Implementera radiobasstationers kontrollplans funktioner med grafikprocessor

Today more devices are being connected to the Internet via mobile networks. With more devices in mobile networks, the workload on radio base stations increases. Radio base stations must be energy efficient and cheap which makes high-performance central processing units (CPUs) a bad alternative to meet the increasing workload. An alternative could be a graphics processing unit (GPU) which have a different hardware architecture more suitable for data parallel problems. This thesis has investigated the parallelisation possibilities in the user-equipment handling part of radio base stations, and the aim was to use a GPU to take advantage of the parallelism. The investigation found a mixed pipeline and data parallelism in user-equipment handling. A parallelism suitable for a graphics processing unit (GPU) execution. The tasks which handle user-equipment were divided into smaller communication-free sub-tasks. Sub-task batches of user-equipment were collected and offloaded to a GPU. A peak throughput gain of 62.2 times over the single-threaded CPU was achieved, but with an impact on latency with more than a magnitude. The latency was for all workloads at least 1.24 higher for the GPU implementations compared to the CPU implementations. A radio base station with many more user-equipment than the once existing today was simulated. For this radio base station, a gain of 14.0 times the single-threaded CPU was achieved, while the latency increased by 2.4 times. To really make use of a GPU implementation the number of user-equipment, the load, must be higher than in existing radio base stations today.