Interference Management in Future Wireless Networks for High Throughput, High Fairness and Low Energy Consumption

Visiting researcher: Dr Guixia Kang (BUPT)
Host researcher: Prof. Harald Haas (UoE)
Duration: 3 months
Status: Ongoing

Biography of the visiting researcher

Guixia Kang, Associate Professor at Beijing University of Posts and Telecommunications (BUPT), has expertise in the physical layer of 3G and B3G systems. She has been active in the research, development and standardization of 3G and beyond 3G (B3G) wireless communications systems as well as short range wireless communications. Since 2002 to 2004, she was a research scientist in the Future Radio Concept Department of Siemens, Munich, Germany. Currently, she is serving as the director of Wireless Transmission and Application Lab in Wireless Technology Innovation (WTI) Institute of BUPT. She is a member of ITU-R 8F - China Working Group. Meanwhile, she served as the TPC members of some of the international conferences such as IEEE ICC conference and IEEE WCNC conference. She was/is the project manager of several national projects such as Important National Science & Technology Specific Project, National 863 project, NSFC (Nature Science Foundation of China) project, etc. She is the author of an English book published by Shaker Verlag, Germany, two Chinese books, as well as the author or co-author of more than 50 journal and conference papers. She has issued 12 patents including an European patent. Besides, she has actively involved in the standarization of 3GPP、3GPP2 and ITU for the next generation wireless communications systems. Prof. Guixia Kang is a winner of “Beijing New Star of Science and Technology” and won the first prize of Science and Technology Award of China Communications Association.

Background and Motivation

With the continuing proliferation of wireless services driven by modern smart phones, it is essential that future wireless systems have to deliver significantly higher volumes of data resulting in significantly increased peak data rates. Clearly this is only possible by improving the system spectral efficiency given the limited and expensive radio frequency spectrum. Recently an additional constraint has gained considerable importance. This is the energy consumed by wireless networks. The target here is to reduce the total energy consumption of future networks. However, given that a minimum received energy per bit is required, and given that the data volume transmitted wirelessly will rise sharply in the future, this would suggest an “increase” in total energy consumed. One key to achieving higher data throughput while reducing the energy consumption is to dramatically reduce the interference in future wireless networks which are interference limited due to full frequency reuse and their hierarchical and self-organising structures.
In order to illustrate the importance of interference management let us consider the well known Shannon equation ,where B is the bandwidth, S is the received signal power, N is the noise and I is the interference in the system which is much larger than N. Reducing interference can be exploited in several different ways: (1) given a fixed S and B, reduced interference results in higher capacity (and, thus, higher spectral efficiency), (b) decreased interference enables us to lower the received signal power S given that B and C are to remain constant, (c) reducing interference below the noise level would let us reuse spectrum, i.e., increase B, originally belonging to other systems (cognitive radio), resulting in increased capacity as well as low energy consumption. In other words, we can either trade-off energy consumption for capacity or via cognitive radio technologies potentially achieve goals, lower energy consumption and higher throughput. In this collaborative research we will explore potential technologies that will (a) mitigate interference and (b) exploit the reduced interference to adaptively increase the throughput and/or decrease the energy consumptions. In this analysis we will consider 4G relevant network architectures such as femtocell deployment as well as distributed multiuser MIMO (multiple-input-multiple-output) transmission concepts such as CoMP (cooperative multipoint), and we will primarily focus on interference mitigation technologies in these systems.

Research Activities

This program aims at investigating interference management in next generation wireless networks, in particular LTE-Advanced. In this context, we would like to develop a novel algorithm to solve the hidden node problem in decentralized and self-organizing wireless CoMP networks. We will especially focus on minimum signaling overhead and energy efficiency. We will analytically study the proposed algorithm as well as carry out system level simulation based on existing simulators developed in both groups. Using these system level simulations we will evaluate and compare system spectral efficiency, energy efficiency and will apply the algorithm to a cognitive radio setup. Finally, we would like to test the algorithm in the testbed developed in WP4.


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