Performance Analysis of an Ultra-Low Power MFSK System

In this dissertation, we investigate the problem of designing an ultra-low power $M$-ary frequency shift keying (MFSK) system. In Chapter 2, We design a communication system that operates under stringent power constraints, but is flexible with bandwidth constraints. Our approach is to consider some of the key elements in a transceiver and optimize them for low power consumption, as opposed to optimizing them to minimize, say, average probability of error. An obvious consequence of this is that high complexity components of the system, such as matched filters, forward error correction that employs iterative decoders, coherent demodulators, and bandwidth-efficient modulation formats, are not feasible for this research. Rather, our system is designed using MFSK with non-coherent detection, optimized two-pole bandpass filters (BPF), and Reed-Solomon (RS) codes with hard-decision decoding. Among other things, we show that by properly optimizing the key parameters of the BPFs and RS codes, we can design the system to be significantly less complex than an optimal one, and only lose about 1.2 dB in terms of performance.In Chapter 3, We extend the results from Chapter 2 to incorporate fast frequency hopping (FFH) and intelligent jamming. The system still operates under stringent power constraints, but is flexible with bandwidth constraints. Our system is designed using MFSK with non-coherent detection and fast frequency hopping (FFH), optimized two-pole BPF, and RS codes with hard-decision decoding. Among other things, we show that by properly optimizing the key parameters of the BPFs and RS codes, we can design the system to be significantly less complex than the MF system with a performance loss of less than 1.4 dB in terms of performance in most scenarios that we considered. Further, the 2-pole BPF system can actually outperform the corresponding MF system by up to 2.4 dB with multi-tone jamming.In Chapter 4, we extend the results from Chapter 2 to incorporate Gaussian filtering. We improve our previous design by considering the power-bandwidth tradeoff, and we show that we can save a large percentage of system bandwidth by sacrificing a small amount of power, when the demodulator and coding parameters are optimized. For example, we can save 50\% of system bandwidth at the cost of 1 dB loss in performance compared to our previous system design. We quantify the performance loss as a function of both the system bandwidth saved and the time-bandwidth product of the Gaussian filter. We keep $M = 16$ as our baseline design, and compare the performance of the $M$-ary GFSK system with the corresponding MFSK system