Wireless Schedulers with Future Sight via Real-Time 3D Environment Mapping

This paper proposes a new wireless scheduling methodology which takes advantage of future predictions of data rate for the several users competing for physical access. Based on a system which allows low-cost 3D mapping of an environment in real-time, the predictions are obtained via either low-resolution path-loss prediction given the physical structure of the surroundings or by reference to data rates achieved by previous visitors to a locality. The proportional fair scheduling (PFS) metric is extended to include measures of the future rates users may achieve, leading to a new family of schedulers. They show useful fairness improvements over PFS in exchange for a small capacity loss, and allow a number of configuration options and a range of trade-offs between fairness and capacity.

[1]  Vinko Erceg.  IEEE P802.11 Wireless LANs TGn Channel Models , 2004 .

[2]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[3]  U. Spagnolini,et al.  A Predictive Opportunistic Scheduler for 4G Wireless Systems , 2007, 2007 16th IST Mobile and Wireless Communications Summit.

[4]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

[5]  Walterio W. Mayol-Cuevas,et al.  Appearance Based Indexing for Relocalisation in Real-Time Visual SLAM , 2008, BMVC.

[6]  Gokhan Sahin.  Predictive Scheduling in Rate-Adaptive Multi-user Relay Channels with Reconfiguration Delays , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems Workshops.

[7]  Chung Gu Kang,et al.  Multi-Phase Predictive Proportional Fairness Scheduling for a Multi-Channel Wireless Packet System , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[8]  Hyeong-Ah Choi,et al.  Predictive scheduling in multi-carrier wireless networks with link adaptation , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[9]  M. Uchida.  Information theoretic aspects of fairness criteria in network resource allocation problems , 2007, Valuetools 2007.

[10]  Jerzy Konorski,et al.  Capacity-Fairness Performance of an Ad Hoc IEEE 802.11 WLAN with Noncooperative Stations , 2007, Networking.

[11]  David Gesbert,et al.  Channel predictive proportional fair scheduling , 2008, IEEE Transactions on Wireless Communications.

[12]  Walterio W. Mayol-Cuevas,et al.  Discovering Higher Level Structure in Visual SLAM , 2008, IEEE Transactions on Robotics.

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

[14]  J. P. McGeehan,et al.  The application of a deterministic ray launching algorithm for the prediction of radio channel characteristics in small-cell environments , 1994 .

[15]  Jp McGeehan,et al.  A ray tracing algorithm for microcellular and indoor propagation modelling , 1995 .