Adaptive Non Orthogonal MFSK

Abstract

M-ary frequency shift keying (MFSK) using one or more orthogonal tones per symbol has been in use in non-coherent systems for quite some time. We present an alternate system for non-coherent systems using non-orthogonal tones, spread non-uniformly throughout the bandwidth, which outperforms the equivalent orthogonal tone system. We demonstrate that from a theoretical capacity point of view, the same bit rate could be achieved by the proposed system with as much as 2.5 dB lower signal-to-noise ratio (SNR). For some practical configurations we demonstrate as much as 2 dB of gain. We present the performance with maximumlikelihood (ML) receivers as well as least-squares (LS) receivers as well as lower complexity receivers based on compressed sensing (CS). We also demonstrate that such a non-orthogonal system may be used to increase the spectral efficiency of the overall system by adapting the spectral efficiency in response to the link SNR. Such an adaptive non-orthogonal MFSK system requires estimation of the SNR (or ), and we present both the Cramér-Rao lower bound (CRLB) as well as maximum-likelihood (ML) estimators, which attain the CRLB for both data-aided (DA) SNR estimation as well as non-data-aided (NDA) SNR estimation.

Spectral Efficiency Enhancement Based on Sparsely Indexed Modulation for Green Radio Communication

“…On the other hand, OFDM may loss the orthogonality advantage through Doppler frequency shift, or carrier frequency offset (CFO). Getting rid of orthogonality limitations of the OFDM, and relaying on new non-orthogonal waveform designs are addressed in [43]- [48]. Moreover, as reported in [47], the employment of non-orthogonal pulses is optimum for minimizing ISI and ICI in double dispersive channels.…”

“…In [48], a scheme of non-orthogonal multi-tone MFSK is regarded as non-orthogonal index modulation on a single subcarrier group. The SE of MFSK is enhanced by relaxing the orthogonality constrains in the tone space.…”

“…The optimum choice of these non-orthogonal tones is performed by nonexhaustive searching algorithm. The searching objective is to minimize the worst-case correlation between any two selected tones [48]. It may be regarded as a type of dictionary training.…”

“…• Similar to the work introduced in [48], the combinatorial space can be expanded through indexing on non-orthogonal tones, along with sparsely indexing on large number of subcarriers and CS-based signal processing tools. The non-orthogonal tones are distributed uniformly without learning efforts.…”