Energy Aware Signal Processing for Software Defined Radio Baseband Implementation

The fast pacing diversity and evolution of wireless communications require a wide variety of baseband implementations within a short time-to-market. Besides, the exponentially increased design complexity and design cost of deep sub-micron silicon highly desire the designs to be reused as much as possible. This yields an increasing demand for reconfigurable/ programmable baseband solutions. Implementing all baseband functionalities on programmable architectures, as foreseen in the tier-2 SDR, will become necessary in the future. However, the energy efficiency of SDR baseband platforms is a major concern. This brings a challenging gap that is continuously broadened by the exploding baseband complexity. We advocate a system level approach to bridge the gap. Specifically, we fully leverage the advantages (programmability) of SDR platforms to compensate its disadvantages (energy efficiency). Highly flexible and dynamic baseband signal processing algorithms are designed and implemented to exploit the abundant dynamics in the environment and the user requirement. Instead of always performing the best effort, the baseband can dynamically and autonomously adjust its work load to optimize the average energy consumption. In this paper, we will introduce such baseband signal processing techniques optimized for SDR implementations. The methodology and design steps will be presented together with 3 representative case studies in HSDPA, WiMAX and 3GPP LTE.