Siheng Li, Kejiao Li, Zenan Xu, Guanhua Huang, Kun Li, Haoyuan Wu, Wujiajia, Zihao Zheng, Chenchen Zhang, Kun Shi, Xue Gong, Qi Yi, Ruibin Xiong, Tingqiang Xu, Yuhao Jiang, Jianfeng Yan, Yuyuan Zeng, Guanghui Xu, Jinbao Xue, Zhijiang xu, Zheng Fang, Shuai LI, Qibin Liu, Xiaoxue Li, Zhuoyu Li, Yangyu Tao, Fei Gao, Cheng Jiang, Bochao Wang, Kai Liu, Jianchen Zhu, Wai Lam, Bo Zhou, Di Wang. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

In this paper, we proposed a cooperative spectrum sharing strategy based on contract theory with optimal power and bandwidth allocation. Specifically, primary user (PU) and secondary users (SUs) act as the employer and employees like labor consumption market, respectively. SUs provide labor, i.e. the relay power used for forwarding the PU's signal, in exchange for the reward, i.e. the spectrum accessing bandwidth for transmitting their own signals. PU needs to overcome a challenge how to balance the relationship between contributions and incentives for SUs. We designed an optimal contract with joint power and bandwidth optimization. We study how to allocate the power and bandwidth to maximize primary user's utility. Simulation results confirm that the utility of the primary user is significantly enhanced with our proposed cooperative spectrum sharing strategy.

To achieve secure communication between legitimate users, a physical layer encryption scheme based on random rotation of the modulated symbol is proposed. By exploiting the random behavior and the reciprocity property of the wireless channel, the channel state information (CSI) shared between transmitter and legitimate receivers is used as a initial seed to generate chaotic sequence. The transmitter uses the chaotic sequence to rotate the modulated symbol to enhance communication security and to reduce eavesdroppers' ability to demodulated symbols correctly. Due to the fact that the eavesdropper does not posses any information about the legitimate channel because the channel response is unique to the location of the transmitter and receiver as well as the environment, the receiver is able to demodulate the random rotated symbols correctly while the eavesdroppers demodulate them erroneously. Simulation results show that bit-error-rate (BER) of the legal user matches theoretical results perfectly while the eavesdroppers' BER stays around 0.5, which means that the proposed scheme keeps data transmission under security.

The correlation coefficient of two consecutive Gaussian sequences is modulated by a binary message bit to achieve a secure communication system. The receiver of the proposed random communication system demodulates the received signal by estimating the correlation coefficient of the transmitted two consecutive sequences. Theoretical bit error rate (BER) expressions in frequency‐flat/‐selective fading channels with/without Doppler shift are derived. Simulation results show that the proposed system can achieve reasonably low BERs in an additive white Gaussian noise channel as well as a Rayleigh fading channel. More importantly, the proposed system shows good performance in resisting eavesdropping, since the transmitted sequence appears to be a Gaussian noise which is almost always inevitable in the process of wireless communications.

In this study, the parameter of a symmetric α ‐stable (S α S) noise sequence is modulated by the binary message sequence to achieve a secure communication system. The characteristic exponent ‘ α ’ of an S α S noise sequence carries the binary information. In order to recover the binary message sequence at the receiver, the authors propose a logarithmic moments estimator to estimate the characteristic exponent ‘ α ’ of the transmitted noise sequence. The optimal decision threshold and the minimum theoretical bit error ratio are derived. It is shown that the simulation results of the presented logarithmic moments estimator are consistent with the analytical results. Moreover, this estimator shows better performance and lower computational complexity than the conventional SINC estimator based on the fractional low‐order moment method.