Movable antenna (MA) systems can reshape the wireless channel by repositioning antenna elements in a confined region, but most existing MA optimization methods depend on perfect channel state information (CSI). This paper studies robust joint transmit beamforming and antenna-position optimization for a downlink multiple-input single-output (MISO) MA system with imperfect CSI. Instead of treating CSI errors as unstructured channel perturbations, we introduce bounded uncertainties directly into physical multipath parameters, including path-gain amplitudes and angular parameters. The resulting worst-case signal-to-noise ratio (SNR) design is approximated through discrete sampling and a harmonic-mean surrogate that penalizes weak channel realizations. An alternating optimization algorithm is then developed, where transmit beamforming is updated on the complex sphere manifold, and antenna positions are optimized via a sequential grid search. Simulation results show that the proposed robust design yields higher SNR performance than non-robust designs and the fixed-position antenna (FPA) baseline.

A review of signal processing algorithms employing Wi-Fi signals for positioning and recognition of human activities is presented. The principles of how channel state information (CSI) is used and how the Wi-Fi sensing systems operate are reviewed. It provides a brief introduction to the algorithms that perform signal processing, feature extraction and recognitions, including location, activity recognition, physiological signal detection and personal identification. Challenges and future trends of Wi-Fi sensing are also discussed in the end.

Recent years have witnessed an explosive growth in mobile video-based services and efficient and reliable video delivery draws more and more attention. As a type of rateless codes, fountain codes can automatically adapt to wireless channel conditions without any knowledge of channels. This paper provides an overview of several typical Forward Error Correction (FEC) codes, such as Reed-Solomon (RS) code, Tornado code, Luby-Transform (LT) code, and Raptor code. We focus on a novel delay-aware fountain coding (DAF) technique that maximizes the code word length under the constraint of a given delay. Based on DAF, this paper also presents Unequal Error Protection DAF (UEP-DAF) which improves the Peak Signal to Noise Ratio (PSNR) without additional coordination between the encoder and the decoder, as well as Model Predictive Control DAF (MPC-DAF) which reduces the computational complexity to an affordable level for real-time video communications. Moreover, we review video streaming technologies, then introduce Dynamic Adaptive Streaming over HTTP (DASH) and DASH over Multiple Content Distribution Servers (MCDS-DASH) in detail. Based on MCDS-DASH that adapts video bitrate at the block level to alleviate video fluctuation, we propose a novel approach to integrating fountain codes with MCDS-DASH, which is capable of achieving unprecedented high throughput.