Design and Complexity Optimization of a New Digital IF for Software Radio Receivers With Prescribed Output Accuracy

Abstract

This paper studies the design, signal round-off noise, and complexity optimization of a new digital intermediate frequency (IF) architecture for a software radio receiver (SRR). The IF under study consists of digital filters with fixed coefficients, except for a limited number of multipliers required in the Farrow-based sampling rate converter (SRC). The fixed-coefficient filters can be implemented efficiently using sum-of-power-of-two (SOPOT) coefficients and the multiplier-block technique, which gives minimum adder realization. Apart from the multipliers required in the SRC, the digital IF can be implemented without any multiplications. While most multiplier- less filter design and realization methods address only the coefficient round-off problem by minimizing the number of SOPOT terms used, the proposed design methodology aims to minimize more realistic hardware complexity measure, such as adder cells and registers, of the digital IF subject to a given spectral and accuracy specifications. The motivation is that the complexity is closely related to the target output accuracy, which is specified statistically by its total output noise power generated by rounding the intermediate data. Two novel algorithms for optimizing the internal wordlengths of linear time-invariant systems are proposed. The first one relaxes the solution to real valued and formulates the design problem as a constrained optimization. A closed-form solution can be determined by the Lagrange multiplier method. The second one is based on a discrete optimization method called the Marginal Analysis method, and it yields the desired wordlengths in integer values. Both approaches are found to be effective and suitable to large scale systems. A design example and the field programmable gate array (FPGA) realization of a multi-standard receiver are given to demonstrate the proposed method