A Novel Noise Reduction Technique to Enhance the Performance of Permutations Index DCSK for Cognitive Communications

In this paper, an advanced technique to enhance the performance of Permutation Index-Differential Chaos Shift Keying (PI-DCSK) with a simplified structure and better performance is proposed. In the standard PI-DCSK, a single chaotic signal is used as a reference, followed by a permutation version of the same copy that is information bearing signal. Permutation is performed in alignment with the sequence of transmitted data sets, however, in the proposed model, which is named Noise Reduction Permutation Index DCSK (NR-PI-DCSK), data is sent as frames with a single chaotic reference signal. This reference is used to modulate multiple information bits. At the receiver, the information bearing signal is decoded, de-mapped and recursively averaged with the same reference signal itself. This significantly enhances system performance, saves energy, and increases the system’s immunity against noise. The theoretical bit-error-rate (BER) expressions of the NR-PI-DCSK scheme are derived using the Gaussian Approximation (GA) method over Additive White Gaussian Noise (AWGN) and multipath Rayleigh fading channels. Furthermore, the BER of the proposed system is analysed and evaluated against various differential coherent and permutation systems with different spreading factors. The results show that the proposed system outperforms standard systems by an average of more than 2 dB in AWGN channel while it constitutes to yield again of an average of 1.5 dB in a Rayleigh fading channel at moderate to high spreading factor values. The results show that our theoretical expressions closely match the simulated results, and the NR-PI-DCSK system can achieve better BER performance than its competitors.