Experimental Phase Separation Differential Chaos Shift Keying Wireless Communication Based on Matched Filter

Abstract

New findings have been identified recently for chaos application in communication systems, including the simplest matched filter to maximize the signal-to-noise ratio (SNR) and the ability to resist multi-path propagation. However, chaos has a broad band frequency spectrum, which impedes its application in the conventional wireless communication systems due to the antenna and transducer bandwidth. To deal with such problem, the chaos generated by a second order hybrid system (SOHS) with a fixed basis function is used for Differential Chaos Shift Keying (DCSK) communication. A sinusoidal and its orthogonal signal are used to separate the reference signal and the information bearing signal, which are transmitted in the wireless channel. In such a way, the obstacle to broadband signal transmission in a wireless channel is overcome. A matched filter, using the convolution of the received signal and the time reverse of the basis function, maximizes the SNR at the receiver. Moreover, the proposed SOHS-DCSK provides an additional bitstream due to the chaotic signal generated by the SOHS, being capable to encode information as well. The two information sub-streams can be transmitted simultaneously in the proposed method, which possesses different bit transmission rates and reliability. In this way, the High Priority (HP) information bits are transmitted at a low transmission rate, while the Low Priority (LP) information bits are transmitted at a higher transmission rate. Hence, the proposed SOHS-DCSK method not only provides a higher data transmission rate as compared to the conventional DCSK but also makes the transmitted signal to be compatible with the conventional transducer and antenna. Due to the matched filter used, the proposed method achieves a lower bit error rate of the HP information as compared to the other existing enhanced DCSK variants for both additive white Gaussian noise channel and wireless communication channel. The numerical simulations and experiments based on the wireless open-access research platform show the validity and superiority of the proposed method. INDEX TERMS Chaotic shape forming filter, matched filter, DCSK, wireless communication.

Improved Channel Equalization using Deep Reinforcement Learning and Optimization

“…Figure 11 presents a graphical comparison of the BER in the Rayleigh channel. The graph illustrates that the proposed work exhibits an average BER of 0.064 while the lowest among the existing studies exhibit an average BER of 0.046, 0.032, 0.023, and 0.018 by [19], Kalman and [42,19] work. Further, Figure 13 represents that the BER analysis against energy per symbol to noise ratio also followed a similar trend and exhibits the lowest average BER of 0.086 in comparison to the existing works to offer the least interference-based communication.…”

“…The performance of the proposed equalization strategy is first evaluated in the AWGN channel in terms of BER evaluation. Figure 5 shows the comparison of BER exhibited by the proposed work against [21], Kalman filter [41], [42], and [19] 6 shows that the proposed work exhibits higher BER at lower values of 𝐸 𝑏 /𝑁 0 which gets improved with the increase in 𝐸 𝑏 /𝑁 0 . This shows that better BER performance is observed for the proposed work between 10 and 17 𝐸 𝑏 /𝑁 0 while exhibiting an average BER of 0.87 as compared to existing works.…”

Artificial intelligence enhances the performance of chaotic baseband wireless communication

“…wileyonlinelibrary.com/iet-com of chaos were reported [11][12][13]. They include the application of chaos in the conventional wireless communication systems [13] and the invariant Lyapunov exponent spectrum, which can be used to relieve the inter-symbol interference (ISI) caused by multipath propagation [11]. Recently, ISI resistance performance of chaotic baseband wireless communication systems (CBWCS) was theoretically and experimentally investigated [11][12][13].…”

“…They include the application of chaos in the conventional wireless communication systems [13] and the invariant Lyapunov exponent spectrum, which can be used to relieve the inter-symbol interference (ISI) caused by multipath propagation [11]. Recently, ISI resistance performance of chaotic baseband wireless communication systems (CBWCS) was theoretically and experimentally investigated [11][12][13]. In particular, some properties from chaotic dynamics could be used to relieve ISI, resulting in superior performance, compared to the conventional methods such as channel equalisation.…”

Radio-Wave Communication With Chaos

“…At the same time, experimental circuit encoding and decoding methods for wireless communication were designed to validate the theoretical predictions [20]. Besides these advances, other advantages for using chaos into communication have been reported recently, including the use of simple matched filter to achieve the maximum signal to noise ratio [21], [22], and a decoding threshold using chaos property to relief Inter-Symbol Interference (ISI) caused by multi-path propagation [23], [24]. All these progresses pushed the research forward to the practical application of chaos in communication systems.…”