Vehicular edge computing (VEC) is a new computing paradigm that enhances vehicular performance by introducing both computation offloading and service caching, to resource-constrained vehicles and ubiquitous edge servers. Recent developments of autonomous vehicles enable a variety of applications that demand high computing resources and low latency, such as automatic driving, auto navigation, etc. However, the highly dynamic topology of vehicular networks and limited caching space at resource-constrained edge servers calls for intelligent design of caching placement and computation offloading. Meanwhile, service caching decisions are highly correlated to the computation offloading decisions, which pose a great challenge to effectively design service caching and computation offloading strategies. In this paper, we investigate a joint optimization problem by integrating service caching and computation offloading in a general VEC scenario with time-varying task requests. To minimize the average task processing delay, we formulate the problem using long-term mixed integer non-linear programming (MINLP) and propose an algorithm based on deep reinforcement learning to obtain a suboptimal solution with low computation complexity. The simulation results demonstrate that our proposed scheme exhibits an effective performance improvement in task processing delay compared with other representative benchmark methods.

This paper investigates a two-way two-relay network-coded differential-chaos-shift-keying (DCSK) system over multipath Rayleigh fading channels. First, a decode-and-forward protocol is considered, when the two relays first decode the two users' orthogonal transmitted signals and then forward their XORed version back to the users. Based on the equal-gain-combining method at the receiver of each user, the bit-error-rate (BER), achievable diversity order, and throughput are analyzed. It is shown that, as compared to the conventional two-way one-relay network-coded DCSK system, the proposed system achieves lower BER, but reduces the throughput meanwhile. To improve the overall performance and avoid the throughput loss, a novel relay-selection criterion is developed based on the decision metrics used for conventional symbol detection, which can be implemented without requiring the channel state information. According to the criterion, three relay-selection strategies are suggested, namely the max-sum, max-product and max-min relay selections. Both analytical and simulated results show that the proposed relay-selection strategies significantly improve the BER and throughput of the two-way two-relay network-coded DCSK system and achieve higher diversity order. As a further insight, the superiority of the proposed relay-selection strategies is demonstrated in multirelay scenarios. Overall, the proposed system stands out as a promising candidate for low-power and low-complexity short-range wireless-communication applications, such as wireless sensor networks.

The performance of over-the-air computation (AirComp) systems degrades due to the hostile channel conditions of wireless devices (WDs), which can be significantly improved by the employment of reconfigurable intelligent surfaces (RISs). However, the conventional RISs require that the WDs have to be located in the half-plane of the reflection space, which restricts their potential benefits. To address this issue, the novel family of simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) is considered in AirComp systems to improve the computation accuracy across a wide coverage area. To minimize the computation mean-squared-error (MSE) in STAR-RIS assisted AirComp systems, we propose a joint beamforming design for optimizing both the transmit power at the WDs, as well as the passive reflect and transmit beamforming matrices at the STAR-RIS, and the receive beamforming vector at the fusion center (FC). Specifically, in the updates of the passive reflect and transmit beamforming matrices, closed-form solutions are derived by introducing an auxiliary variable and exploiting the coupled binary phase-shift conditions. Moreover, by assuming that the number of antennas at the FC and that of elements at the STAR-RIS/RIS are sufficiently high, we theoretically prove that the STAR-RIS assisted AirComp systems provide higher computation accuracy than the conventional RIS assisted systems. Our numerical results show that the proposed beamforming design outperforms the benchmark schemes relying on random phase-shift constraints and the deployment of conventional RIS. Moreover, its performance is close to the lower bound achieved by the beamforming design based on the STAR-RIS dispensing with coupled phase-shift constraints.

LoRa is a modulation technology for low power wide area networks (LPWAN) with enormous potential in 5G era. However, the performance of LoRa system deteriorates seriously in fading-channel environments. To tackle this problem, in this paper we introduce multiple-input-multiple-output (MIMO) configuration employing space-time block coding (STBC) schemes into the LoRa system to formulate an STBC-MIMO LoRa system. Then, we investigate the theoretical performance of the proposed system over Rayleigh fading channels. To this end, we derive the distribution of the decision metric for the demodulator in the proposed system. Based on the above distribution, we propose a closed-form approximate BER expression of the proposed system when perfect and imperfect channel state information (CSI) are considered. Furthermore, we analyze the diversity order and the throughput of the proposed system. The results of the diversity analysis demonstrate that the diversity order of the system in the imperfect CSI scenario with fixed channel estimate error variance is zero. However, in the imperfect CSI scenario with a decreasing channel estimate error variance and the perfect CSI scenario, the system can achieve full diversity. In addition, the results of the throughput analysis show that the throughput of the proposed system is little affected by CSI conditions. Simulation results verify the accuracy of the theoretical analysis and the excellent performance of the proposed system. Due to such superiority, the proposed STBC-MIMO LoRa system can be considered as a good scheme for LPWAN.