Accelerating software radio: Iris on the Zynq SoC.

The emergence of cognitive radio and software defined networks are signs of a network world that is much more dynamic. These kinds of systems support reconfiguration of the radio or the network to suit user demands and prevailing conditions so that bandwidth and other resources can be directed to where they are needed. As communication systems become ever more sophisticated, achieving high computational capacity while supporting a high level of flexibility becomes more of a challenge. In this paper we focus on the computational complexity and flexibility that will be required of future cognitive radios. The challenge is to achieve sufficient computational capacity, in particular for processing wide-band high-bitrate waveforms, within acceptable size, weight and power consumption limits while supporting significant flexibility. One method of addressing this problem is through the use of hybrid processing architectures that provide both programmability and performance. In particular we focus on a cognitive radio framework called Iris and explore how Xilinx's Zynq system-on-chip (SoC) can deliver the kind of performance that is needed of future cognitive radio systems. The Zynq SoC has the flexibility offered by an ARM based processing system (PS), while also having performance-orientated programmable logic (PL). The challenges of multi-core programming on embedded platforms and the difficulties of accelerating the cognitive radio functionality in the PL are discussed.