An iteratively decoded variable length space time coded modulation (VL-STCM-ID) scheme capable of simultaneously providing both coding and iteration gain as well as multiplexing and diversity gain is proposed. Non-binary unity-rate precoders are employed for assisting the iterative decoding of the VL-STCM-ID scheme. The discrete-valued source symbols are first encoded into variable-length codewords that are mapped to the spatial and temporal domains. Then the variable-length codewords are interleaved and fed to the precoder assisted modulator. More explicitly, the proposed VL-STCM-ID arrangement is a jointly designed iteratively decoded scheme combining source coding, channel coding, modulation as well as spatial diversity/multiplexing. As expected, the higher the source correlation, the higher the achievable performance gain of the scheme becomes. Furthermore, the performance of the VL-STCM-ID scheme is about 14.6 dB better than that of the fixed length STCM (FL-STCM) benchmarker at a source symbol error ratio of 10^-4

This paper presents a novel timing synchronization scheme for orthogonal frequency-division multiplexing communication systems by leveraging the phase shift caused by the timing error and the power difference between subcarriers. The proposed scheme is applied in the physical layer of vehicular ad hoc networks using the IEEE 802.11p standard. The proposed work joints three different estimators to present a robust synchronizer. The results demonstrate that the proposed estimators greatly improve the performance of the communication system and outperform other approaches in terms of the mean square error and the bit error rate. The estimators can either work as totally blind or data-aided using the preamble field of the IEEE 802.11p.

This paper studies the energy-efficient optimization problem for low earth orbit (LEO) satellite edge computing served by medium earth orbit (MEO) satellite when partial computation offloading strategy is adopted. An optimization model with the goal of minimizing the total energy consumption of LEO satellites is established, with constraints of task tolerable delay, transmit power, and CPU-cycle frequency, forming a challenging mixed-integer and nonlinear problem. Based on the non-convexity of the optimization problem and the coupling variables, the problem is decomposed into three manageable subproblems as local computing subproblem, task offloading subproblem, and resource allocation subproblem, which are solved using analytical method, convex optimization, and Lagrange dual decomposition method, respectively. Based on the solution of the subproblems, alternative iterations are performed to converge to the optimal value. The simulation results show that when using the partial computation offloading optimization algorithm, the total energy consumption required for LEO satellites is significantly lower than that of local computing and full offloading strategies.