In future space-air-ground integrated networks, time synchronization technology serves as the cornerstone for realizing network communication. In this network, the self-synchronization within the network achieved via communication links has advantages such as autonomy and higher synchronization accuracy compared to the timekeeping of the Global Navigation Satellite System (GNSS), and it is applied in various complex environments. Therefore, in the time synchronization technology of integrated networks, more attention should be paid to the issue that space-air/ground links are affected by dynamic interference. Such interference can lead to a decline in time synchronization accuracy and fluctuations in network performance. To address these challenges, this paper proposes a Neighbor Aware Reinforcement Learning (NARL) time synchronization framework. A lightweight neighbor node interaction mechanism is designed to control synchronization overhead and effectively prevent broadcast information explosion among nodes. Specifically, for partial space-air/ground link interference, we develop the NARL master-slave synchronization (NARL-MSS) algorithm, which constructs an online scoring model to enable rapid synchronization response while enhancing long-term performance through RL. Under full space-air/ground link interference, an NARL distribution synchronization (NARL-DS) algorithm is employed to identify optimal synchronization link sets, jointly optimizing synchronization accuracy and network overhead. Simulations demonstrate that NARL-MSS can achieve an 80% improvement in synchronization errors, while NARL-DS exhibits excellent synchronization convergence and significantly reduces synchronization costs.

Space simultaneous information and power transfer (SSIPT) extends simultaneous wireless information and power transfer (SWIPT) from terrestrial to space-based scenarios for efficient energy utilization beyond the limitations of photovoltaic systems. A large-aperture antenna is required to provide sufficient gain to compensate for the severe path loss caused by the extremely long transmission distance in the SSIPT system. However, most existing antennas employ phased-array (PA) architectures that depend on costly hardware components, making it difficult to achieve the aforementioned requirements under constrained budgets. In this paper, we propose a reconfigurable holographic surface (RHS)-assisted SSIPT system. Specifically, RHSs, which can be implemented entirely with low-cost, commercially available components, offer a promising alternative to conventional PAs for realizing cost-efficient SSIPT. The serial-feed architecture of RHSs introduces radiation power coupling among adjacent elements, which significantly affects the transmission characteristics and invalidates conventional PA-based SWIPT analytical models. To address this issue, we develop a new analytical SSIPT framework that accurately captures the serial coupling effect and design amplitude-controlled beamforming schemes that depart fundamentally from phase-shift-based approaches, which improve rate-energy (R-E) performance. In simulations, we demonstrate that under the same hardware cost, the RHS achieves an expanded R-E region compared with the PA. Therefore, the compact and low-cost characteristics of RHSs make them more suitable for SSIPT scenarios with limited payload and cost.

In future applications of Internet of Everything (IoE), we need to timely and reliably collect multi-modal sensing data in order to monitor dynamic environment. To this end, we study a timely wireless powered crowdsensing system by enabling cooperative sensing among multiple sensors to increase reliability, by exploiting radio frequency (RF) based wireless power transfer (WPT) to address energy shortage of miniature sensors, and by minimising the average age of information (AoI) to guarantee the timeliness of the sensing data. We jointly optimise the inter-group sensors scheduling and the intra-group sensors scheduling for minimising the weighted AoI among multiple group of sensors. Since the optimisation problem is NP-hard, we propose a joint scheduling algorithm to obtain the optimal scheduling policy. Simulation results demonstrate the superiority of our scheme over the existing state of the art.

Age of Information (AoI) has been studied recently for satisfying the timeliness requirements of the emergent applications, i.e. smart cities and smart wearables in future Internet of Everything (IoE). In order to integrate multiple information flows i wireless powered sensor network (WPSN), we propose age of sensing (AoS) for measuring freshness of the fused information, which is defined as the time elapsed from the generation moment of the sensing information used for generating the fresh reliable fused information. Specifically, a wireless power transfer (WPT) aided wireless sensor network (WSN) is studied. Multiple batteryless sensors cooperatively sense common objects and then timely upload the sensing information to a fusion center (FC). The FC fuses the correctly decoded information from different sensors and finally evaluates the reliability of the fused information. The number of time slots for WPT and the deployment of the sensors are then jointly optimised, in order to minimise the average AoS. A Fibonacci aroused integer programming approach is then proposed to solve the nonlinear integer problem having NP-hard complexity. Simulation results validate the accuracy of the theoretical analysis for the AoS, while also demonstrating that our algorithm achieves the superb performance by referring to the optimal exhaustive method.

Simultaneous wireless information and power transfer (SWIPT) has been considered as a promising technique to address energy shortage of communication devices deployed in Internet of Everything (IoE). In this paper, we consider a multi-relay aided cooperative communication network with SWIPT, where relay stations (RSs) receive RF signal from a source node (SN) for energy harvesting and information reception by power splitters. A single activated RS then decodes and forwards information to the destination using the harvested energy. Selective-decode-and-forward (S-DF) protocol is adopted, where the activated RS forwards only when information is correctly decoded. By considering time-varying channels, we maximise the end-to-end (E2E) throughput by jointly designing the transmit beamformers for both SN and RSs, optimising transmit power and power splitters for RSs, as well as the RS selection. The original formulated non-convex optimisation problem with coupled variables is solved by invoking an iterative algorithm. Numerical results demonstrate that our design with SDF protocol outperforms that with the decode-and-forward (DF) protocol. Moreover, the impact of the imperfect channel state information (CSI) on the E2E throughput is also evaluated.

In order to satisfy timeliness requirements arising from environmental sensing applications, Age of Information (AoI) was proposed to characterize the freshness of the received updates. In this article, we consider a wireless powered relay aided communication network (WPRCN), in which a relay wirelessly powered by a hybrid-access point (H-AP) receives environmental monitoring information update from a sensor and forwards it to the H-AP. The long-term average AoI is studied since the decision correctness depends on the update timely uploaded by the relay. The wireless powered relay adopts either a decode-and-forward (DF) or an amplify-and-forward (AF) protocols, respectively, subject to the energy causality. We also consider the decoding cost of DF protocol owing to the relay’s limited energy storage. Since the expression of the average AoI is nonelementary, we propose a Taylor approximation-based algorithm to obtain its integral. We optimize the transmit power/the equivalent average power consumption of the relay for the sake of minimizing the average AoI in the whole WPRCN with different forwarding protocols. Our simulation results demonstrate the accuracy of the theoretical analysis, while the average AoI of the WPRCN is optimized by our power allocation scheme at the relay. The proposed algorithm is verified to achieve a great approximation effect.

In order to meet timeliness requirements arising from sensing applications, age of information (AoI) was proposed to characterise the freshness of the received updates. In this paper, we study the average AoI for a two-hop network, in which a relay wirelessly powered by a hybrid-access point (H-AP) receives environmental monitoring information update from a sensor and forwards it to the H-AP. We optimise the transmit power of the relay for the sake of minimising the average AoI in the whole wireless powered relay aided communication nework (WPRCN). The wireless powered relay adopts a decode-and-forward strategy by considering the energy causality. Our simulation results demonstrate the impact of the relay's transmit power on the average AoI, while the information freshness of the WPRCN is optimised by our power allocation scheme at the relay.

In wireless powered communication networks (W-PCNs), full duplex (FD) is adopted owing to high efficiency. Furthermore, multi-antenna technique is also widely utilised, since it is capable substantially of improving communication throughput and reliability. In this paper, we study the optimal transmit beamforming and receive combining design for a multiantenna and FD aided hybrid access point (H-AP) in a WPCN, which aims for maximising the uplink sum-throughput of bat-teryless user equipments (UEs). Furthermore, self-interference cancellation (SIC) at the H-AP is also considered in the joint transmit beamforming and receive combining design. Since the optimisation problem is non-convex, a block descent method is exploited for finding the near-optimal solution. Our simulation results demonstrate that the sum-throughput obtained by our design outperforms the other counterparts. As the number of antennas increases, the performance of our design with self-interference approaches that without self-interference (or with perfect self-interference cancellation). Furthermore, our design is robust for accommodating increasing number of batteryless UEs.