Energy efficient design of an adaptive switching algorithm for the iterative-MIMO receiver

An efficient design dedicated for iterative-multiple-input multiple-output (MIMO) receiver systems is now imperative in our world since data demands are increasing tremendously in wireless networks. This puts a massive burden on the signal processing power especially in small receiver systems where power sources are often shared or limited. This thesis proposes an attractive solution to both the wireless signal processing and the architectural implementation design sides of the problem. A novel algorithm, dubbed the Adaptive Switching Algorithm, is proven to not only save more than a third of the energy consumption in the algorithmic design, but is also able to achieve an energy reduction of more than 50% in terms of processing power when the design is mapped onto state-of-the-art programmable hardware. Simulations are based in MatlabTM using the Monte Carlo approach, where multiple additive white Gaussian noise (AWGN) and Rayleigh fading channels for both fast and slow fading environments were investigated. The software selects the appropriate detection algorithm depending on the current channel conditions. The design for the hardware is based on the latest field programmable gate arrays (FPGA) hardware from Xilinx R , specifically the Virtex-5 and Virtex-7 chipsets. They were chosen during the experimental phase to verify the results in order to examine trends for energy consumption in the proposed algorithm design. Savings come from dynamic allocation of the hardware resources by implementing power minimization techniques depending on the processing requirements of the system. Having demonstrated the feasibility of the algorithm in controlled environments, realistic channel conditions were simulated using spatially correlated MIMO channels to test the algorithm’s readiness for real-world deployment. The proposed algorithm is placed in both the MIMO detector and the iterative-decoder blocks of the receiver. When the final full receiver design setup is implemented, it shows that the key to energy saving lies in the fact that both software and hardware components of the Adaptive Switching Algorithm adopt adaptivity in the respective designs. The detector saves energy by selecting suitable detection schemes while the decoder provides adaptivity by limiting the number of decoding iterations, both of which are updated in real-time. The overall receiver can achieve more than 70% energy savings in comparison to state-of-the-art iterative-MIMO receivers and thus it can be concluded that this level of ‘intelligence’ is an important direction towards a more efficient iterative-MIMO receiver designs in the future