for the Gaussian interference channel. This dissertation demonstrates duality relationships for integer-forcing among three different channel models. We explore in detail two distinct duality types in this thesis: uplink-downlink duality and source-channel duality. Uplink-downlink duality is established for integer-forcing between the Gaussian MIMO multiple-access channel and its dual Gaussian MIMO broadcast channel. We show that under a total power constraint, integer-forcing can achieve the same sum rate in both cases. We further develop a dirty-paper integer-forcing scheme for the Gaussian MIMO BC and show an uplink-downlink duality with successive integer-forcing for the Gaussian MIMO MAC. The source-channel duality is established for integer-forcing between the Gaussian MIMO multiple-access channel and its dual Gaussian distributed source coding problem. We extend previous results for integer-forcing source coding to allow for successive cancellation. For integer-forcing without successive cancellation in both channel coding and source coding, we show the rates in two scenarios lie within a constant gap of one another. We further show that there exists a successive cancellation scheme such that both integer-forcing channel coding and integer-forcing source coding achieve the same rate tuple

Outage Probability and Outage-Based Robust Beamforming for MIMO Interference Channels with Imperfect Channel State Information

In this paper, the outage probability and outage-based beam design for multiple-input multiple-output (MIMO) interference channels are considered. First, closed-form expressions for the outage probability in MIMO interference channels are derived under the assumption of Gaussian-distributed channel state information (CSI) error, and the asymptotic behavior of the outage probability as a function of several system parameters is examined by using the Chernoff bound. It is shown that the outage probability decreases exponentially with respect to the quality of CSI measured by the inverse of the mean square error of CSI. Second, based on the derived outage probability expressions, an iterative beam design algorithm for maximizing the sum outage rate is proposed. Numerical results show that the proposed beam design algorithm yields better sum outage rate performance than conventional algorithms such as interference alignment developed under the assumption of perfect CSI.Comment: 41 pages, 14 figures. accepted to IEEE Transactions on Wireless Communication