IET Communications最新文献

Traditional pseudo-satellite-based indoor positioning techniques are greatly affected by the presence of multipath effects, leading to a notable reduction in the positioning precision. In order to tackle this challenge, a pseudo-satellite indoor positioning method based on deep learning is proposed. The method grids the localization region, thus transforming positioning from a regression problem to a classification problem in the gridded areas. 1D-convolutional neural network is employed to extract the correlation between pseudo-satellite data and the positioning of indoor areas. Data are collected and the method is validated in three types of areas of the experimental field, namely unobstructed area, semi-unobstructed area and obstructed area. The experimental results demonstrate that the method exhibits superior positioning accuracy compared to traditional methods, enabling effective localization even in obstructed area.

This study analyses the interference effect in a visible light-non-orthogonal multiple access (VL-NOMA) network that considers the signal power parameters performance for near and far users. The light-emitting diode (LED) as a carrier transmits signals, and we investigate the interference effect. The interference effect challenge is a result of unaligned signal power parameters, thereby producing noise or echo during the signal transmission. The signal power parameters are successfully aligned, and NOMA techniques are deployed, which improves the signal performance in terms of bit-error rate (BER), achieved data rate, and signal-to-interference plus noise ratio (SINR). Furthermore, the deployed NOMA techniques, such as power allocations (PA) to assign the signals appropriately, then superposition coding (SC) encodes the entire signal, and successive interference cancellation (SIC) cancels the interference within the signals. The signal behavior of the aligned and the unaligned signal power parameters performance are used to investigate the interference effect. We observed that unaligned signal power parameters reduce the signal performance of achieved data rate, BER, and SINR. Further, the aligned signal power parameter with NOMA techniques improves the signal performance. Moreover, in the aligned signal power scenario of NOMA, the near user performed better than the far user.

In the context of certain specific digital communication systems, where there are limitations such as spectral resources and energy availability, continuous phase modulation (CPM) emerges as an appealing choice among various modulation methods. Among CPM signals, multi-h CPM is particularly noteworthy for its ability to address these constraints within the realm of single-carrier and constant-envelope waveforms. At the physical layer, the design of a multi-h CPM receiver necessitates the efficient implementation of timing and frequency synchronization algorithm within a high dynamic environment. So this paper presents an innovative approach for achieving timing and frequency synchronization. To rectify timing offset and mitigate the adverse effects of noise in received signals, a re-configurable local filter generation method is integrated into the timing synchronization algorithm. Simultaneously, an enhanced least mean square adaptive filter algorithm is applied to address frequency synchronization. A comprehensive series of simulations rigorously evaluates the outcomes of proposed novel synchronization methodology. These analyses demonstrate a notable proximity between the synchronization errors of proposed algorithm in this paper and the performance benchmark set by the modified Cramer–Rao bound. The proposed synchronization technology also exhibits the capability to substantially reduce the bit error rate, thereby effectively enhancing demodulation performance in multi-h CPM receivers.

Joint sensing and communications systems have gained significant research interest by merging sensing capabilities with communication functionalities. However, few works have examined the case of multiple users. This work investigates a dual-user joint sensing and communications system, focusing on the interference between the users that explores the optimal performance trade-offs through a time-division approach. Bi-static radar setting is considered. Two typical strategies under this approach are studied: one in which both users follow the same order of communications and then sensing, and the other in which the tasks are performed in opposite order at two users. In each strategy, the sum rate and the detection probability are evaluated and optimized. The results show that the opposite order strategy offers superior performance to the same order strategy, and they also quantify their performance difference. This research highlights the potential benefits of time-division strategies and multiple users in joint sensing and communications systems.

The ultra-dense deployment of pico cells in 5G heterogeneous networks (HetNets) has raised serious concerns regarding interference and energy consumption. Both industry and academia are focusing on enhancing network energy efficiency (EE) while maintaining satisfactory quality of service (QoS) levels. However, finding an optimal solution to NEE is very challenging, especially in ultra-dense HetNets. Here, a user association and power management algorithm is presented that follows a heuristic approach and aims to maximize EE while satisfying other network requirements. The proposed algorithm associates users based on criteria that consider the users’ EE and minimizes energy consumption by intermittently switching into sleep mode base stations with the highest impact on overall network EE. The performance of this solution is evaluated in a realistic multi-cell two-tier scenario considering both co-tier and cross-tier interference by comparing it with two other solutions: a heuristic approach based on standardized eICIC, and an optimization approach based on Lagrangian dual decomposition. The simulation results show that our solution outperforms benchmarking solutions in terms of EE, average user rate, and network throughput while minimizing energy consumption.

Turbo codes play a crucial role in wireless communication systems, and their compiled code structures are key factors affecting the performance of the entire communication system. As a result, the study of turbo compiled code structures has been a focal point for researchers. The iterative decoding of turbo code structures has multiple limitations and large storage resource consumption, leading to poor system anti-interference ability and a rapid increase in BER. To address these issues, this paper proposes the mimic turbo compiled code structure (MTCCS) for wireless communication systems. MTCCS is based on the DHR idea, incorporating dynamic, heterogeneous, and redundancy characteristics. Dynamicity is achieved through a dynamic scheduling algorithm based on abnormal feedback information. Heterogeneity is achieved through a codec component collection design method based on intrinsic and extrinsic heterogeneity. Redundancy is achieved through a majority voting algorithm. At the beginning of information transmission, MTCCS randomly selects heterogeneous codecs from the heterogeneous codec collection to enter the runtime pool. After the information transmission is complete, the majority voting algorithm is used to adjudicate the multi-mode output of the codecs, resulting in a relatively accurate decoding outcome. Meanwhile, the dynamic scheduling module calculates the abnormal feedback information of each codec and accordingly dynamically schedules the mimic turbo codecs to replace the abnormal ones. Through the above process, MTCCS realizes the adaptive compilation code and improves the anti-interference ability of turbo code. Simulation experiments are conducted on MTCCS in both non-interference and interference scenarios. Simulation experiments show that MTCCS introducing the DHR idea achieves a balance between anti-interference and decoding performance. It effectively addresses the issue of poor anti-interference ability in turbo codes, and the decoding performance of MTCCS is superior to that of the previous single conventional turbo codes.

In the era of industry 4.0 and the widespread use of digital devices, the number of cyber attacks poses an escalating and diverse threat, jeopardizing users' online activities. Intrusion detection systems (IDS) emerge as pivotal solutions, playing a crucial role in detecting anomalous signals within network systems. To counter novel attack patterns, IDS systems require periodic rule updates for effective identification of unusual signals. Typically, these policies are updated based on rule-based or deep learning algorithms to enhance detection performance. However, the insufficient number of labeled samples remains a challenge for real-world deployment. In this article, an automated labeling method is presented that has shown high effectiveness, requiring minimal hardware resources, and applicable to IDS systems. Additionally, the approach utilizes transfer learning combined with attention mechanisms to boost the efficiency of abnormal signal detection. The results from the approach are compared with those of a reference model, illustrating an overall improvement of nearly 10% in our model's performance compared to the reference model. This underscores the effectiveness of automating rule adjustments for IDS, contributing significantly to reducing associated financial costs. The research addresses the challenges in deploying IDS in real-world scenarios and provides a valuable contribution to enhancing cyber threat detection capabilities.

A preprint has previously been published [11].

This study investigates the integration of dimmable constant weight polar-coded non-orthogonal multiple access (NOMA) with orthogonal space-time block coding (OSTBC) in visible light communication (VLC) systems over Nakagami-$�m$ fading environments. The proposed scheme aims to enhance the reliability of VLC systems by reducing the outage probability while accommodating dimming requirements. By allowing multiple users to utilize the same time-frequency resources and adjust power levels based on individual channel conditions, the system optimizes resource utilization. Additionally, the OSTBC method provides effective communication among multiple users by leveraging transmit diversity to improve system performance. The efficacy of the proposed approach is demonstrated through analytical analysis and Monte Carlo simulations, showcasing superior outage probability performance compared to conventional Alamouti-STBC schemes.

Codeword position index based sparse code multiple access (CPI-SCMA) is an effective scheme that expands codeword positions in the time domain and carries extra information by their index. This paper proposes a dual-mode CPI-SCMA (DCPI-SCMA) scheme to improve the error propagation caused by the mismatch between SCMA codewords and information bits. Furthermore, a DCPI-SCMA with transmit diversity scheme is proposed where index bits are repeatedly transmitted to obtain a transmit diversity gain; hence, a higher reliability can be achieved with a slight loss of spectral efficiency. An optimal approach for the codebook index pattern is derived where the decision of index bits is involved in the demodulation of SCMA. It can be seen from simulation results and system analysis that the proposed schemes achieve better bit error rate performance with a decrease in complexity and obtain better robustness and flexibility compared with the existing CPI-based SCMA schemes under the same spectral efficiency.