Exploiting information theory for adaptive mobility and resource management in future cellular networks

We utilize tools from information theory to develop adaptive algorithms for two key problems in cellular networks: location tracking and resource management. The use of information theory is motivated by the fundamental observation that overheads in many aspects of mobile computing can be traced to the randomness or uncertainty in an individual user's movement behavior. We present a model-independent information-theoretic approach for estimating and managing this uncertainty, and relate it to the entropy or information content of the user's movement process. Information-theoretic mobility management algorithms are very simple, yet reduce overhead by /spl sim/80 percent in simulated scenarios by optimally adapting to each individual's movement. These algorithms also allow for flexible tradeoff between location update and paging costs. Simulation results demonstrate how an information-theory-motivated resource provisioning strategy can meet QoS bounds with very small wastage of resources, thus dramatically reducing the overall blocking rate.

[1]  Archan Misra,et al.  A rate-distortion framework for information-theoretic mobility management , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[2]  Ian F. Akyildiz,et al.  A dynamic location management scheme for next-generation multitier PCS systems , 2002, IEEE Trans. Wirel. Commun..

[3]  Sajal K. Das,et al.  LeZi-Update: An Information-Theoretic Framework for Personal Mobility Tracking in PCS Networks , 2002, Wirel. Networks.

[4]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[5]  Ian F. Akyildiz,et al.  A resource estimation and call admission algorithm for wireless multimedia networks using the shadow cluster concept , 1997, TNET.

[6]  Archan Misra,et al.  An information-theoretic framework for optimal location tracking in multisystem 4G wireless networks , 2004, IEEE INFOCOM 2004.

[7]  Abraham Lempel,et al.  Compression of individual sequences via variable-rate coding , 1978, IEEE Trans. Inf. Theory.

[8]  Ian H. Witten,et al.  Data Compression Using Adaptive Coding and Partial String Matching , 1984, IEEE Trans. Commun..

[9]  Roy D. Yates,et al.  Minimizing the average cost of paging under delay constraints , 1995, Wirel. Networks.

[10]  Sajal K. Das,et al.  Coping with uncertainty in mobile wireless networks , 2004, 2004 IEEE 15th International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE Cat. No.04TH8754).

[11]  Amotz Bar-Noy,et al.  Mobile users: To update or not to update? , 1995, Wirel. Networks.

[12]  Nariman Farvardin,et al.  Optimum quantizer performance for a class of non-Gaussian memoryless sources , 1984, IEEE Trans. Inf. Theory.

[13]  John G. Proakis,et al.  Digital Communications , 1983 .

[14]  Victor C. M. Leung,et al.  Mobility-based predictive call admission control and bandwidth reservation in wireless cellular networks , 2002, Comput. Networks.

[15]  Amotz Bar-Noy,et al.  Mobile users: To update or not to update? , 1994, Proceedings of INFOCOM '94 Conference on Computer Communications.