MIMO Interference Alignment Over Correlated Channels with Imperfect CSI

Interference alignment (IA), given uncorrelated channel components and perfect channel state information, obtains the maximum degrees of freedom in an interference channel. Little is known, however, about how the sum rate of IA behaves at finite transmit power, with imperfect channel state information, or antenna correlation. This paper provides an approximate closed-form signal-to-interference-plus-noise-ratio (SINR) expression for IA over multiple-input-multiple-output (MIMO) channels with imperfect channel state information and transmit antenna correlation. Assuming linear processing at the transmitters and zero-forcing receivers, random matrix theory tools are utilized to derive an approximation for the post-processing SINR distribution of each stream for each user. Perfect channel knowledge and i.i.d. channel coefficients constitute special cases. This SINR distribution not only allows easy calculation of useful performance metrics like sum rate and symbol error rate, but also permits a realistic comparison of IA with other transmission techniques. More specifically, IA is compared with spatial multiplexing and beamforming and it is shown that IA may not be optimal for some performance criteria.Comment: 21 pages, 7 figures, submitted to IEEE Transactions on Signal Processin

User Arrival in MIMO Interference Alignment Networks

In this paper we analyze a constant multiple-input multiple-output interference channel where a set of active users are cooperating through interference alignment while a set of secondary users desire access to the channel. We derive the minimum number of secondary transmit antennas required so that a secondary user can use the channel without affecting the sum rate of the active users, under a zero-forcing equalization assumption. When the secondary users have enough antennas, we derive several secondary user precoders that approximately maximize the secondary users' sum rate without changing the sum rate of the active users. When the secondary users do not have enough antennas, we perform numerical optimization to find secondary user precoders that cause minimum degradation to the sum rate of the active users. Through simulations, we confirm that i) with enough antennas at the secondary users, gains equivalent to the case of all the users cooperating through interference alignment is obtainable, and ii) when the secondary users do not have enough antennas, large rate losses at the active users can be avoided.Comment: 17 pages, 6 figures, submitted to IEEE Transactions on Wireless Communication

Increasing the accuracy of brain functional maps through large deformation diffeomorphic metric mapping

The accuracy of the brain normalization method directly impacts the preciseness of statistical analysis of functional magnetic resonance imaging (fMRI) data. Furthermore, the study of the medial temporal lobe and cortical layer structures requires an accurate co-registration method due to large inter-subject variability. In this thesis, we first introduce a fully automated fMRI post-processing pipeline aimed to reduce the registration error during group studies and we will demonstrate its superiority over two widely used registration methods by conducting a comprehensive bleeding study using a synthesized fMRI data-set as well as surface-to-surface distance quantifications over both cortical and sub-cortical regions. Finally, we apply our processing pipeline to a functional MRI data-set of a schizophrenia study and show how accurate registration of hippocampus and inferior frontal gyrus structures can increase the accuracy of functional maps over these regions when performing group analysis

Designing MIMO interference alignment networks

textWireless networks are increasingly interference-limited, which motivates the development of sophisticated interference management techniques. One recently discovered approach is interference alignment, which attains the maximum sum rate scaling (with signal-to-noise ratio) in many network configurations. Interference alignment is not yet well understood from an engineering perspective. Such design considerations include (i) partial rather than complete knowledge of channel state information, (ii) correlated channels, (iii) bursty packet-based network traffic that requires the frequent setup and tear down of sessions, and (iv) the spatial distribution and interaction of transmit/receive pairs. This dissertation aims to establish the benefits and limitations of interference alignment under these four considerations. The first contribution of this dissertation considers an isolated group of transmit/receiver pairs (a cluster) cooperating through interference alignment and derives the signal-to-interference-plus-noise ratio distribution at each receiver for each stream. This distribution is used to compare interference alignment to beamforming and spatial multiplexing (as examples of common transmission techniques) in terms of sum rate to identify potential switching points between them. This dissertation identifies such switching points and provides design recommendations based on severity of the correlation or the channel state information uncertainty. The second contribution considers transmitters that are not associated with any interference alignment cooperating group but want to use the channel. The goal is to retain the benefits of interference alignment amid interference from the out-of-cluster transmitters. This dissertation shows that when the out-of-cluster transmitters have enough antennas, they can access the channel without changing the performance of the interference alignment receivers. Furthermore, optimum transmit filters maximizing the sum rate of the out-of-cluster transmit/receive pairs are derived. When insufficient antennas exist at the out-of-cluster transmitters, several transmit filters that trade off complexity and sum rate performance are presented. The last contribution, in contrast to the first two, takes into account the impact of large scale fading and the spatial distribution of the transmit/receive pairs on interference alignment by deriving the transmission capacity in a decentralized clustered interference alignment network. Channel state information uncertainty and feedback overhead are considered and the optimum training period is derived. Transmission capacity of interference alignment is compared to spatial multiplexing to highlight the tradeoff between channel estimation accuracy and the inter-cluster interference; the closer the nodes to each other, the higher the channel estimation accuracy and the inter-cluster interference.Electrical and Computer Engineerin