22-12-2012, 05:53 PM
Interference Management for Future Wireless Networks
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Introduction
Future wireless systems are characterized by large user-capacity, high speed, and high reliability. Yet, fading and interference in wireless networks render these design objectives challenging. While the development of diversity technologies such as MIMO, cooperative communications, relaying and multi-user diversity, partially address wireless fading (and can in some circumstances even be utilized for increased performance), truly efficient strategies for combating fading or further exploiting multi-user interference are lacking, at least until very recent years.
One efficient interference mitigation approach is joint multi-cell processing (normally referred to as CoMP: coordinated multiple point processing) [1], [2], [3]. Figure 1 shows a group of mobile terminals lie close to the edges of cell boundaries. When they access the different base station by non-orthogonal channels, their signals may interfere with each other. Joint processing across multi-cell, supported by the fiber backhaul can greatly reduce the interference. Significant gains are also possible with relatively low degrees of cooperation between the cells, for example by exchanging a limited amount of information related to the scheduling and pre-coding used for the terminals that suffer most of the intercell interference. In such systems, it is interesting to study algorithms that work in a distributed fashion over the network, reducing the need for backhaul information exchange. All interference suppression schemes that operate at the transmitter side require some amount of channel state information which has to be estimated at the receivers and fed back to the transmitters; this reduces the spectral efficiency. Therefore, it is interesting to study schemes that use a minimum number of feedback bits. The unavoidable delay between estimation and use of the channel state information may affect the convergence properties of the decentralized resource management algorithms.
Project description
This project aims at increasing the transmission efficiency, e.g., energy efficiency, error probability, throughput, and network capacity for interference-limited wireless networks. Specifically, the following aspects (or WPs) should be considered.
(1). Network coding for interference mitigation: We shall study how to mitigate or further exploit interference [7] by network coding approaches. Theoretical limits and practical design principles shall be studied, especially for the coding scheme in finite fields. Multi-dimensional codes with high complexity or one-dimensional codes with low complexity shall be studied. The rate-reliability tradeoff shall also be considered in the high SNR region. We shall also study the joint processing gain for the cellular networks with relaying. Finite-field or soft network coding schemes (superposition in particular) shall be compared for different scenarios. Information theoretic bounds and schemes inspired by positive coding theorems is also considered. Preliminary work in this direction includes [8] where new achievable rates for an uplink with collaborating base-stations were presented.
(2). Interference alignment [9]: Interference alignment is a new concept recently proposed for wireless networks. The motivation of interference alignment is the principle of do-no-harm rather than winner-takes-all. By coordinating the transmissions across a simple network the interference experienced at each receiver can be perfectly aligned and subsequently easily mitigated or removed. This strategy has so far mainly been investigated in terms of information-theoretic limits, and very little has been reported on the practical realization of interference alignment. In this work, we propose to conduct a thorough investigation into the application of interference alignment as a critical component in an overall interference management strategy. Since inter-cell interference in downlink transmission has been recognized as a key bottleneck issue, we particular focus on the downlink scenario. However, similar principles may be applied for uplink transmission.
(3) Performance and complexity assessment: The development of new communication technologies and concepts is greatly aided by the simultaneous development of analysis tools and techniques for assessing, and further improving, the performance and implementation complexity of these technologies. This is made even more pertinent by the often very high-dimensional signaling schemes envisioned in the interference mitigation technologies under development. We therefore propose the application of tools such as (but not limited to) large deviation theory to develop practically useful models for complexity and performance in interference mitigation technologies. Preliminary work in this direction includes [10] which consider low complexity joint decoding of several users in a MIMO-MAC setting.