Collaborative Communications Research Group
Cooperative communications refers to the wireless system where users are allowed to cooperate either by relaying each other's data to the destination or, from the signal processing perspective, by forming a virtual antenna array to enhance the signal reliability. 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:
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.
The concept of cross-layered designs has existed for many decades but has become increasingly important in next generation wireless networks due to the demand for high speed high data rate communications. In the past, cross-layered frameworks often lead to untractable or simulation-based designs, which limits the applicability of the studies. To move forward in this area, it is important to arrive at clean formulations and theoretical results that will eventually facilitate the practical designs. Several cross-layered ideas that have been studied in the literature are such as using channel state and queue state information to increase the efficiency of MAC, routing or resource allocation policies or such as considering the importance of the transmitted data frame to provide more protection or to allocate more resources to the transmission.
We are interested in exploring these problems from an information theoretic point of view to avoid the complex interaction among a large number of parameters in real systems and, hopefully, to arrive at meaningful and fundamental design concepts.