ABSTRACT
Contents 8.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272 8.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272
8.2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272 8.2.2 HSPA Network Planning and Dimensioning . . . . . . . . . . . . . . . . 273 8.2.3 Chapter Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
8.3 Modeling and Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 8.3.1 The System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275
8.3.1.1 Preliminaries and Overview . . . . . . . . . . . . . . . . . . . . . . . 275 8.3.2 Coverage and CCH Power Consideration . . . . . . . . . . . . . . . . . . . 278 8.3.3 R99 Power Consideration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 8.3.4 HSDPA Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 8.3.5 Uplink Consideration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
8.4 Optimization Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 8.4.1 Optimization Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 8.4.2 Complexity Consideration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 8.4.3 Search Algorithms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284 8.4.4 Simulated Annealing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284 8.4.5 Configuration Adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286
8.5 A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 8.6 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
8.1 Overview Automated optimization of radio network configurations can be considered a cost-effective means to improve mobile broadband performance, provided that accurate spatial network information is available. This chapter addresses automated optimization of antenna configurations in evolved 3G networks featuring High-Speed Packet Access (HSPA). Detailed radio link and network models are described, together with performance metrics in terms of link models relating radio link quality to data rates. The network planning task is formulated as an optimization problem maximizing HSDPA throughput with HSUPA performance as a soft constraint, while taking into account resource sharing among common channels, HSPA, and Release 99 traffic. A search algorithm is developed to solve the resulting optimization problem effectively and time efficiently. Performance analysis for a realistic large-scale planning scenario is provided to demonstrate the benefit of the automated optimization approach and the impact of optimizing different antenna configuration parameters, including antenna tilt and azimuth. For example, cell-edge data rates are improved by more than 50% by adopting automated optimization compared to the baseline configuration, and the largest performance gain is achieved by means of electrical antenna tilting.
