Browsing by Subject "Interference channel"

Now showing 1 - 5 of 5

Capacity bounds for some Gaussian interference channels
(2018-05) Kim, Muryong; Vishwanath, Sriram; Baccelli, Francois; Dimakis, Georgios-Alex; Vikalo, Haris; Pisek, Eran
In current wireless networks, co-channel interference is the major limiting factor in achieving high spectral efficiency. The effective interference at receivers can be minimized by using advanced interference management techniques. Given channel conditions, what is the fundamental limit on maximum spectral efficiency we can achieve, and which encoding and decoding techniques achieve this limit? These research questions can be addressed as network information theory problems. In particular, the capacity of Gaussian interference channels is an important open problem dealing with these fundamental questions. Some special cases of the interference channels and their capacity regions are studied in this dissertation. For a class of partially connected interference channels, approximate capacity regions are characterized. The impact of topology, interference alignment, and the interplay between interference and noise are discussed. The results show that for these channels, genie-aided outer bounds are tight to within a constant gap from capacity. Near-optimal achievable schemes, based on rate-splitting and lattice alignment, are presented. The Gaussian X-channel is also an important Gaussian interference channel model. Lower and upper bounds on the sum-rate capacity are derived for this channel. The achievable schemes are based on layered lattice coding and compute-and-forward decoding. For different regimes of channel parameters, some combinations of encoding and decoding strategies are designed. For some range of channel parameters, the approximate sum-rate capacity is characterized to within a constant gap.
Designing MIMO interference alignment networks
(2012-08) Nosrat Makouei, Behrang; Heath, Robert W., Jr, 1973-; Andrews, Jeffrey G.; Evans, Brian L.; Hasenbein, John; Nettles, Scott; Vishwanath, Sriram
Wireless 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.
Interference alignment in real world environments
(2010-05) El Ayach, Omar; Heath, Robert W., Jr, 1973-; Sanghavi, Sujay
Interference alignment (IA) has been shown to provide all users of an interference channel with half the capacity achievable in an interference free point-to-point link resulting in linear sum capacity scaling with the number of users in the high SNR regime. The linear scaling is achieved by precoding 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 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. We show that IA achieves the claimed scaling factors in a wide variety of measured channel settings for a 3 user, 2 antennas per node setup. In addition to verifying the claimed performance, we characterize the effect of several realistic system imperfections such as channel estimation error, feedback delay, and channel spatial correlation, on sum rate performance.
On the capacity of multi-terminal systems : the interference and fading broadcast channels
(2011-05) Jafarian, Amin; Vishwanath, Sriram; de Veciana, Gustavo; Caramanis, Constantine; Voloch, Felipe; Erez, Uri
A central feature of wireless networks is multiple users sharing a common medium. Cellular systems are among the most common examples of such networks. The main phenomenon resulting from this inter-user interaction is interference, and thus analyzing interference networks is critical to determine the capacity of wireless networks. The capacity region of an interference network is defined as the set of rates that the users can simultaneously achieve while ensuring arbitrarily small probability of decoding error. It is an inherently hard problem to find the capacity region of interference networks. Even the capacity region of a general 2-user interference channel is a prominent open problem in information theory. This work's goal is to derive achievable regions that are improved over known results, and when possible, capacity theorems, for K user interference networks. Another multiuser channel that is commonly found in wireless systems is a broadcast channel. Broadcast channels stand side by side with Interference channels as the two of the most important channels for which capacity results are still not completely known. In this work we develop inner and outer bounds on the capacity region of fading broadcast channels, using which we find a part of the capacity region under some conditions. In summary, this work first presents coding arguments for new achievable rate regions and, where possible, capacity results for K-user interference networks. Second, it provides inner and outer-bounds for a class of fading broadcast channels.
Source and channel aware resource allocation for wireless networks
(2011-08) Jose, Jubin; Vishwanath, Sriram; Andrews, Jeffrey G.; Shakkottai, Sanjay; de Veciana, Gustavo; Morton, David
Wireless networks promise ubiquitous communication, and thus facilitate an array of applications that positively impact human life. At a fundamental level, these networks deal with compression and transmission of sources over channels. Thus, accomplishing this task efficiently is the primary challenge shared by these applications. In practice, sources include data and video while channels include interference and relay networks. Hence, effective source and channel aware resource allocation for these scenarios would result in a comprehensive solution applicable to real-world networks. This dissertation studies the problem of source and channel aware resource allocation in certain scenarios. A framework for network resource allocation that stems from rate-distortion theory is presented. Then, an optimal decomposition into an application-layer compression control, a transport-layer congestion control and a network-layer scheduling is obtained. After deducing insights into compression and congestion control, the scheduling problem is explored in two cross-layer scenarios. First, appropriate queue architecture for cooperative relay networks is presented, and throughput-optimality of network algorithms that do not assume channel-fading and input-queue distributions are established. Second, decentralized algorithms that perform rate allocation, which achieve the same overall throughput region as optimal centralized algorithms, are derived. In network optimization, an underlying throughput region is assumed. Hence, improving this throughput region is the next logical step. This dissertation addresses this problem in the context of three significant classes of interference networks. First, degraded networks that capture highly correlated channels are explored, and the exact sum capacity of these networks is established. Next, multiple antenna networks in the presence of channel uncertainty are considered. For these networks, robust optimization problems that result from linear precoding are investigated, and efficient iterative algorithms are derived. Last, multi-cell time-division-duplex systems are studied in the context of corrupted channel estimates, and an efficient linear precoding to manage interference is developed.