Physical Communication最新文献

In this paper, we present new measurement results to model large-scale path loss, angular spread and channel sparsity at the sub-THz (141–145 GHz) band, for both indoor and outdoor scenarios. Extensive measurement campaigns have been carried out, taking into account both line-of-sight (LoS) and non line-of-sight (NLoS) propagation. For all considered propagation scenarios, omni-directional and directional path loss models have been developed, based on the so-called close-in (CI) free-space reference distance model. A power angular spread analysis is further presented. The sparsity of the wireless channel has also been studied by employing suitable metrics, namely the so-called Gini index (GI), the Ricean K-factor and the root mean square (RMS) delay spread.

Radio frequency fingerprint (RFF) based identification technique has been proved efficient for ensuring the validity of devices connected to network. However, it is still a tough task to extract robust RFF in the scenarios with multi-path channel and moving terminals. To solve this problem, this paper proposes a channel-resilient RFF extraction scheme which can effectively reduce the influences from complex channel condition and retain robust device fingerprint. In the proposed system, blind synchronization and symbol-scale carrier frequency offset (CFO) estimation are designed for signal preprocessing for preparations of the following RFF extraction. A cyclic-prefix based de-channel algorithm (CPDCA) which can effectively weaken channel interference is proposed to meet the channel robustness of our system. Additionally, symbol-scale feature stacking algorithm (SFSA) is applied for RFF denoising, which can further enhance the performance of proposed system. Experiments using practical dataset collected from Long Term Evolution (LTE)-V2X communication system has been carried out under different signal-to-noise ratio (SNR). The results demonstrate that the proposed scheme has the ability to extract channel-robust RFF and to achieve reliable classification performance under complex channel conditions.

This study presents a comprehensive analysis of the performance degradation effects of carrier frequency offset (CFO) on orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems operating over frequency-selective multipath fading channels. CFO is an impairing factor that degrades the signal-to-noise ratio (SNR) through signal attenuation and inter-carrier interference (ICI). We derive a closed-form expression to quantify the SNR degradation under CFO for OFDM-IM systems. Additionally, we formulate a very tight upper bound for the bit error rate (BER), accounting for index modulation errors, CFO distortion, and multipath fading.

The presented analytical formulations capture the unique characteristics of OFDM-IM systems and facilitate precise performance evaluation. The findings yield valuable insights into mitigating CFO-induced BER degradation through appropriate system parameter selection and CFO compensation techniques. Moreover, this investigation makes significant contributions towards designing reliable OFDM-IM communication links resilient to the combined effects of index modulation, frequency offsets, and dispersive channel conditions.

In this paper, we conduct a comparative study of two classes of convolutional low-density parity-check (LDPC) codes: block Markov superposition transmission (BMST) codes and staircase codes, which are both constructed by incorporating spatial coupling between LDPC coded blocks. By examining the differences and similarities between the two classes of codes in coding, decoding, performance, and complexity, we demonstrate that the BMST-LDPC codes exhibit lower complexity and superior waterfall performance, but have higher error floors. We present two approaches to reduce the error floors. One approach is to use conventional concatenated codes with Bose–Chaudhuri–Hocquenghem (BCH) codes as outer codes, which allows for the prediction of error floors. The other approach is to use free-ride coding for cyclic redundancy check (CRC) bits, which is applicable to staircase-LDPC codes and does not result in any loss of code rate. Additionally, we propose double-check to reduce effectively the mis-correction probability, enabling the decoder to stop the iterative decoding process early without error propagation, thereby reducing complexity. Simulation results show that the proposed scheme can improve the performance of the staircase code, constructed using a variant of the 5G LDPC code, by achieving a gain of about $0.2\mathrm{dB}$ at a bit error rate (BER) of $10^{-7}$ without any loss of code rate, and reduce the decoding complexity by approximately 40%.

With the widespread adoption of wireless technology, there has been a significant surge in the number of devices seeking wireless connectivity over the past decade. To meet the extensive demand for high-data-rate wireless connectivity, the fifth-generation (5G) cellular network plays a pivotal role. 5G cellular network aims to support a large number of applications with ultra-high data rates by maximizing device connectivity while satisfying quality of service (QoS) requirements. In this paper, we present an innovative priority-based subcarrier allocation (PSA) algorithm to address the challenge of maximizing connectivity in 5G new radio (5G NR) networks. Initially, we formulate the connectivity maximization problem as a subcarrier allocation problem by considering three key parameters: bandwidth requirement, waiting time, and energy level of user devices. The objective of the formulated problem is to optimally allocate subcarriers to multiple users in order to maximize connectivity while maintaining QoS requirements. To address the problem, we propose the PSA algorithm that prioritizes bandwidth, waiting time, and energy parameters using the R-method. To accommodate the network scenarios, we develop three variants of the PSA algorithm—PSA-1, PSA-2, and PSA-3. These variants allocate subcarriers based on the priority-based score of user. We carried out a simulation-based study to illustrate the effectiveness of our proposed algorithm in comparison to traditional methods. The simulation results reveal that our proposed algorithms outperform first come first serve (FCFS) and longest remaining time first (LRTF), and achieves comparable or superior results compared to priority and fairness-based resource allocation with 5G new radio numerology (PFRA-0N) in terms of the number of user allocations, average user allocation ratio, user drop ratios and average connectivity rate. Compared to the shortest job first (SJF) technique, our proposed PSA algorithm performance is slightly inferior in terms of the number of user allocations, average allocation ratio and average connectivity rate; however, it shows superior performance in drop ratios. Further, the proposed algorithms show significant improvements in execution time compared to the optimal exhaustive search solution.

The proliferation of various Internet of Everything applications places urgent demand for high energy efficiency, massive connection and wide coverage for the future communication era. Motivated by this, rate-splitting multiple access (RSMA) and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has attracted wide publicity from industry and academia. In this paper, we consider a STAR-RIS assisted two-user RSMA network with imperfect successive interference cancellation, and all channels are modeled as Nakagami-$m$ distribution. By adopting effective capacity (EC) as the metric, we analyze the system performance under certain quality-of-service constraint. Specifically, analytical expressions of EC for a pair of RSMA users are provided. To explore further insights, high signal-to-noise ratio (SNR) conditions are also considered. Furthermore, the effect of some specific elements on system EC performance are analyzed, and some significant conclusions are obtained as follows: (1) As SNR grows, the effective capacities of two users improve, but finally converge to constant at high SNR. (2) The increase in the amount of the STAR-RIS elements can obviously increase the effective capacities. (3) Compared to traditional STAR-RIS assisted non-orthogonal multiple access networks, STAR-RIS assisted RSMA network has distinct advantages to improve system EC performance.

A rate splitting multiple access (RSMA)-based dual-unmanned aerial vehicle (UAV) secure communication system is proposed in this paper, where one UAV is deployed to communicate with ground users, while the other UAV is dispatched to transmit the jamming signal to a ground eavesdropper. Considering the limited energy of UAV batteries, the minimum secrecy rate is maximized via optimizing RSMA precoding matrix and trajectories of UAVs under the constraint of UAV energy consumption. To address the complexity arising from coupled variables, the optimization problem is decomposed into two equivalent subproblems: precoding matrix optimization and UAV trajectory design. This decomposition is achieved using the block coordinate descent method. Next, the subproblems are transformed into convex forms by using semidefinite relaxation and successive convex approximation techniques, which are iteratively solved until convergence. Simulation results show that the secrecy performance of RSMA scheme is superior to that of the benchmark schemes, Specifically, the average secrecy rate of the RSMA scheme is approximately 22% and 10.8% higher than that of the NOMA and TDMA schemes, respectively.

The surge in educational, entertainment, multimedia, and gaming applications used by the number of users necessitates substantial data rates, compelling the exploration of the untapped spectrum in the forthcoming sixth-generation (6G) networks. Traditional networks fall short of meeting the escalating demands, prompting the integration of cognitive radio networks (CRNs) in 6G. Cognitive radio (CR) technology enhances spectrum utilization by opportunistically accessing unused spectrum when not in use by licensed users. In CRN, primary users (PUs) are served by the primary radio base station (PBS), while the secondary radio base station (SBS) utilizes opportunistic spectrum access using spectrum sensing, catering specifically to secondary users (SUs). Hybrid multiple access (HMA) as a combination of orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA), is introduced to further accommodate the increasing number of users in 6G, ultimately enhancing spectral efficiency. Notably, this paper investigates a novel CR based cluster assisted downlink HMA (CR-CDHMA) in CRN to jointly optimize the network rate, user admission in clusters, user association with SBS, user-channel allocation obtained through opportunistic spectrum access using spectrum sensing, and fairness in power allocation. A novel mathematical problem based on the proposed network model is formulated as a mixed-integer nonlinear programming (MINLP) problem, addressed through an $ϵ$-optimal outer approximation algorithm (OAA). Extensive simulations confirm the novel proposed technique’s effectiveness in 6G CRN rate improvement, user admission in clusters, user association with SBS, user-channel allocation obtained through opportunistic spectrum access using spectrum sensing, and fairness in power allocation under the constraints of false-alarm, missed-detection, and quality of service (QoS) surpassing performance compared to the existing OMA only assisted CRN and NOMA-only assisted CRN. An $ϵ$-optimal algorithm achieves results with $ϵ=10^{-3}$, demonstrating its computational efficiency.

With the development of power systems, digital distance protection, as an innovative and cutting-edge technology, plays a crucial role in ensuring the stable operation of the power grid. Due to its high precision, rapidity, and reliability, digital distance protection has become a key component of power system safety. Distance protection is widely used in distribution networks at or below 35 kV. Therefore, studying its adaptability and effectiveness as a remote backup protection can provide an effective foundation for improving grid security.With the utilization of Python and PSCAD, the adaptability of digital distance protection is meticulously examined in the context of low voltage side faults in 110 kV/35 kV transformers, specifically as a remote backup protection measure. The core objective of this investigation is to assess the efficacy of this protection strategy in upholding the safety and reliability of power systems. To achieve this, 3 approaches is employed: theoretical analysis, simulation modeling, and experimental validation. This process allows for a comprehensive evaluation of the performance characteristics and application efficacy of digital distance protection. The insights garnered from this meticulous study offer profound understanding into the strengths and potential limitations of this protection paradigm, serving as a solid foundation for the refinement of existing protection strategies and the enhancement of the overall resilience of power systems. In essence, this article aims to evaluate the effectiveness of digital distance protection as a remote backup protection strategy for faults on the low-voltage side of 110 kV/35 kV transformers. The core objective is to assess the efficacy of this protection strategy in maintaining the safety and reliability of the power system.

In this paper, we investigate the physical layer security (PLS) of a cognitive radio network (CRN) assisted by a reconfigurable intelligent surface (RIS) based on discrete phase control. Specifically, the phase shifts of the RIS are designed to maximize the received signal-to-noise ratio (SNR) at the secondary receiver. In the presence of passive eavesdropping, we address the secrecy outage performances for the considered system under two different scenarios whether the direct link exists or not. To characterize the performance, novel exact expressions of secrecy outage probability (SOP) are derived leveraging the Gaussian–Chebyshev quadrature. We also conduct the asymptotic analysis to study the influence of the main parameters such as the number of reflect elements of RIS and the number of quantization bits on the secrecy performance of our proposed system. Finally, our analytical results are verified through performing Monte Carlo simulations. Simulation results show that significant security enhancement can be achieved in CRN by employing the RIS.