Integrated Sensing and Communication (ISAC) is a pivotal technology for 6G vehicle-to-everything (V2X) applications, enabling concurrent target detection and data exchange within a unified framework. Beam misalignment, precoder imperfections, and fluctuating radar cross sections increase sensing latency, challenging the low-latency needs of safety-critical V2X scenarios. In this paper, we develop a robust optimization framework to minimize sensing latency in ISAC systems while preserving high detection probability and communication quality. We propose a novel signal model for antenna-array imperfections and derive analytical detection thresholds and repetition bounds for Unmanned Aerial Vehicle (UAV) and vehicular environments. We optimize sensing repetitions, block length, and detection thresholds via low-complexity Branch-and-Bound for MINLP, achieving 99% lower complexity (0.11 ms) than grid search, which benchmarks optimal results. Simulations show our framework achieves latencies below 15 ms, detection probabilities above 0.95, and robust Signal-to-Interference-plus-Noise Ratio (SINR) despite precoder imperfections, meeting safety-critical V2X demands. The proposed framework thus offers a scalable solution for 6G V2X, effectively balancing sensing and communication performance in dynamic vehicular environments.

In this paper, we revisit the received signal strength (RSS)-based target localization technique presented in Vempaty et al., where a simple threshold quantizer was employed to quantize the RSS values prior to sending them to the fusion center. It was shown that the probability of misclassification of the distributed classification fusion using error correcting codes scheme vanishes as the number of sensors tends to infinity. This result was obtained based on an intuitive threshold design at the local sensors, and the question of how much a careful design of local thresholds can help improve the overall performance was not addressed. In this paper, we demonstrate the significance of threshold design for accurate and robust target localization in wireless sensor networks, particularly, when the number of sensors is finite. With this objective, we derive an upper bound on the probability of misclassification as a function of RSS thresholds by using the union inequality. The RSS thresholds that algorithmically minimize the derived misclassification error bound are then numerically obtained over a mirror-based homomorphic sensor deployment structure. Simulations over fading wireless links show that the scheme based on newly found optimized RSS thresholds considerably outperforms the previous scheme using the thresholds that are intuitively selected, especially in the presence of Byzantine attacks that severely impact information security.

An iterative detection aided down-link (DL) space division multiple access (SDMA) system is proposed. The base station (BS) requires DL channel state information (CSI) estimated by and fed back from the mobile station (MS) for separating the DL signals to be transmitted to the MSs from the BS. We investigate the achievable system performance subject to finite-accuracy CSI feedback. The achievable receiver performance is investigated with the aid of extrinsic information transfer (EXIT) charts. Furthermore, a novel concept, referred to as the EXIT-chart optimized CSI quantization (ECO-CQ) is proposed. The ECO-CQ scheme assists the system in maintaining the lowest possible CSI feedback overhead, while ensuring that an open EXIT-tunnel is still attainable, which implies maintaining an infinitesimally low BER. Furthermore, we demonstrate that the proposed ECO-CQ may reduce the normalized feedback overhead compared to the conventional CQ. For instance, the ECO-CQ aided iterative DL-SDMA system using an average of q = 2.7 quantization bits per CIR coefficient achieves a 10% normalized overhead reduction at Eb/N0= 5 dB, compared to the conventional CQ aided benchmarker system.

When an iterative-decoding aided system is configured to operate at a near-capacity performance, an excessive complexity may be imposed by the iterative process. In this paper, we propose the novel framework of generic detection, which invokes appropriately amalgamated multiple detectors. Hence the proposed Irregular Generic Detection (IrGD) algorithm may reduce the complexity of iterative detectors. We show in the context of an iterative Down-Link (DL) Space Division Multiple Access (SDMA) system that the proposed IrGD may indeed reduce the complexity of the iterative receiver. The IrGD aided DL-SDMA system detects the appropriate fractions of the received bitstream with the aid of different detectors. This allows us to match the Extrinsic Information Transfer (EXIT) curve of the detector to that of the channel decoder, hence facilitating a near-capacity operation, which reducing the detection complexity by about 28% compared to a powerful near-Maximum-Likelihood (ML) sphere detector benchmark system.

In this treatise, a jointly optimized bit interleaved coded modulation using Iterative decoding (BICM-ID) and Luby transform (LT) coding scheme was proposed for the sake of attaining the best possible performance, when communicating over the wireless Internet. This scheme is particularly attractive when handling packetized wireless Internet data traffic received over wireless channels inflicting both statistically multiplexing induced packet erasure and packet corruption imposed by the channel without retransmitting the corrupted packets. A LLR-based estimation packet reliability algorithm was proposed to assist the LT decoder in recovering all the transmitted packets. Furthermore, the bit-to-sphere-packing-symbol mapping scheme was optimized for achieving error free LT decoding at the lowest possible Eb/No value rather than for approaching the channel's capacity. These two design philosophies require different mapping schemes. Finally, differential space time coding (DSTBC) was employed for combatting the effects of fading and provided spatial diversity at the same time. The LT code's packet length was also carefully chosen to strike a good balance between the affordable complexity and the achievable performance.

The literature of up-link SDMA systems is rich, but at the time of writing there is a paucity of information on the employment of SDMA techniques in the down-link. Hence, in this paper a space division multiple access (SDMA) down-link (DL) multi-user communication system invoking a novel low-complexity maximum likelihood (ML) space-time detection technique is proposed, which can be regarded as an advanced extension of the complex sphere decoder (CSD). We demonstrate that as opposed to the previously published variants of the CSD, the proposed technique may be employed for obtaining a high effective throughput in the so-called "over-loaded" scenario, where the number of transmit antennas exceeds that of the receive antennas. The proposed method achieves the optimum performance of the ML detector even in heavily over-loaded scenarios, while the associated computational complexity is only moderately increased. As an illustrative example, the required Eb/NO increased from 2 dB to 9 dB, when increasing the normalized system load from unity, representing the fully loaded system, to a normalized load of 1.556.