Wireless Channel Randomness Integrated Spread Spectrum Sequence Generation

Spread spectrum communication plays a vital role in safeguarding the Internet of Things systems, due to its inherently low probability of interception and anti-jamming capability. However, conventional spread spectrum systems based on pseudorandom sequences are disadvantageous in limited sequence length and deterministic periodicity, making them vulnerable to brute-force attacks. To address these limitations and enhance the randomness of the spread spectrum sequences, a novel wireless channel randomness integrated spread spectrum sequence generation method is proposed in this work. Taking advantages of the intrinsic randomness, temporal variations, and unpredictability of wireless channel fadings, the proposed approach converts the extracted channel features into ordered sequences, which are then used to control the selection of irreducible generating polynomials for spread spectrum sequence generation. The proposed method improves the randomness and secrecy of the integrated spread spectrum sequence. Theoretical analysis and simulation results demonstrate that the proposed sequences not only achieve higher randomness entropy compared to the traditional m-sequence, but also pass the National Institute of Standards and Technology randomness tests. Furthermore, performance evaluations under various signal-to-interference ratio conditions show improved autocorrelation properties and largely lower bit error rates, validating the effectiveness of the proposed method in improving the anti-jamming capability.