Group:Network Science Group
Title: Advances in Cognitive Radio Networks: A survey, Asymptotically Optimal Geometric
Speaker: Haisheng Tan, Xiaohong Hao University
Time: 2011-10-28 12:30-2011-10-28 14:00
Venue: FIT 1-203-5

Abstract:

Title: Advances in Cognitive Radio Networks: A survey

Abstract: 

With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization,under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years oncognitive radios.

In this talk, based on the survey by Wang and Liu. I will briefly introduce the background and some selected research outputs in the literature. Then, I will introduce the algorithmic problems in dynamic spectrum access we are working on and report some of our recent results.

Title: Asymptotically Optimal Geometric Mobile Ad-Hoc Routing. 

Abstract:

In this paper we present AFR, a new geometric mobile ad-hoc routing algorithm. The algorithm is completely distributed; nodes need to communicate only with direct neighbors in their transmission range. We show that if a best route has cost c, AFR fi nds a route and terminates with cost $O(c^2)$ in the worst case. AFR is the first algorithm with cost bounded by a function of the optimal route. We also give a tight lower bound by showing that any geometric routing algorithm has worst-case cost  (c2). Thus AFR is asymptotically optimal. We give a on-geometric algorithm  that also matches the lower bound, but needs some memory at each node. This establishes an intriguing trade-off between geometry and memory.

Because of the time time limitation, I might not cover the whole lecture but some interesting part of it.