Applications of Multi-Objective Optimization Techniques in Radio Resource Scheduling of Cellular Communication Systems

Novel objectives such as very low outage, high capacity, and high throughput are major challenging problems in radio resource management of mobile communication systems. More specifically, in radio resource scheduling (RRS), the aim is how to optimize available resources such as transmission power and data rate to achieve certain targeted objectives. Conventional RRS algorithms are based on optimizing one objective while keeping others as constraints. This paper proposes a novel distributed RRS algorithm based on analytic multi-objective optimization. The proposed algorithm relaxes the constraints and jointly optimizes all the required objectives. Infinity set of optimal solutions, called Pareto optimal, is obtained. Each solution in the set is optimal in a specific sense. The decision maker selects the required solution that fulfills the network requirements and conditions. Some of the conventional RRS algorithms are special cases of our multi-objective based algorithm. Detailed mathematical analysis of the proposed algorithm is given. Simulation results show the behavior of the proposed algorithm as well as its advantages over conventional algorithms.

[1]  I. Hartimo,et al.  Fully distributed power control algorithm with one bit signaling and nonlinear error estimation [mobile radio systems] , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[2]  Seong-Jun Oh,et al.  Optimal resource allocation in multiservice CDMA networks , 2003, IEEE Trans. Wirel. Commun..

[3]  Lei Song,et al.  Hierarchical SIR and rate control on the forward link for CDMA data users under delay and error constraints , 2001, IEEE J. Sel. Areas Commun..

[4]  Heikki N. Koivo,et al.  Multi-objective totally distributed power and rate control for wireless communications , 2003, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[5]  Kit Po Wong,et al.  Hybrid GA/SA algorithms for evaluating trade-off between economic cost and environmental impact in generation dispatch , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[6]  Mohammed Elmusrati Radio resource scheduling and smart antennas in cellular CDMA communication systems , 2004 .

[7]  Jack M. Holtzman,et al.  Power control and resource management for a multimedia CDMA wireless system , 1995, Proceedings of 6th International Symposium on Personal, Indoor and Mobile Radio Communications.

[8]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[9]  Mohamed-Slim Alouini,et al.  Coded Communication over Fading Channels , 2005 .

[10]  Sajal K. Das,et al.  An efficient multi-objective QoS-routing algorithm for wireless multicasting , 2002, Vehicular Technology Conference. IEEE 55th Vehicular Technology Conference. VTC Spring 2002 (Cat. No.02CH37367).

[11]  Ajay K. Ray,et al.  APPLICATIONS OF MULTIOBJECTIVE OPTIMIZATION IN CHEMICAL ENGINEERING , 2000 .

[12]  M. Elmusrati,et al.  On downlink throughput maximization in DS-CDMA systems , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[13]  Jens Zander,et al.  Constrained power control in cellular radio systems , 1994, Proceedings of IEEE Vehicular Technology Conference (VTC).

[14]  Xiaoxin Qiu,et al.  On the performance of adaptive modulation in cellular systems , 1999, IEEE Trans. Commun..

[15]  Jens Zander,et al.  Distributed cochannel interference control in cellular radio systems , 1992 .

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

[17]  Heikki N. Koivo,et al.  Multiobjective Distributed Power Control Algorithm for CDMA Wireless Communication Systems , 2007, IEEE Transactions on Vehicular Technology.

[18]  Heikki N. Koivo,et al.  Multi-objective distributed power and rate control for wireless communications , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[19]  Johan Andersson,et al.  A survey of multiobjective optimization in engineering design , 2001 .

[20]  Sennur Ulukus,et al.  Throughput maximization in CDMA uplinks using adaptive spreading and power control , 2000, 2000 IEEE Sixth International Symposium on Spread Spectrum Techniques and Applications. ISSTA 2000. Proceedings (Cat. No.00TH8536).

[21]  Stephen P. Boyd,et al.  Joint optimization of communication rates and linear systems , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[22]  Xiaoxin Qiu,et al.  Throughput performance of adaptive modulation in cellular systems , 1998, ICUPC '98. IEEE 1998 International Conference on Universal Personal Communications. Conference Proceedings (Cat. No.98TH8384).

[23]  Jian-Bo Yang,et al.  Normal vector identification and interactive tradeoff analysis using minimax formulation in multiobjective optimization , 2002, IEEE Trans. Syst. Man Cybern. Part A.

[24]  Mahmoud Naghshineh,et al.  QoS-enabled broadband mobile access to wireline networks , 2002, IEEE Commun. Mag..

[25]  Carlos A. Coello Coello,et al.  A Short Tutorial on Evolutionary Multiobjective Optimization , 2001, EMO.

[26]  Heikki N. Koivo,et al.  Multi-objective distributed power control algorithm , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[27]  Roy D. Yates,et al.  A Framework for Uplink Power Control in Cellular Radio Systems , 1995, IEEE J. Sel. Areas Commun..

[28]  Rajeev Kumar,et al.  Topological design of communication networks using multiobjective genetic optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[29]  Chang Wook Ahn,et al.  QoS provisioning dynamic connection-admission control for multimedia wireless networks using a Hopfield neural network , 2004, IEEE Transactions on Vehicular Technology.

[30]  Mohamed-Slim Alouini,et al.  Digital Communication Over Fading Channels: A Unified Approach to Performance Analysis , 2000 .