A graph theory based opportunistic link scheduling for wireless ad hoc networks

Taking advantage of the independent fading channel conditions among multiple wireless users, opportunistic transmissions schedule the user with the instantaneously best condition and thus increase the spectrum utilization efficiency of wireless networks. So far, most proposed opportunistic scheduling policies for ad hoc networks exploit local multiuser diversity, i.e., each transmitter selects its best receiver independently. However, due to co-channel interference, the decisions of neighboring transmitters are highly correlated. Furthermore, the neighboring links without a common sender also experience independent channel fading. Taking the contention relationship and the channel diversity among links into account, we extend the concept of multi-user diversity to a more generalized one, by which a set of senders cooperatively schedule the instantaneously and globally best out-going links, thus the spatial diversity of the channel variation can be further exploited. In this paper, we formulate the opportunistic scheduling problem with fairness requirements into an optimization problem and present its optimal solution, i.e., the optimal scheduling policy. We also propose GOS, a distributed Graph theory based and Opportunistic Scheduling algorithm, which modifies IEEE 802.11 protocol to implement the optimal scheduling policy. Theoretical analysis and simulation results both verify that our implementation achieves higher network throughput and provides better fairness support than the existing algorithms.

[1]  Patrick Thiran,et al.  Connectivity vs capacity in dense ad hoc networks , 2004, IEEE INFOCOM 2004.

[2]  Edward W. Knightly,et al.  OAR: An Opportunistic Auto-Rate Media Access Protocol for Ad Hoc Networks , 2005, Wirel. Networks.

[3]  Mario Gerla,et al.  Effectiveness of RTS/CTS handshake in IEEE 802.11 based ad hoc networks , 2003, Ad Hoc Networks.

[4]  Qian Zhang,et al.  Cooperative and opportunistic transmission for wireless ad hoc networks , 2007, IEEE Network.

[5]  Jun Zhao,et al.  On the Capacity of Wireless Ad-Hoc Network Basing on Graph Theory , 2005, ICN.

[6]  Mario Gerla,et al.  How effective is the IEEE 802.11 RTS/CTS handshake in ad hoc networks , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[7]  Hongqiang Zhai,et al.  Opportunistic media access control and rate adaptation for wireless ad hoc networks , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[8]  Haiyun Luo,et al.  A topology-independent wireless fair queueing model in ad hoc networks , 2005, IEEE Journal on Selected Areas in Communications.

[9]  Yuanyuan Yang,et al.  Contention-Based Prioritized Opportunistic Medium Access Control in Wireless LANs , 2006, 2006 IEEE International Conference on Communications.

[10]  Wanjiun Liao,et al.  Fair scheduling in mobile ad hoc networks with channel errors , 2005, IEEE Trans. Wirel. Commun..

[11]  David Tse,et al.  Opportunistic beamforming using dumb antennas , 2002, IEEE Trans. Inf. Theory.

[12]  Tomio Hirata,et al.  Approximation Algorithms for the Weighted Independent Set Problem , 2005, WG.

[13]  Yu Hong-yi,et al.  On the capacity of wireless ad-hoc network basing on graph theory , 2005 .

[14]  Jean C. Walrand,et al.  Fair end-to-end window-based congestion control , 2000, TNET.

[15]  Georgios B. Giannakis,et al.  Queuing with adaptive modulation and coding over wireless links: cross-Layer analysis and design , 2005, IEEE Transactions on Wireless Communications.

[16]  Yi Yang,et al.  Exploiting medium access diversity in rate adaptive wireless LANs , 2004, MobiCom '04.

[17]  Brahim Bensaou,et al.  On max-min fairness and scheduling in wireless ad-hoc networks: analytical framework and implementation , 2001, MobiHoc.