Accurate localization is critical for vehicle-toinfrastructure (V2I) communication systems, especially in urban areas where GPS signals are often obstructed by tall buildings, leading to significant positioning errors, necessitating alternative or complementary techniques for reliable and precise positioning in applications like autonomous driving and smart city infrastructure. This paper proposes a multimodal contrastive learningbased regression framework for V2I localization. By integrating channel state information (CSI) with visual data, the framework achieves enhanced accuracy and reliability. The approach leverages the complementary strengths of wireless and visual data to overcome the limitations of traditional localization methods, offering a robust solution for V2I applications. Simulation results demonstrate that the proposed CSI-vision fusion model significantly surpasses both traditional and unimodal benchmarks, delivering superior localization precision in challenging urban environments.

Ensuring secure and efficient multi-user (MU) transmission is critical for vehicular communication systems. Chaos-based modulation schemes have garnered considerable interest owing to their inherent advantages in physical layer security. However, most existing MU chaotic communication systems, particularly those based on non-coherent detection, suffer from low spectral efficiency due to reference signal overhead and limited user connectivity under orthogonal multiple access (OMA). Although non-orthogonal schemes such as sparse code multiple access (SCMA)-based differential chaos shift keying (DCSK) have been explored, they incur high computational complexity and exhibit inflexible scalability owing to fixed codebook designs. This paper proposes a deep learning-assisted power-domain non-orthogonal multiple access chaos shift keying (DL-NOMA-CSK) system for vehicular communications. A deep neural network (DNN)-based demodulator is designed to learn the intrinsic characteristics of chaotic signals during offline training, thereby eliminating the need for chaotic synchronization or reference signal transmission. The demodulator employs a dual-domain feature extraction architecture that jointly processes time-domain and frequency-domain information of the received chaotic signals, enhancing feature learning under dynamic channel conditions. The DNN is integrated into a successive interference cancellation (SIC) framework to mitigate error propagation. Theoretical analysis and extensive simulations demonstrate that the proposed system achieves superior performance in terms of spectral efficiency (SE), energy efficiency (EE), bit error rate (BER), security, and robustness compared to conventional MU-DCSK and existing deep learning-aided schemes. These advantages confirm the practical viability of the proposed system for secure vehicular communications.

We propose a multiple chirp rate index modulation (MCR-IM) system based on Zadoff-Chu (ZC) sequences that overcomes the problems of low transmission rate and large-scale access in long-range wide-area network (LoRaWAN) using classical LoRa modulation. We demonstrate the extremely low cross-correlation of MCR-IM signals across different spread factors, showing that the proposed MCR-IM system also inherits the characteristics of ZC sequences modulation. Moreover, we derive an approximate approximate closed-form expression for the bit-error-rate (BER) of the proposed MCR-IM system over Nakagami-mfading channels. Simulation results confirm the accuracy of the derived approximate closed-form expression and demonstrate that the MCR-IM system achieves higher levels of spectral efficiency (SE) compared to existing systems like frequency-shift chirp spread spectrum with index modulation (FSCSS-IM), group-based CSS (GCSS), layered CSS (LCSS), and layered group-based CSS (LGCSS). In this context, assigning multiple chirp rates to each user results in a reduction in the number of parallel channels. To mitigate this issue, we propose a peak detection based successive interference cancellation (PD-SIC) algorithm to accommodate more users. Results further show that the proposed system with the PD-SIC algorithm achieves a lower BER and higher throughput than the orthogonal scatter CSS (OrthoRa) system under collision scenarios, making it a compelling solution for future large-scale, high-throughput Internet of Things network.

In this paper, we propose BeamLLM, a vision-empowered millimeter-wave (mmWave) beam prediction framework leveraging large language models (LLMs) to enhance the accuracy and robustness of beam prediction. By integrating computer vision (CV) with LLMs’ cross-modal reasoning capabilities, the framework extracts user equipment (UE) positional features from RGB images and aligns visual-temporal features with LLMs’ semantic space through reprogramming techniques. Evaluated on a realistic vehicle-to-infrastructure (V2I) scenario, BeamLLM achieves 61.01% top-1 accuracy and 97.39% top-3 accuracy in standard prediction tasks, outperforming traditional deep learning models. In few-shot prediction scenarios, performance degradation is limited to 12.56% (top-1) and 5.55% (top3) from time sample 1 to 10, demonstrating superior prediction capability.

Chaotic signals are spread-spectrum nonlinear signals with initial value sensitivity that can potentially provide safe and anti-jamming digital communication systems. However, to reduce receiver complexity and achieve smooth demodulation, traditional chaos-based wireless communication systems require the transmission of additional chaotic reference signals, which reduces the spectral efficiency and degrades the security characteristics of the chaotic signals. Recent work has explored deep learning (DL)-aided transceivers to address these issues. However, these techniques have not yet fully exploited the inherent characteristics of chaotic signals, e.g., spectral properties. To maximize the potential of chaotic signals in wireless communication, this paper proposes a power spectral density-based deep learning chaos shift keying (PSD-DLCSK) receiver. The proposed PSD-DLCSK scheme effectively utilizes the spectral properties of chaotic signals, where the PSD of received signals serves as input to a deep neural network (DNN) for symbol detection. The proposed DNN architecture combines long short-term memory networks with self-attention mechanisms to effectively capture the temporal dependencies and spectral properties of chaotic signals, enabling reliable intelligent demodulation without chaotic reference signals. Extensive simulations demonstrate that PSD-DLCSK achieves superior bit error rate (BER) performance compared to traditional receivers as well as other DL-aided schemes over additive white Gaussian noise and multipath Rayleigh fading channels.

Although LoRa has emerged as the leading technology among the rapidly developing low-power wide-area networks, the performance of the LoRa system severely deteriorates over fading channels. To address this problem, in this paper, we introduce multiple reconfigurable intelligent surfaces (multi-RISs) into the LoRa system to improve its performance. Our specific focus is on the impact of outdated channel state information (CSI), the imperfection of estimated CSI, and the design of RIS discrete phase shifts on the performance. To this end, we first use the moment-matching method to obtain the end-to-end (E2E) channel coefficient of the joint outdated channels and erroneous channels over Nakagami-m fading. Moreover, the closed-form bit error rates (BERs) of the proposed system with non-coherent and coherent detections are derived. The results reveal that, in the high signal-to-noise ratio (SNR) regime, coherent detection encounters the error floor and performs worse than non-coherent detection. Furthermore, we also analyze delay outage rate, throughput, and achievable diversity order of the proposed system. The results show that, despite the presence of outdated CSI and channel estimation errors, the proposed system is still superior to RIS-aided LoRa systems adopting blind transmission and RIS-free ones. Finally, we also thoroughly investigate the effects of various important factors such as the correlation factor, channel estimation errors, the number of RIS reflecting elements, and the number of quantization bits for RIS discrete phase shifts on the performance.

In this article, we propose a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)- and energy buffer-aided multiple-input-single-output (MISO) simultaneous wireless information and power transfer (SWIPT) nonorthogonal multiple access (NOMA) system, which consists of a STAR-RIS, an access point (AP), and reflection users and transmission users with energy buffers. In the proposed system, the multiantenna AP can transmit information and energy to several single-antenna reflection and transmission users simultaneously by the NOMA fashion in the downlink, where the power transfer and information transmission states of the users are modeled using Markov chains. The reflection and transmission users harvest and store the energy in energy buffers as additional power supplies, which are partially utilized for uplink information transmission. The power outage probability, information outage probability, sum throughput, and joint outage probability closed-form expressions of the proposed system are derived over Nakagami-m fading channels, which are validated via simulations. Results demonstrate that the proposed system achieves better performance as compared to the proposed system with discrete phase shifts, the STAR-RIS-aided MISO SWIPT-NOMA buffer-less, conventional reconfigurable intelligent surface (RIS)- and energy buffer-aided MISO SWIPT-NOMA, and STAR-RIS- and energy buffer-aided MISO SWIPT-time-division multiple access (TDMA) systems. Furthermore, a particle swarm optimization-based power allocation (PSO-PA) algorithm is designed to maximize the uplink sum throughput with a constraint on the uplink joint outage probability and Jain’s fairness index (JFI). Simulation results illustrate that the proposed PSO-PA algorithm can achieve an improved sum throughput performance of the proposed system.

It has been proved that a long-range (LoRa) system can achieve long-distance and low-power transmission. However, the performance of LoRa systems can be severely degraded by fading. In addition, LoRa technology typically adopts an ALOHA-based access mechanism, which inevitably produces interfering signals for the target user. To overcome the effects of fading and interference, we introduce a reconfigurable intelligent surface (RIS) to LoRa systems. In this context, both non-coherent and coherent detections are considered and their bit error rate (BER) performance analyses are conducted. Moreover, we derive the closed-form BER expressions for the proposed system over Nakagami-m fading channels. Simulation results are used to verify the accuracy of our proposed analytical results. It is shown that in the presence of the interference, the proposed system outperforms RIS-free LoRa systems, and RIS-aided LoRa systems adopting blind transmission. In addition, we also compare the proposed system to single-user RIS-aided LoRa systems adopting blind transmission, and the results show that the proposed system maintains its superior performance even in the presence of the interference. Furthermore, the impacts of the spreading factor (SF), the number of reflecting elements, and the Nakagami-m fading parameters are investigated. It is shown that increasing the number of reflecting elements can remarkably enhance the BER performance, which is an affective measure for the proposed system to balance the trade-off between data rate and coverage range. We further observe that the BER performance of the proposed system is more sensitive to the fading parameter m at high signal-to-noise ratios.

A lightweight secure communication scheme, i.e., orthogonal frequency division multiplexing with index modulation using artificial noise (OFDM-IM AN), is proposed in this letter, which integrates the artificial noise into OFDM-IM to interfere the eavesdropper (Eve) from physical layer. In the proposed scheme, ANs are generated using channel state information (CSI) of legitimate link through a differential way, so the ANs will be eliminated at the legal receiver by the differential demodulation. Since the wiretap channel is independent of the legitimate channel, Eve will be confused by AN and make wrong detection. We derive both the tight upper bound on the bit error rate (BER) and the security rate of the proposed scheme. Simulation results show that though the BER performance of OFDM-IM AN is worse than that of OFDM-IM with the same configuration, the proposed scheme can enhance the security of OFDM-IM with a low complexity.

This paper proposes an energy buffer and reconfigurable intelligent surface (RIS) aided differential chaos-shift-keying (DCSK) wireless-powered communication (WPC) system, which includes an access point (AP), a RIS, and a source node equipped with an energy buffer. In such system, the source node first harvests and stores radio-frequency energy from the AP in the downlink, then uses the stored energy to transmit information to the AP in the uplink. A simple time-switching scheme for the proposed system is designed. Two different energy management policies at the source node are considered, i.e., best-effort policy (BEP) and on-off policy (OOP). The bit-error-rate (BER) expressions of the proposed system with BEP and OOP are derived over multipath Rayleigh fading channels. Results demonstrate that the proposed system is able to achieve better BER performance than the conventional DCSK-WPC system and the RIS aided DCSK-WPC buffer-less system, while keeping the non-coherent feature of the DCSK system.

This paper proposes a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided wireless-powered non-orthogonal multiple access (NOMA) system, which includes an access point (AP), a STAR-RIS, and two non-orthogonal users located at both sides of the STAR-RIS. In this system, the users first harvest the radio-frequency energy from the AP in the downlink, then adopt the harvested energy to transmit information to the AP in the uplink concurrently. Two policies are considered for the proposed system. The first one assumes that the time-switching protocol is used in the downlink while the energy-splitting protocol is adopted in the uplink, which is referred to as time-switching and energy-splitting policy (TEP). The second one assumes that the energy-splitting protocol is utilized in both the downlink and uplink, which is referred to as double energy-splitting policy (EEP). The outage probability, sum throughput, and average age of information (AoI) of the proposed system with TEP and EEP are investigated over Nakagami-$m$fading channels. In addition, we also analyze the outage probability, sum throughput, and average AoI of the STAR-RIS aided wireless-powered time-division-multiple-access (TDMA) system. Simulation and numerical results demonstrate that the proposed system with TEP and EEP yields better performance than baseline schemes. Although the proposed system sacrifices the outage probability and average AoI performance compared to STAR-RIS aided wireless-powered TDMA systems, it significantly enhances the sum throughput. Furthermore, we design a genetic-algorithm based time allocation and power allocation (GA-TAPA) algorithm to maximize the sum throughput and ensure a certain average AoI. Simulation results indicate that the proposed GA-TAPA algorithm can further improve the sum throughput of the proposed system.

In this paper, we investigate the performance of space-time block-coded multiple-input-multiple-output (STBCMIMO) LoRa system over Nakagami-m and Ricean fading channels with perfect and imperfect channel state information (CSI). Specifically, we derive the closed-form bit-error-rate expressions and analyze the diversity order of the STBC-MIMO LoRa system with perfect and imperfect CSI, where two common channel estimation error models are considered. Moreover, we perform simulations to evaluate the coverage performance of the system and to verify the accuracy of the theoretical analyses.

As an attempt to tackle the low-data-rate issue of the conventional LoRa systems, we propose two novel frequency-bin-index (FBI) LoRa schemes. In scheme I, the indices of starting frequency bins (SFBs) are utilized to carry the information bits. To facilitate the actual implementation, the SFBs of each LoRa signal are divided into several groups prior to the modulation process in the proposed FBI-LoRa system. To further improve the system flexibility, we formulate a generalized modulation scheme and propose scheme II by treating the SFB groups as an additional type of transmission entity. In scheme II, the combination of SFB indices and that of SFB group indices are both exploited to carry the information bits. We derive the theoretical expressions for bit error rate (BER) and throughput of the proposed FBI-LoRa system with two modulation schemes over AWGN and Rayleigh fading channels. Simulation results not only verify the accuracy of theoretical BER and throughput analyses but also show that the proposed FBI-LoRa schemes can significantly increase the transmission throughput compared with the existing LoRa systems at the expense of a slight loss in BER performance. The proposed FBI-LoRa system is a promising alternative for high-data-rate Internet of Things (IoT) applications.

In conventional star-topology LoRa networks, the gateways are expected to collect the data from all the nodes nearby. However, a major challenge for the conventional LoRa system is the performance degradation due to the long-range communication over fading channels. To resolve the challenging issue, this paper investigates a two-hop amplify-and-forward relaying LoRa network in a two-dimension plane, where random nodal distances are considered. Moreover, a relay-selection mechanism is developed for the proposed system. Based on the best relay-selection protocol, the analytical bit-error-rate (BER) and asymptotic BER expressions, achievable diversity order, coverage probability, and throughput of the proposed system are derived over the Nakagami-$m$fading channel. Furthermore, to maximize the throughput of the proposed system, a two-dimensional resource allocation optimization problem (i.e., the spread factor selection and power allocation optimization) is formulated and investigated. The proposed optimal spread factor selection and power allocation scheme is verified to outperform the two baseline schemes. Simulation and numerical results show that although the proposed system reduces the throughput compared to the conventional LoRa system, it significantly improves the BER and coverage probability. Hence, the proposed system can be considered as a promising technique for low-power, long-range and highly reliable Internet-of-Things applications.

Code index modulated multi-carrier M-ary differential chaos shift keying (CIM-MC-M-DCSK) system not only inherits low-power and low-complexity advantages of the conventional DCSK system, but also significantly increases the transmission rate. This feature is of particular importance to Internet of Things (IoT) with trillions of low-cost devices. In particular, for e-health IoT applications, an efficient transmission scheme is designed to solve the challenge of the limited battery capacity for numerous user equipments served by one base station. In this paper, a new multiple-input-single-output simultaneous wireless information and power transfer (MISO-SWIPT) scheme for CIM-MC-M-DCSK system is proposed by utilizing orthogonal characteristic of chaotic signals with different initial values. The proposed system adopts power splitting mode, which is very promising for simultaneously providing energy and transmitting information of the user equipments without any external power supply. In particular, the new system can achieve desirable anti-multipath-fading capability without using channel estimator. Moreover, the analytical bit-error-rate expression of the proposed system is derived over multipath Rayleigh fading channels. Furthermore, the spectral efficiency and energy efficiency of the proposed system are analyzed. Simulation results not only validate the analytical expressions, but also demonstrate the superiority of the proposed system.

LoRa is a modulation technology for low power wide area networks (LPWAN) with enormous potential in 5G era. However, the performance of LoRa system deteriorates seriously in fading-channel environments. To tackle this problem, in this paper we introduce multiple-input-multiple-output (MIMO) configuration employing space-time block coding (STBC) schemes into the LoRa system to formulate an STBC-MIMO LoRa system. Then, we investigate the theoretical performance of the proposed system over Rayleigh fading channels. To this end, we derive the distribution of the decision metric for the demodulator in the proposed system. Based on the above distribution, we propose a closed-form approximate BER expression of the proposed system when perfect and imperfect channel state information (CSI) are considered. Furthermore, we analyze the diversity order and the throughput of the proposed system. The results of the diversity analysis demonstrate that the diversity order of the system in the imperfect CSI scenario with fixed channel estimate error variance is zero. However, in the imperfect CSI scenario with a decreasing channel estimate error variance and the perfect CSI scenario, the system can achieve full diversity. In addition, the results of the throughput analysis show that the throughput of the proposed system is little affected by CSI conditions. Simulation results verify the accuracy of the theoretical analysis and the excellent performance of the proposed system. Due to such superiority, the proposed STBC-MIMO LoRa system can be considered as a good scheme for LPWAN.

In this letter, we conduct an insightful study on protograph-low-density parity-check (PLDPC)-code-assisted deterministic measurement matrices for compressed sensing applications. As is well known, the recovery performance of conventional PLDPC sparse matrices (PLDPC-SM) will be dramatically degraded as the ratio of N to M increases, where M × N is the size of the matrices. To address the above issue, we propose a novel construction method to formulate a class of extended PLDPC-SM (EPLDPCSM) by intelligently inserting part of Hadamard matrices into the conventional PLDPC-SM. The proposed EPLDPC-SM not only can realize more flexible sizes with respect to the existing counterparts, but also can be amenable to lower coherence without costing more storage resources. Both coherence analyses and experiment results demonstrate that the proposed EPLDPC-SM are superior to the well-performing deterministic measurement matrices (i.e., PLDPCSM) and random matrices (i.e., random Gaussian matrices (R-GM) and random sparse matrices (R-SBM)) for various values of N/M1.

In this letter, we propose a new hyperspectral image (HSI) classification approach, called the random subspace ensemble with enhanced feature (RSE-EF), which trains several individual classifiers with enhanced spatial information. The proposed approach aims to address two common issues: the curses of the imbalanced training samples and high feature-to-instance ratio. Specifically, we first propose a similar-neighboring-sample-search (SNSS) method to address the issue of imbalanced training samples. Afterward, we generate the enhanced random subspaces (ERSs) that possess relatively lower dimensionality and more distinctive information compared with the original random subspaces (RSs) so as to alleviate the curse of high feature-to-instance ratio more effectively. Furthermore, a shallow neural network kernel-based extreme learning machine (KELM) is applied to the RSE-EF to classify image pixels. Experimental results on two public hyperspectral data sets illustrate that the proposed RSE-EF approach outperforms the state-of-the-art HSI classification counterparts.

Adaptive link selection for buffer-aided relaying can achieve significant performance gain compared with the conventional relaying with fixed transmission criterion. However, most of the existing link-selection strategies are designed based on perfect channel state information (CSI), which are very complex by requiring channel estimator. To solve this issue, in this paper, we investigate a buffer-aided differential chaos-shift-keying based simultaneous wireless information and power transfer (DCSK-SWIPT) relay system, where a decode-and-forward protocol is considered and the relay is equipped with a data buffer and an energy buffer. In particular, we propose two link-selection protocols for the proposed system based on harvested energy, data-buffer status and energy-shortage status, where the CSI is replaced by the harvested energy to avoid the channel estimation and the practical problem of the decoding cost at the relay is considered. Furthermore, the bit-error-rate (BER) and average-delay closed-form expressions of the proposed protocols are derived over multipath Rayleigh fading channels, which are validated via simulations. Finally, results demonstrate that both the proposed protocols not only provide better BER performance than the conventional DCSK system and DCSK-SWIPT relay system but also achieve better BER performance and lower average delay in comparison to the conventional signal-to-noise-ratio-based buffer-aided DCSK-SWIPT relay systems.

With the continual increase of storage density, NAND flash memory cells are particularly vulnerable to channel noise, which significantly degrades the storage reliability. To overcome this issue, low‐density parity check (LDPC) codes have been considered as a preferable choice for flash memory systems. To further improve the efficiency of the decoder, the convergence speed and the error‐rate performance are the key performance indicators for LDPC‐coded NAND flash memory. In this study, a threshold‐voltage‐drift‐aware scheduling for belief propagation (BP) decoding of LDPC‐coded NAND flash memory is introduced to improve the convergence speed and the error‐rate performance. The basic idea of the proposed scheduling is to find an appropriate updated order of variable nodes according to their corresponding locations of threshold voltages. Since the proposed scheduling updates less reliable variable nodes with higher priority, it can improve the efficiency of BP decoding. Simulation results show that the proposed scheduling not only significantly improves the convergence speed, but also obtains better error‐rate performance than the conventional serial scheduling.

As a bandwidth-efficient technique, bit-interleaved coded modulation with iterative demapping and decoding (BICM-ID) has attracted much research attention in the field of wireless communication. In this paper, we put forth a joint design of root-protograph (RP) low-density parity-check (LDPC) codes and BICM-ID, referred to as RP-based BICM-ID (RP-BICM-ID), over block-fading (BF) channels so as to boost the throughput under limited bandwidth. To preserve the full-diversity property of RP codes, we propose an efficient modulation strategy for the RP-BICM-ID system by taking the fading-block length into consideration. We also analyze the outage-probability limit of the RP-BICM-ID systems to establish the fundamental lower-limit on their word-error-rate (WER) performance. Moreover, we conceive a multi-level protograph extrinsic information transfer (ML-PEXIT) algorithm to derive the asymptotic WER and bit error rate (BER) of the RP-BICM-ID systems over BF channels. As a further insight, we develop a novel unequal-error-protection (UEP) bit-to-symbol (B2S) mapping scheme for the RP-BICM-ID systems, which gives rise to an additional performance improvement. Analyses and simulations show that the proposed RP-BICM-ID systems can not only realize desirable spectral efficiency, but also obtain near-outage-limit performance over BF channels. Therefore, the proposed RP-BICM-ID systems are very promising in achieving high-reliability and high-rate transmissions under slow-fading wireless-communication environments.

Frequency-modulated differential chaos shift keying ultrawideband (FM-DCSK UWB) system has attracted more and more attention in recent years because of its low-complexity and low-power advantages. Nevertheless, its system performance is severely degraded in the presence of narrowband interference (NBI), which further limits its practical applications. In this paper, an enhanced energy-based detector (EED) is proposed for the FM-DCSK UWB system to tackle this problem. Compared with the conventional energy detector (ED), the proposed EED significantly enhances the anti-NBI capability while maintaining the low-power and low-complexity feature. As a further insight, the analytical bit-error-rate (BER) expression of the proposed EED-based FM-DCSK UWB system is derived over additive white Gaussian noise as well as IEEE 802.15.4a multipath fading channels. Moreover, simulation results are carried out to demonstrate the accuracy of the theoretical analysis and the merit of the proposed EED. It is illustrated that the proposed EED achieves better performance than the conventional ED in various transmission scenarios. Thanks to the above-mentioned advantages, the proposed EED-based FM-DCSK UWB system appears to be an excellent candidate for low-power and low-complexity tactile Internet-of-Things applications, e.g., wireless sensor networks and wireless body area networks.

Coded modulation (CM) is a bandwidth efficient framework to approach the capacity limit of the differential chaos shift keying (DCSK) systems. In this paper, we propose an M-ary DCSK system operated with CM based on nonbinary protograph low-density parity-check (LDPC) codes over Rayleigh fading channels. First, we investigate the performance of the proposed nonbinary channel coded DCSK (CM-DCSK) and bit-interleaved coded DCSK (BICM-DCSK). In particular, we show that CM-DCSK outperforms BICM-DCSK over Rayleigh fading channels in terms of capacity limit. Compared with BICM-DCSK, CM-DCSK can simplify the receiver structure, since it does not require turbo iteration between the noncoherent detector and channel decoder. Second, guided by the modified extrinsic information transfer (EXIT) analysis, we put forth two new types of nonbinary protograph LDPC codes to approach the capacity limit of CM-DCSK. Both EXIT analysis and simulation results demonstrate that the proposed protograph-coded CM-DCSK achieves a better error performance than BICM-DCSK even with iterative decoding. Furthermore, we show the performance superiority of nonbinary protograph-coded CM-DCSK over a practical ultra-wideband channel. Hence, we conclude that this proposed scheme offers a good alternative for wireless local area network applications.

This paper investigates the performance of nonbinary low-density parity-check (LDPC) channel coded M-ary differential chaos shift keying (DCSK) modulation systems over Rayleigh fading channels. The receiver adopts non-coherent detector for DCSK modulation and sum-product algorithm (SPA) for channel coding. Unlike that the previous binary channel coded M-ary DCSK system uses turbo iterative decoding between the detector and the channel decoder, the nonbinary coded DCSK system does not require turbo iteration, which simplifies the receiver implementation and reduces the decoding latency, because that soft information from M-ary detector can be directly used by M-ary channel decoder. The simulation result shows that the proposed nonbinary coded M-ary DCSK system has much better error performance than the binary coded one.

Despite of the ultra-wideband (UWB) system's robustness against multipath in cluttered environments, a number of challenges remain before UWB localization can be implemented. In particular, non-line-of-sight (NLOS) propagation is especially critical for high-resolution localization systems because non-negligibly positive biases will be introduced in distance measurements, thus degrading the localization performance. Here, based on received and first path powers obtainable from channel impulse response (CIR), we propose a simple but very efficient method to distinguish between NLOS and LOS conditions. Our method needs neither the training data nor the prior knowledge about the environments, thus enabling realtime NLOS identification. Despite the simplicity of our method, the experimental results verify its speediness and highly correct detection rate.

In this paper, we deal with the problem of maximum likelihood (ML) estimation of the signal-to-noise ratio (SNR) parameter for frequency modulated differential chaos shift key (FM-DCSK) system over multipath Rayleigh fading channels. The ML estimators are derived for various scenarios including data-aided (DA), non-data aided (NDA) and joint DA-NDA estimation by using both the data and pilot symbols. For comparison purposes, the Cramér- Rao lower bounds (CRLBs) for the SNR estimators are derived. The performance of the estimators is evaluated by simulations and comparing with CRLBs in terms of the mean-square-error. Simulated results show that for a large spreading factor the proposed scheme performs well over a wide SNR range in comparisons with CRLBs

A novel spectrum sensing approach based on distribution discontinuity estimation facilitated by change-point (CP) detection algorithm has been presented in this work. Specifically, a Markov Chain Monte Carlo (MCMC) based CP detection algorithm to estimate the variations in the distribution over the received signal is developed. Primary User (PU) activity, autonomous classification of modulation and detection of PU emulation attempts are detected using the CP- Maximum Likelihood Estimation (MLE) framework. Specifically, the CP based approach facilitates PU activity detection and initiates the MLE based mechanism to discern or reveal the underlying modulation scheme within the received signal. Thus, the proposed joint CP-MLE framework not only aims at detecting the discontinuity or the variations in the underlying distribution over the sensed signal, but also helps in attributing those variations to distinct modulation schemes, in an effort to identify PU emulation attempts. This CP- MLE framework has been extensively validated using the Universal Software Radio Peripheral (USRP) devices for various types of scenarios involving real-time modulation classification and identification of PU emulation type attacks.

Capacity bounds are calculated for the differential chaos shift keying (DCSK) system with non‐coherent detectors, including differentially coherent detector and energy detector, over additive white Gaussian noise (AWGN) and Rayleigh fading channels. Through theoretical analysis and numerical simulations, it is found that the capacity characteristics of the non‐coherent DCSK system are significantly different from those of the coherent case. It is shown that there are different capacity bounds corresponding to different spreading factor values. Optimal code rates are found, which minimise the required bit signal‐to‐noise ratio for a reliable communication system, and they are increasing with the increase of the spreading factor value over an AWGN channel while decreasing over a Rayleigh fading channel. As compared with the AWGN channel, the performance over a Rayleigh fading channel is much more sensitive to the code rate. The new results are useful as benchmark for designing capacity‐approaching codes for the non‐coherent DCSK system.

Although the performance of a differential chaos shift keying (DCSK) system can be improved by designing appropriate channel codes, it is still a great challenge to do so for various channel models through transmitter and receiver designs, particularly with short frame length transmissions. Alternatively, to bypass the difficult task of designing a good channel code, an iterative receiver (IR) DCSK system is proposed in this paper. A soft demapper suitable for non-coherent M-ary DCSK system is presented, which can work either with or without fading amplitude information. Bit error rate (BER) performance shows its advantages over the non-IR DCSK system in different channel models. The achievable rate curves also indicate that gains relative to non-iterative DCSK system can be achieved with the iterative receiver.

A new multiresolution M-ary differential chaos shift keying (DCSK) modulation scheme is proposed in this paper. It is a promising technique for providing a different quality of service for transmitted bits within a symbol according to their different bit error rate (BER) requirements based on the principle of nonuniformly spaced constellations. The new system not only is simple but also provides better antimultipath fading performance against various spreading factors, inheriting the advantages of the conventional DCSK system. Furthermore, the proposed scheme and its multicarrier version further increase spectral efficiency and use lower energy consumption at the same bandwidth as compared with the conventional DCSK and its multicarrier system. Explicit BER expressions of the new system are derived and analyzed over additive white Gaussian noise and multipath Rayleigh fading channels. All simulation results verify the prominent advantages of the new scheme and the accuracy of the new analytical approach.