An enhanced on-off division multiple access (ODMA) transmission scheme is introduced for unsourced multiple access networks. Building upon the foundational ODMA transmission scheme, we have implemented further refinements to the original joint on-off pattern and data detection algorithm. Specifically, we propose a pattern collision resolution technique that can blindly recognize the collision degree of each on-off pattern, and then iteratively recover the data of collided users over a joint factor graph. Furthermore, we introduce a finite-length performance analysis for on-off pattern detection and iterative multi-user decoding. Through this analysis, we derive numerous numerical results, revealing the impact of various parameters on the performance of collision degree detection and multi-user decoding, respectively. By summarizing the rules observed from these numerical results, we formulate design strategies for these parameters, aiming to optimize the overall performance of our scheme. The inherent super sparse property of ODMA ensures that our scheme maintains low decoding complexity. Numerical results demonstrate that, with the implementation of our pattern collision resolution method and meticulous parameter design, the proposed scheme achieves a gap of less than 1.2 dB compared to the random coding bound for up to 300 active users. This performance surpasses state-of-the-art schemes across a broad range of user numbers.

An enhanced on-off division multiple access (ODMA) transmission scheme is proposed for unsourced multiple access network. The message of each active user is divided into two parts, where the first part is used to determine an on-off pattern, and the second part is encoded and transmitted in a time-hopping manner according to an on-off pattern. Leveraging the super sparse property of ODMA, the users' on-off pattern and pattern collisions are blindly detected based on the received signal without the help of pilot. Moreover, the on-off pattern detection, data decoding and collision recovery are performed iteratively over one sparse graph to enhance the overall system reliablity. We propose a finite-length performance analysis to the on-off pattern detection and iterative multi-user decoding, based on which both the user access sparsity, and channel code are optimized. Numerical result shows that with a rate 1/ 3 low-density parity-check code over G F (26), the gap between the proposed scheme and the random coding bound is less than 1.2 dB for up to 300 active users.

In this paper, dual-functional radar-communication system which can perform both radar and communication functionalities using the same hardware platform and spectrum resource is studied. Concretely, the mean-squared error between the designed and desired beampatterns is minimized subject to the communication quality-of-service requirements and the constant-modulus constraint. To solve this resulted problem efficiently, the alternating minimization framework is presented. Specifically, in the sub-problem of transmit signal design through symbol-level precoding, the low-complexity linearized alternating direction method of multipliers algorithm is presented. Finally, computer simulations are given to demonstrate the effectiveness of the proposed method.