WCDMA for UMTS: Radio Access for Third Generation Mobile Communications
WCDMA for UMTS: Radio Access for Third Generation Mobile Communications
Uplink UMTS network design: an integrated approach
Computer Networks: The International Journal of Computer and Telecommunications Networking
A tabu search algorithm for the global planning problem of third generation mobile networks
Computers and Electrical Engineering
Automated optimization of service coverage and base station antenna configuration in UMTS networks
IEEE Wireless Communications
Planning UMTS base station location: optimization models with power control and algorithms
IEEE Transactions on Wireless Communications
Planning reliable UMTS terrestrial access networks
IEEE Communications Magazine
Introducing automated procedures in 3G network planning and optimization
Journal of Systems and Software
Automatic planning of 3G UMTS all-IP release 4 networks with realistic traffic
Computers and Operations Research
| Hi-index | 0.00 |
The 3G universal mobile telecommunications system (UMTS) planning problem is combinatorially explosive and difficult to solve optimally, though solution methods exist for its three main subproblems (cell, access network, and core network planning). We previously formulated the entire problem as a single integrated mixed-integer linear program (MIP) and showed that only small instances of this global planning problem can be solved to optimality by a commercial MIP solver within a reasonable amount of time (St-Hilaire, Chamberland, & Pierre, 2006). Heuristic methods are needed for larger instances. This paper provides the first complete formulation for the heuristic sequential method (St-Hilaire, Chamberland, & Pierre, 2005) that re-partitions the global formulation into the three conventional subproblems and solves them in sequence using a MIP solver. This greatly improves the solution time, but at the expense of solution quality. We also develop a new hybrid heuristic that uses the results of the sequential method to generate constraints that provide tighter bounds for the global planning problem with the goal of reaching the provable optimum solution much more quickly. We empirically evaluate the speed and solution accuracy of four solution methods: (i) the direct MIP solution of the global planning problem, (ii) a local search heuristic applied to the global planning problem, (iii) the sequential method and (iv) the new hybrid method. The results show that the sequential method provides very good results in a fraction of the time needed for the direct MIP solution of the global problem, and that optimum results can be provided by the hybrid heuristic in greatly reduced time.