Cooperative Communications

(合作式通訊)

 

Most recent wireless communication systems available are concerned mostly with the transceiver design of a single transmitter and a single receiver. However, the performances that can be achieved by modern cellular systems are often limited by the reliability of the wireless medium. More specifically, the quality of our reception may vary dramatically depending on the location and the mobility of both the mobile and its neighboring objects. This large variation in performance often causes interruption in communication and a bad quality of service. As the proportion of multimedia contents gradually increase in the wireless traffic, the reliability of the communication link becomes more and more important. Although higher layer networking protocols can provide a certain level of quality guarantee, the improvement is still limited by the reliability provided through the physical layer design.

 

The main idea of cooperative communications is to have multiple wireless terminals cooperate in transmitting or receiving information. The advantage is rather intuitive: the probability that all the cooperating users experience bad channels simultaneously is exponentially smaller than the probability of that for a single user. This is a form of distributed spatial diversity which is analogous to that of multiple antennas. However, there are several challenges in this area of research. For example: (1) the cooperation requires coordination among users that may occupy communication resources that can otherwise be used to increase the data rate, therefore, the problem is how to design a transmission or signaling for coordination such that the improvement in data rate or reliability is increased even with the additional use of communication resources. (2) Another interesting question is: Who should we cooperate with? Ideally, every user wants to cooperate with the user that possesses the best channel, however, the inter-user channel may not allow one to do so and the fairness may also be sacrificed. It is interesting to see, what the ideal tradeoffs for such systems are. (3) What are the additional advantages that we can explore when we increase the diversity in frequency, in time or in coding? The interesting problems to explore goes on and on.

 

Several references on this subject is listed below:

*     A. Nosratinia, T.E. Hunter and A. Hedayat,  Cooperative communication in wireless networks, IEEE Communications Magazine, Volume 42,  Issue 10,  Oct. 2004 Page(s):74 - 80

*     A. Sendonaris, E. Erkip and B. Aazhang. User cooperation diversity-Part I: System description. IEEE Transactions on Communications, vol. 51, no. 11, pp. 1927-1938, November 2003.

*     A. Sendonaris, E. Erkip and B. Aazhang. User cooperation diversity-Part II: Implementation aspects and performance analysis. IEEE Transactions on Communications, vol.  51, no. 11, pp. 1939-1948, November 2003.

*     J. N. Laneman and G. W. Wornell, Distributed Space-Time Coded Protocols for Exploiting Cooperative Diversity in Wireless Networks, IEEE Trans. Inform. Theory, vol. 49, no. 10, pp. 2415-2525, Oct. 2003.

*     J. N. Laneman, D. N. C. Tse, and G. W. Wornell, ``Cooperative Diversity in Wireless Networks: Efficient Protocols and Outage Behavior,'' IEEE Trans. Inform. Theory, vol. 50, no. 12, pp. 3062-3080, Dec. 2004.

 

 

 

Wireless Sensor Networks

(無線感測網路)

 

 

Wireless sensor networks typically consists of a group of small miniature devices that are able to sense the environment, process the observations and communicate to coordinate a common response. This is a wide and exciting topic that has received a new wave of interest in recent years, in all areas of engineering. Specifically, we are interested in the communication and signal processing aspect of this problem.

 

Sensor networks are often assumed to be deployed in massive scale to perform pervasive monitoring and computing of the environment, which provides an interface for closely integrating our every-day lives with the natural world. The major challenges of a sensor network are the limited energy resources at each node and the scalability of the communications and the computations. In fact, it has been shown that the point-to-point per node throughput of a wireless network vanishes rapidly with the number of nodes in the network. This is a pessimistic result that has hindered the development of dense wireless networks. However, in sensor networks, the observations at each sensor are often highly correlated and the computation is often performed for a common purpose. Therefore, the highly redundant information contained in the sensors’ messages can be utilized to reduce the communication cost of the network. In this sense, there is a significant difference between wireless sensor nodes and that of conventional wireless ad hoc networks. Therefore, it is important to develop both energy efficient and bandwidth efficient strategies for the sensors to achieve their common goal or to efficiently communication their local observations in a compressed form.

 

There are many open problems concerning wireless sensor systems. Specifically, I am interested in topics related to distributed data compression, data gathering strategies, distributed detection, localization and energy-efficiency through sleep-wake algorithms.

 

There is a vast literature on this topic, some survey articles are listed below:

 

*    Wayne Manges., It's Time for Sensors to Go Wireless. Part 1: Technological Underpinnings., Sensors Magazine., April 1999

*    Wayne Manges., It's Time for Sensors to Go Wireless. Part 2: Take a Good Technology and Make It an Economic Success, Sensors Magazine., May 1999

*    M. Tubaishat and S. Madria., Sensor Networks: an Overview., IEEE Potentials, 22, 2, 20-23, April 2003

*    I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci., A Survey on Sensor Networks., IEEE Communication Magazine, August 2002

 

 

 

 

Network Information Theory

(網路消息理論)

 

 

With all in mind, I am certainly interested in the fundamental theory of communications and networking. In particular, I am interested in looking at multi-user systems from the information-theoretic point of view. This involves fundamental research on source coding, such as Distributed Source Coding, Multiple Description Coding, Successive Refinement Coding; and, also in channel coding, such as Broadcasting, Multiple Access, Relay Transmissions. Extending from the conventional theory that often requires long blocks of data to achieve the coding efficiency, I am particularly interested in looking at single letter coding strategies or, in other words, uncoded transmissions of information.