Jie Zhong

Considering a reconfigurable intelligent surface (RIS) aided wireless powered Internet of Things (WP IoT) network. To address the energy-limitation issue, IoT devices in such a network can be wirelessly powered by a power station (PS) first and then connect with an access point (AP) using their own harvested energy. The RIS helps enhance energy and information receptions in the downlink wireless energy transfer (WET) and uplink wireless information transfer (WIT), respectively. This work unveils the impact of phase shift error (PSE) and transceiver hardware impairment (THI) on the considered network. Our investigation starts with a scenario where only the impact of the PSE on system under study is considered, then moves toward a scenario with the compound effect of both PSE and THI. A maximization problem of the system sum throughput is formulated to evaluate the overall performance for these two scenarios, subject to the constraints of the adjustable RIS phase shifts, the statistical PSE and the transmission time scheduling. To handle the non-convexity of the formulated problem due to those coupled variables, we first adopt the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions to derive the optimal time scheduling in closed-form. Next, we recast the stochastic PSE into the deterministic counterpart for its tractability. Then, we adopt a successive convex approximation (SCA) to iteratively derive the optimal WIT’s phase shifts, and element-wise block coordinate decent (EBCD) and complex circle manifold (CCM) methods to iteratively derive the optimal WET’s phase shifts. Finally, we complete our solution approach for the scenario with both PSE and THI. Simulation results highlight the performance of the proposed scheme and the benefits induced by the RIS in comparison to benchmark schemes.

In this paper, theoretical closed expressions for the symbol error rate (SER) of two optical spatial modulation (OSM) schemes in a free-space optical (FSO) communication system—optical spatial pulse amplitude modulation (OSPAM) and optical spatial pulse position modulation (OSPPM)—over correlated gamma–gamma fading channels are derived. To study practical optical channels affected by atmospheric eddies, the effect of arbitrary atmospheric channel correlation is considered particularly, and it is shown that the correlation can degrade system performance. The parameters of atmospheric turbulence and the number of optical antennas are also under consideration in performance analysis of the FSO multiple input, multiple output system. All analytical results are validated with Monte Carlo simulations, which clearly illustrate the effect of spatial constellation and signal constellation on the average SER. In addition, it is shown by comparison that turbulence fluctuation and channel correlation have less influence on the OSPPM system than the OSPAM system. Overall, the framework proposed in this paper is proven to be effective and conducive to algorithm research on reducing the effect of correlated channels on OSM FSO systems.

In this article, we propose an intelligent reflecting surface (IRS)-enabled wireless-powered caching system. In the proposed IRS model, a power station (PS) provides wireless energy to multiple Internet of Things (IoT) devices, delivering their information to an access point (AP) by utilizing the harvested power. The AP, equipped with a local cache, stores the IoT data to avoid waking up the IoT devices frequently. Meanwhile, we deploy the IRS involving in the wireless energy and information transfer process for performance enhancements. In this practical system, the PS and AP could belong to different service providers. Also, the AP requires to incentivize the PS to offer a provisional energy service. We model the interaction between the PS and AP as a Stackelberg game that jointly optimizes the transmit power of the PS, the energy price, the phase shifts of the wireless energy transfer (WET) and wireless information transfer (WIT) phases, as well as wireless caching strategies of the AP. In this way, we first derive the optimal solutions of the phase shifts and the transmit power of the PS in a closed form. We propose an alternating optimization (AO) algorithm to optimize the wireless caching strategies and the energy price iteratively. Finally, we present various numerical evaluations to validate the beneficial role of the IRS and the wireless caching strategies and the performance of the proposed scheme compared with the existing benchmark schemes.

Free-space optical communication brings large-capacity communication with excellent confidentiality, though fatal obstacles are set by atmospheric turbulence that causes phase shifting in laser links. Therefore, we derived a novel, to the best of our knowledge, iterative wavefront correction algorithm based on a complete second-order deformable mirror (DM) Shack–Hartmann wavefront sensor model as a solution to it. For correcting static wavefront aberration, the proposed algorithm possesses a converging speed faster than the traditional one. In terms of correcting dynamic atmospheric turbulence, it can achieve convergence within two iterations with a residual wavefront root mean square value of less than 1/8 wavelength. The input wavefront under 1.5 wavelength can be corrected on our testbed due to the deformability of the micromachined membrane DM. The research result offers a solution for atmospheric turbulence in the adaptive optics field and may contribute to the development of free-space optical communication.

In this Letter, a deep reinforcement learning‐based approach is proposed for the delay‐constrained buffer‐aided relay selection in a cooperative cognitive network. The proposed learning algorithm can efficiently solve the complicated relay selection problem, and achieves the optimal throughput when the buffer size and number of relays are large. In particular, the authors use the deep‐Q‐learning to design an agent to estimate a specific action for each state of the system, which is then utilised to provide an optimum trade‐off between throughput and a given delay constraint. Simulation results are provided to demonstrate the advantages of the proposed scheme over conventional selection methods. More specifically, compared to the max‐ratio selection criteria, where the relay with the highest signal‐to‐interference ratio is selected, the proposed scheme achieves a significant throughput gain with higher throughput‐delay balance.

The Integrated Laser Communication/Ranging System, which uses a coded signal as the ranging information carrier, is of great importance to the next large-capacity inter-satellite information network. In this paper, a system design with a high-sensitivity feedback-homodyne detection scheme and an asynchronous ranging algorithm is demonstrated with real-time field-programmable gate array-implementation (FPGA). The parallel fast Fourier transformation (FFT) estimation is applied to improve the speed and the range of the wavelength drift tracking, which can handle a dynamic wavelength drift up to 2.4 pm/s (300 MHz/s). Meanwhile, for clock sources with subtle dynamic frequency offset and sufficient stability, the proposed fractional symbol ranging method is proven to achieve millimeter-level measurement accuracy. The designed system is shown to perform well in terms of both laser linewidth tolerance and noise resistance.

Sparse code multiple access (SCMA) is a novel non-orthogonal multiple access scheme for 5G systems, in which based stations are usually equipped with multiple antennas. In this letter, we propose a novel resource-selection based message passing algorithm (RSB-MPA) detector for uplink SCMA systems with multiple receive antennas. In the proposed RSB-MPA detector, several resources are selected to perform the Jointly Gaussian Algorithm and the remaining are to perform the maximum likelihood algorithm. The resource selection criterion is based on the minimum distance at each resource, which is lower bounded by the minimum singular value of the corresponding channel matrix. Simulation results show that the RSB-MPA detector can significantly reduce the computational complexity with slight performance degradation.

Orthogonal frequency division multiplexing with index modulation (OFDM-IM), which uses the subcarrier indices as a source of information, has attracted considerable interest recently. When the index modulation (IM) technique is applied to filter bank multicarrier (FBMC) system, the intrinsic interferences are partly eliminated but the remaining interferences still affect the bit error rate (BER) performance. In this paper, the dominant factors that have influence on the BER performance of the FBMC with IM (FBMC-IM) system are investigated. Then we propose a combination-selection algorithm to reduce the impact of these factors by considering the largest average Hamming distance (HD) principle and the fewest bad combinations principle. The theoretical analysis and simulation results clearly show the BER improvement when we select the optimal combinations.

Cooperative communications and full-duplex (FD) relaying have been proposed to meet the ever increasing data traffic demands and fully exploit the scarce spectrum resources. In this paper, we consider FD relaying networks with multiple source-destination (S-D) pairs and multiple FD relays. We propose the joint optimal relay assignment and power allocation (ORAPA) scheme to maximize the sum rate of the network. The sum rate maximization problem is formulated as a mixed-integer nonlinear programming (MENLP) problem. We provide an equivalent maximum weighted bipartite matching (MWBM) problem to solve the MINLP issue and reduce computational complexity by adopting the Hungarian algorithm. Simulations results are provided to verify the effectiveness of our proposed scheme.