Unmanned aerial vehicle (UAV) assisted relaying has become the focus of the next generation network owing to its superiority of low cost and swift deployment. In addition, the orthogonal frequency division multiplexing (OFDM) based simultaneous wireless information and power transfer (SWIPT) is known to have significant advantages in system complexity compared to the traditional time-switching (TS) and power-splitting (PS) techniques. Since the UAV is known to have limited size, weight and power, we investigate the OFDM-based SWIPT for a multi-source-destination UAV relaying system in this paper. With the purpose of maximizing the average transmission rate (ATR) under the constraint of the harvested energy, we jointly optimize user scheduling, resource allocation and UAV trajectory. To tackle this issue, we first divide it into three subproblems of user scheduling, power and subcarrier allocation, and UAV trajectory optimization. Subsequently, the user scheduling subproblem is optimally solved. The power and subcarrier subproblem is approximately solved by addressing its dual problem and the UAV trajectory optimization subproblem is addressed by successive convex approximation technique. Then, we put forward an iterative algorithm based on block coordinate descent method by solving the three subproblems alternately. Numerical results demonstrate that our proposed algorithm is preferable than the two benchmark schemes.

This research delves into an integrated sensing and communication (ISAC) system, which leverages a ship-based station to simultaneously offer maritime communication services and perform target detection. Through the establishment of a channel model that captures the complexities of the maritime environment and the analysis of the dynamic behavior of the ship-based station, this article introduces a unified signal processing framework for this ISAC system. This framework is tailored for various ship movement patterns through the integration of alternating optimization coupled with trust-region-based sequential convex approximation (SCA) techniques, with the goal of maximize the communication data rate without compromising the sensing performance. Simulation results corroborate the validity of the proposed model, laying a theoretical foundation for the advancement of maritime communication and perception systems, thereby anticipating enhanced support for future generations of integrated maritime applications.

In this paper, we study an uplink reconfigurable intelligent surface (RIS) aided orthogonal frequency division multiplexing (OFDM) system, where the RIS simultaneously acts as a passive reflector for a user’s quadrature phase-shift keying (QPSK) OFDM signal and an information source which sends information through spatial modulation of the reflected signal. We present a maximum-likelihood (ML) detector for the detection of RIS signals and analyze the error probability theoretically. We derive closed-form expressions of the error probability for the detection of RIS signals for the special case of flat-fading channels. Then we analyze the error probability of the detection of user’s signals. Analysis indicates that faulty detection of RIS signal results in channel estimation errors, consequently compromising the precision of OFDM signal detection. High correlation between code words limits the error propagation to the user but decreases accuracy for RIS signal’s detection. Addressing this, an index modulation with beamforming (IM-BF) code is proposed to enhance the transmission for the user, and a quadrature reflection modulation with beamforming (QRM-BF) code is proposed for a performance trade-off between the user and the RIS. Simulation results demonstrate the theoretical results, and show that the QRM-BF code has better performance for the RIS transmission, and both schemes outperform benchmark schemes from the literature for the user’s transmission. Simulation results also show that the IM-BF scheme significantly improves the user transmission performance compared to the state of the art.

The purpose of this paper is to solve the reconstruction problem of sparse vectors in distributed compressed sensing with Multiple Measurement Vectors (MMV). Many traditional methods are based on certain sparse conditions, such as assuming that signals of different channels are joint sparse. This paper relaxes this restriction and assumes some correlation between the signals of different channels. We use Gated Recurrent Units (GRU) to capture this correlation and reconstruct the signal. Meanwhile, the previous reconstruction algorithms treat the signals of different channels equally, but the influence of different channels on the reconstruction results may be different. To solve this problem, we design an attention mechanism that adaptively learns and adjusts the influence factors of different channel signals, and optimizes the reconstruction results. The method proposed in this paper is only for the decoder, without any additional requirements for the encoder, so the encoder can use the conventional compression sampling method. Extensive experiments indicate the efficiency and robustness of the proposed method in the case of simulated data and real data.

In this paper, we propose a simultaneous wireless information and power transfer (SWIPT) aided integrated remote wireless sensor and satellite network. In particular, a terrestrial wireless sensor network (WSN) harvests energy from the radio frequency (RF) signal of an amplify-and-forward (AF) terrestrial relay and utilizes the harvested energy to transmit data to a satellite with the assistance of the relay. The satellite-relay link is assumed to undergo the Shadowed-Rician fading, and the channels between the sensor nodes and the terrestrial relay links are assumed to undergo Nakagami-m fading. By assuming that the energy harvesting (EH) technology is employed at the sensor nodes of the WSN and the AF protocol is employed at the terrestrial relay, we first derive the expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the signal to interference noise ratios (SINRs) for the sensor nodes at the relay and the satellite. Then, we derive the outage probability (OP) expressions of the sensor nodes at the relay and the satellite. Finally, average end-to-end throughput and energy efficiency expressions of the proposed network are derived. Theoretical analyses and Monte Carlo simulation results are presented to reveal the impact of system parameters on the performance gains.

The airborne mobile wireless networks (AMWNs) composed of unmanned aerial vehicles (UAVs) communication networks is one of the emerging application scenarios of the Space-Ground-Sea Integrated Networks in 6G. Due to its high mobility, UAV exhibits great advantages in assisted cellular network communication and emergency communication. The multi-antenna technology and quality of service (QoS) can help cellular networks reduce latency and improve network capacity. In this paper, we jointly optimize the transmit power and flight trajectory of the multiuser MISO UAV communication system to improve the total effective capacity of the system. Specifi-cally, zero-forcing (ZF) beamforming and block diagonalization are adopted to eliminate multiuser interference. In addition, the optimization problem with regard to maximizing the total effective capacity of the system under the condition of delay constraint is proposed. Furthermore, an iterative optimization algorithm jointly considering UAV trajectory and subchannel transmit power is considered, in which we use successive convex optimization techniques and the block coordinate descent method to solve the thorny non-convex problem. Simulation results verify the effectiveness and convergence of the proposed algorithm.

Recently, preventing road collapse caused by subsurface voids became an urgent problem that needs to be solved in the urban road safety area. While the most study in the field of subsurface object detection by deep learning method has only focused on the objects that can be acquired GPR B-scan data easily. This paper aims to realize the subsurface voids detection under the condition that lacks verified GPR B-Scan data. In this paper, a GPR B-Scan image augmentation method by SinGAN is proposed and the YOLOv5 object detection algorithm is applied correspondingly to detect subsurface voids from both real collected and generated GPR B-Scan data. The detection results show that the proposed technique realized subsurface voids detection in limited verified GPR B-scan data samples and become an inspiration for similar tasks that lacking training samples.

Ultra-dense network (UDN) is emerging as a promising solution to meet the 1000-fold wireless traffic volume increment in wireless communication systems. In order to inspire system design and evaluate performance, this paper develops a tractable analysis framework of multi-antenna UDNs over Nakagami-m fading channels, in which the base stations (BSs) of each tier are distinguished by spatial densities, transmit powers and numbers of antennas. Resorting to stochastic geometry model, we derive the closed-form expression of coverage probability. The analytical expression reveals the signal-to-interference-plus-noise ratio (SINR) invariance property of UDNs with Rayleigh fading only holds in some special case of Nakagami-m fading scenario. In order to observe intuitively the effects of system parameters on coverage probability, the asymptotic results are also given, which are verified to be almost accurate when the SINR threshold is greater than 6 dB. The area spectral efficiency (ASE) is also provided. Furthermore, an effective algorithm is proposed to design the optimal active BSs densities, maximizing the ASE with appropriate requirements of coverage probability.

Ultra-dense network (UDN) is emerging as a promising technology to satisfy the explosive data traffic requirement in the fifth generation wireless communication systems. In order to facilitate system design and evaluate performance, this paper develops a tractable analysis framework of K-tier UDNs over Nakagami-m fading channels, in which the base stations (BSs) of each tier have a particular spatial density and transmit power. Using stochastic geometry, we derive the closed-form expression of coverage probability for a typical user. The analytical expression reveals the signal-to-interference-plus-noise ratio (SINR) invariance property of UDNs with Rayleigh fading also holds in Nakagami-m fading scenario when each tier has the same fading parameter. The asymptotic expression with a simple form is also provided, from which it is convenient to observe the effects of system parameters on the coverage probability. The simulation results verify the asymptotic form is very accurate for moderate SINR targets, e.g., above 5 dB. The average outage rate of a typical user is also provided. Furthermore, an effective algorithm is proposed to find the optimal SINR threshold, maximizing the average outage rate with appropriate requirements of coverage probability.

In sixth-generation (6G) communication networks, ultrahigh-data rate and reliability are greatly vital for massive user connections and network sensors, such as Internet of Things (IoT) devices. Simultaneous wireless information and power transfer (SWIPT) has been evolved as an efficient strategy to enhance the reliability of wireless communication systems through prolonging the battery lifetime by harvesting energy from the received radio-frequency (RF) signals. Furthermore, cooperative relay sensors in IoT networks can extend the network coverage. In this article, we consider a massive multiple-input–multiple-output (MIMO) two-way relaying system, where the relay node splits the received RF signals into two power streams, one for information decoding (ID) and the other for energy harvesting (EH). Two classical and linear relay precodings, i.e., zero-forcing reception/zero-forcing transmission (ZFR/ZFT) and maximum-ratio combining/maximum-ratio transmission (MRC/MRT), are adopted to satisfy the requirements of high rate in this relay system. Different from prior work, the SWIPT technique and large-scale fading effects of MIMO channels are taken into account for deriving the asymptotic sum-rates of four prevalent power scaling cases when the number of relay antennas grows to infinity. Finally, the analytical results are evaluated by the presented simulation and numerical results.

Although the use of coordinated direct and relay transmission (CDRT) in non-orthogonal multiple access (NOMA) can extend the coverage, its duplicated transmission reduces the spectrum efficiency (SE) of NOMA. To improve the SE, we propose a spectrum-efficient scheme for NOMA-based CDRT over Nakagami-m fading channels. In this scheme, the base station (BS) connects with a cell-center user (CCU) directly while communicating with a cell-edge user (CEU) via a relay and the CCU. Then, the relay and the CCU use network coding to process and retransmit the signals sent by the BS first and the CEU later. Finally, the BS and the relay simultaneously broadcast downlink signals. We derive the closed-form expressions for the average SE, the user fairness index and the energy efficiency (EE) as well as the asymptotic average SE using both perfect and imperfect successive interference cancellation (SIC). Simulations verify the correctness of our theoretical analysis and the superiority of the proposed scheme in SE and EE.

Coordinated direct and relay transmission (CDRT) is a promising strategy to extend cell coverage. However, higher spectral efficiency (SE) cannot be guaranteed in CDRT due to the cooperative process. Thus, non-orthogonal multiple access (NOMA) based CDRT is investigated, where a relaying user assists a base station (BS) in communicating with a cell-edge user (CEU) while the BS directly communicates with a cell-center user (CCU). Specifically, a novel joint downlink-uplink adaptive scheme is proposed for NOMA-based CDRT to improve the SE further. The proposed scheme jointly designs uplink and downlink via NOMA and adaptive transmission to implement bidirectional communication. First, we study the performance of the proposed scheme under both perfect and imperfect successive interference cancellation (SIC), and closed-form expressions are derived for the outage probability, diversity order, outage throughput (OT), ergodic sum rate (ESR), and energy efficiency (EE). Then, an optimal power allocation algorithm using the segment optimization and a modified particle swarm optimization algorithm are proposed to maximize the ESR under perfect and imperfect SIC, respectively. Numerical results verify the superiority of the proposed scheme in terms of the ESR, OT, EE, and the outage performance of CEU. The effectiveness of the proposed power allocation algorithms is also validated.

In this paper, we investigate the multiple-input- multiple-output (MIMO) two-way amplify-and-forward (AF) relaying system with simultaneous wireless information and power transfer (SWIPT), where two users harvest energy from the relay signal by power splitting (PS) scheme. Under the transmit power constraints at all nodes, the energy optimization problem is formulated which maximizes the total residual energy of two users by optimizing the splitting ratios and the precoding matrixes at the relay and two users, while still guaranteeing sufficient signal-to-noise ratios (SNR) at two user nodes. We divide the complex non-convex objective problem into three subproblems which are then solved through the proposed alternating optimization (AO) scheme. Numerical results are provided to verify the analysis and demonstrate the efficiency of the proposed scheme.

In this paper, a multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay system with direct link is investigated, where simultaneous wireless information and power transfer (SWIPT) technique is applied at the multiple-antenna relay node which splits the received signal into two parts, one portion is used for information decoding (ID) and the other portion is adopted for energy harvesting (EH). By considering power splitting (PS) scheme of SWIPT, the relay node consumes the harvested energy to forward the ID signal to the destination. We design the precoding matrixes of the source and relay nodes to derive the achievable rate. Finally, the analytical results are validated by the simulations.

In this paper, a multiple-input multiple-output (MIMO) two-way amplify-and-forward (AF) relay system is investigated, where simultaneous wireless information and power transfer (SWIPT) technique is applied at the massive-antenna relay node which splits the received signal into two parts, one portion is used for information decoding (ID) and the other portion is adopted for energy harvesting (EH). By considering power splitting (PS) scheme of SWIPT, the relay node consumes the harvested energy to forward the ID signal to two users. When the number of relay antennas approaches to infinity, the deterministic sum-rate of the relay system is analyzed. The close-form expression of optimal PS factor is derived. Finally, the analytical results are validated by the simulations.

Image super-resolution (SR) plays a significant role in Internet of Vehicles (IoV), and is widely used in many important applications, such as object recognition and vehicle identification. However, in certain cases, the quality of acquired images is low and general SR algorithms are inapplicable. Aiming at the disadvantages of the traditional image super- resolution methods which are mainly based on interpolation and example learning, this paper utilizes compressed sensing (CS) and sequence information to present a new approach of image super-resolution. In order to keep high frequency information and reduce ringing and jagged artifacts, the proposed method takes advantage of the useful information between multiple image frames and jointly trains coupled dictionaries for the low- resolution (LR) and high-resolution (HR) image block pair. By fusing atoms of LR dictionary, the atom of HR dictionary is obtained and the HR image can be recovered in terms of the learned HR dictionary. The experimental results show that the proposed algorithm has better performance in both subjective assessment and objective standards, including Entropy and Average Gradient.

There is an increasing interest to combine satellite and terrestrial components to form a single telecom network, this is called integrated satellite and terrestrial mobile system. In such systems, the ground component is controlled by the satellite resource and network management system. Further, the ground component uses the same portions of MSS (Mobile Satellite Service) frequency bands. However, frequency reuse between satellite and terrestrial components will inevitably generate co-channel interferences between satellite and terrestrial networks. It is one of the important factors that not only affect the user experience, but may even affect the normal operation of the network. This paper presents a model of an integrated mobile network consists of a multi-beam satellite, terrestrial base stations and dual satellite/terrestrial terminals. The types of interferences in the integrated system were analyzed, and some serious scenarios of interferences were simulated. The influence of several parameters such as the number of terrestrial station, the azimuth angle of the terrestrial station relative to the satellite beam center and the maximum transmitting power of the terrestrial station is then presented. The results have shown that the interferences due to terrestrial base station on satellite uplink are nonnegligible and can have a serious impact on the overall system performance.

Since presented by K. Fall, the new-type network Delay and Disruption Tolerant Network (DTN) came to become a hot area of research. In recent years, many kinds of DTN routing algorithms have been proposed. With the characteristics of long time delay, high packet loss rate and intermittent connectivity. Satellite networks also belong to a kind of DTN. But meanwhile, they have their unique characteristics of satellite nodes regular running in orbits and predictable inter-satellite links on and off, for which deterministic routing algorithm is more suited in Satellite DTN networks. This paper focuses on studying the theoretical knowledge of a kind of deterministic DTN routing algorithm, Earliest-Delivery(ED) algorithm. And combining with the characteristics of the satellite network above, we propose an improved ED algorithm from three aspects of distributed routing, routing update strategy and tag - based dynamic storage scheme. Ultimately, we simulate the LEO/MEO two-layer satellite delay tolerant network in OPNET, and analyze the performance of two algorithms upon packet delivery ratio, average end-to-end delay and the number of packets destroyed in the storage queue. The result shows the improved algorithm performs better in satellite DTN network.

In this study, non‐orthogonal multiple access (NOMA)‐based coordinated direct and relay transmission (CDRT) is considered, where a base station ( BS ) directly communicates with two cell‐centre users (CCUs) while communicating with a cell‐edge user (CEU) via a relay. A novel dynamic scheme is proposed, in which the CCU close to the BS will act as a relay to assist the CEU in the second phase if it can obtain the prior information of the CEU in advance, otherwise it will switch to the receiving mode. To evaluate the system performance of the proposed scheme, the closed‐form expressions of the outage probability, diversity order and ergodic sum rate (SR) are, respectively, derived. Simulation results demonstrate that the proposed scheme attains greater diversity order for the CEU as well as superior outage performance without performance loss of the ergodic SR, compared with conventional one in NOMA‐based CDRT. In addition, a suboptimal power allocation (SPA) for this dynamic scheme is put forward, for which the closed‐form expression is also obtained. It is also indicated that the presented SPA for dynamic scheme achieves near‐optimal ergodic SR performance at high SNR region.

This paper treats a multiuser relay scenario, where multiple user equipments have a two-way communication with a common base station in the presence of a buffer-equipped relay station. Each of the uplink (UL) and downlink (DL) transmission can take place over a direct or over a relayed path. Traditionally, the UL and the DL path of a given two-way link are coupled, that is, either both are direct links or both are relayed links. By removing the restriction for coupling, one opens the design space for a decoupled two-way links. Following this, we devise two protocols: orthogonal decoupled UL/DL buffer-aided (ODBA) relaying protocol and non-ODBA (NODBA) relaying protocol. In NODBA, the receiver can use successive interference cancellation to extract the desired signal from a collision between UL and DL signals. For both protocols, we characterize the transmission decision policies in terms of maximization of the average two-way sum rate of the system. The numerical results show that decoupling association and non-orthogonal radio access lead to significant throughput gains for two-way traffic.

Cognitive radio (CR) is a critical technology for improving spectrum utilization and solving the radio spectrum scarcity problem. In CR devices, spectrum sensing is important to implement opportunistic spectrum access. Many spectrum sensing schemes have been proposed, including uncooperative, cooperative, centralized, and distributed algorithms. However, they aimed to obtain a global consensus sensing result, which may not always be possible in large-scale cognitive radio networks (CRNs) due to heterogeneous spectrum availability in different areas. Hence, some new spectrum sensing schemes should be designed to discover idle heterogeneous spectrum in CRNs. In this paper, we propose an intelligent cooperative spectrum sensing algorithm based on a non-parametric Bayesian learning model, namely the hierarchical Dirichlet process, which groups spectrum sensing data without the need to know the number of hidden spectrum states, and discovers a common sparse spectrum within each group. Furthermore, a concisely distributed information exchange scheme is designed, where intra-cluster and inter-cluster spectrum information is shared for global spectrum cognition. Experimental results show that the proposed algorithm can exploit the spatial relationship among sensed data to achieve a better spectrum sensing performance in terms of detection probability and false alarm probability.

We consider the topological interference management problem for a downlink hexagonal cellular network, where the channel state information at the transmitters is limited to just the network topology. Recent work by Jafar showed that if interference is limited to only near the cell boundary, then, an aligned frequency reuse pattern achieves the optimal value of 6/7 degrees of freedom (DoF) per cell, as opposed to the conventional frequency reuse baseline of 1/3 DoF per cell. We generalize the setting to include interference from multiple layers of adjacent cells and characterize how the gains of the optimal solution over basic frequency reuse diminish with increasing number of interference layers. Next, we focus on single-layer interference and explore the sensitivity of the idealized assumptions behind the connectivity model of Jafar, which achieves higher DoF but only at the cost of a higher effective noise floor than the baseline, and under idealized placements of users. A modified connectivity model that operates at a comparable noise-floor to the baseline is then studied, and its DoF are shown to be bounded above by 6/11 and below by 1/2. Through numerical simulations, we compare the solutions that achieve 6/7, 1/2, and 1/3 DoF per cell and find that, while both the 6/7 and the 1/2 DoF solutions beat the baseline 1/3 figure, between them, the 1/2 DoF aligned frequency reuse pattern is more robust for small cell networks particularly for random users' distribution on the cell boundaries.

Network coding, which works in the network layer, is an effective technology to improve the throughput of two-way relay networks. In this paper, we compare the existing network coding schemes: traditional network coding (NC) scheme, physical-layer network coding (PNC) scheme and soft network coding (SNC) scheme, and propose a new physical layer scheme which can be seen as the implementation of network coding in two-way relay networks. Relay nodes combine the received signals from two source nodes before demodulation and channel decoding. The computational complexity and BER performance of the proposed scheme are analyzed compared with the previous schemes. Theoretical analysis show that the proposed scheme can save 50% computational cost of demodulation and channel decoding processes compared with NC scheme, meanwhile increase the power efficiency of the relay nodes in two-way relay networks significantly. Future works with the proposed scheme are also discussed.

Recently, multimedia transmission over cognitive radio networks (CRNs) becomes an important topic due to the CR's capability of using unoccupied spectrum for data transmission. Conventional work has focused on typical quality-of-service (QoS) factors such as radio link reliability, maximum tolerable communication delay, and spectral efficiency. However, there is no work considering the impact of CR spectrum sensing frequency and packet-loading scheme on multimedia QoS. Here the spectrum sensing frequency means how frequently a CR user detects the free spectrum. Continuous, frequent spectrum sensing could increase the medium access control (MAC) layer processing overhead and delay, and cause some multimedia packets to miss the receiving deadline, and thus decrease the multimedia quality at the receiver side. In this research, we will derive the math model between the spectrum sensing frequency and the number of remaining packets that need to be sent, as well as the relationship between spectrum sensing frequency and the new channel availability time during which the CRN user is allowed to use a new channel (after the current channel is re-occupied by primary users) to continue packet transmission. A smaller number of remaining packets and a larger value of new channel availability time will help to transmit multimedia packets within a delay deadline. Based on the above relationship model, we select appropriate spectrum sensing frequency under single-channel case, and study the trade-offs among the number of selected channels, optimal spectrum sensing frequency, and packet-loading scheme under multi-channel case. The optimal spectrum sensing frequency and packet-loading solutions for multi-channel case are obtained by using the combination of Hughes-Hartogs and discrete particle swarm optimization (DPSO) algorithms. Our experiments of JPEG2000 packet-stream and H.264 video packet-stream transmission over CRN demonstrate the validity of our spectrum sensing frequency selection and packet-loading scheme.