In this paper, we study a movable antenna (MA) empowered secure transmission scheme for reconfigurable intelligent surface (RIS) aided cell-free symbiotic radio (SR) systems. Specifically, the MAs deployed at distributed access points (APs) work collaboratively with the RIS to establish high-quality propagation links for both primary and secondary transmissions, as well as suppressing the risk of eavesdropping on confidential primary information. We consider both continuous and discrete MA position cases and maximize the secrecy rate of primary transmission under the secondary transmission constraints, respectively. For the continuous position case, we propose a two-layer iterative optimization method based on differential evolution with one-in-one representation (DEO), to find a high-quality solution with relatively moderate computational complexity. For the discrete position case, we first extend the DEO based iterative framework by introducing the mapping and determination operations to handle the characteristic of discrete MA positions. To further reduce the computational complexity, we then design a single-layer iterative framework to solve all variables alternatively. In particular, we develop an efficient strategy to derive the sub-optimal solution for the discrete MA positions, superseding the DEO-based method. Numerical results validate the effectiveness of the proposed MA empowered secure transmission scheme along with its optimization algorithms.

Wireless jamming identification, which detects and classifies electromagnetic jamming from non-cooperative devices, is crucial for emerging low-altitude wireless networks consisting of many drone terminals that are highly susceptible to electromagnetic jamming. However, jamming identification schemes adopting deep learning (DL) are vulnerable to attacks involving carefully crafted adversarial samples, resulting in inevitable robustness degradation. To address this issue, we propose a differential transformer framework for wireless jamming identification. Firstly, we introduce a differential transformer network in order to distinguish jamming signals, which overcomes the attention noise when compared with its traditional counterpart by performing self-attention operations in a differential manner. Secondly, we propose a randomized masking training strategy to improve network robustness, which leverages the patch partitioning mechanism inherent to transformer architectures in order to create parallel feature extraction branches. Each branch operates on a distinct, randomly masked subset of patches, which fundamentally constrains the propagation of adversarial perturbations across the network. Additionally, the ensemble effect generated by fusing predictions from these diverse branches demonstrates superior resilience against adversarial attacks. Finally, we introduce a novel consistent training framework that significantly enhances adversarial robustness through dual-branch regularization. Simulation results demonstrate that our proposed methodology is superior to existing methods in boosting robustness to adversarial samples.

Harnessing multi-level electron transitions, Rydberg Atomic REceivers (RAREs) can detect wireless signals across a wide range of frequency bands, from Megahertz to Terahertz. This capability enables multi-band wireless communications and sensing (CommunSense). Existing research on multi-band RAREs primarily focuses on experimental demonstrations, lacking a tractable model to mathematically characterize their mechanisms. This issue leaves the multi-band RARE as a black box and poses challenges in its practical applications. To fill in this gap, this paper investigates the underlying mechanism of multi-band RAREs and explores their optimal performance. For the first time, an analytical transfer function with a closed-form expression for multi-band RAREs is derived by solving the quantum response of Rydberg atoms. It shows that a multi-band RARE simultaneously serves as amulti-band atomic mixerfor down-converting multi-band signals and amulti-band atomic amplifierthat reflects its sensitivity to each band. Further analysis of the atomic amplifier unveils that the intrinsic gain at each frequency band can be decoupled into aglobal gainterm and aRabi attentionterm. The former determines the overall sensitivity of a RARE to all frequency bands of wireless signals. The latter influences the allocation of the overall sensitivity to each frequency band, representing a unique attention mechanism of multi-band RAREs. The optimal design of the global gain is provided to maximize the overall sensitivity of multi-band RAREs. Subsequently, the optimal Rabi attentions are also derived to maximize the practical multi-band CommunSense performance. An experiment platform is built to validate the effectiveness of the derived transfer function, and numerical results confirm the superiority of multi-band RAREs.

Affine frequency division multiplexing (AFDM) exhibits strong robustness against time and frequency dispersion in doubly dispersive channels (DDCs), enabling reliable communication under high mobilities. However, in the multi-user uplink scenario, inter-user channel delay and Doppler differences in the discrete affine Fourier transform (DAFT) domain manifest as inevitable multi-user interference (MUI). To address this issue, building upon the DAFT and AFDM, we propose a novel uplink multiple access scheme termed as DAFT-spread affine frequency division multiple access (DAFT-s-AFDMA). In our proposed scheme, DAFT spreading is performed by each user to multiplex the transmitted symbols over the DAFT domain, which includes a pre-chirp parameter that can be flexibly adjusted to reduce the peak-to-average power ratio (PAPR) of the AFDM system. Accordingly, we derive new guidelines for setting the DAFT parameters and the asymptotically tight upper bounds on the average bit error rate, revealing the insights of PAPR reduction. Furthermore, a low-complexity cross-domain expectation propagation (CD-EP) detector is proposed, capitalizing on the sparsity of DAFT domain effective channel matrix and the corresponding symbol domain constellation constraints to enhance the error performance. Simulation results show that the proposed CD-EP detector outperforms both conventional Gaussian message passing (GMP) and minimum mean square error (MMSE) detectors with a much lower complexity, and also verify the superiority of DAFT-s-AFDMA to plain AFDMA across various scenarios of high-mobility DDCs.

Affine frequency division multiplexing (AFDM) is a promising waveform for next generation wireless networks, effectively resisting the channel double selectivity. Conventional embedded pilot (EP) scheme for AFDM requires additional guard symbols, leading to a reduction in spectral efficiency (SE). To address this issue, superimposed pilot (SP)-based schemes have been proposed, improving the SE; however, at the cost of increased computational complexity at the receiver. In this work, we propose an iterative joint channel estimation and data detection scheme for AFDM by harnessing SPs, aiming to enhance the SE while reducing the detection complexity. Simulation results demonstrate that our proposed scheme outperforms the conventional SP-based scheme in both channel estimation and data detection, while achieving a lower computational complexity. Notably, under low data power conditions, our approach surpasses the EP scheme in terms of both SE and data detection accuracy.

Holographic multiple-input multiple-output (HMIMO) is envisaged as a viable manner for manipulating electromagnetic field produced or perceived by antennas, in an effort to achieve an intelligent and endogenously holography-capable wireless propagation environment. This notion garners significant interest when engaging large antenna elements at high frequencies, such as millimeter-wave or terahertz. Under these conditions, operations often occur within the Fresnel region, i.e., near-field region, where assumptions of planar wavefront no longer apply. This article investigates the codebook solution for HMIMO, unmasking a number of challenges intrinsic in the near-field context and limitations of applying codebooks specified in current standards. Specifically, we proposed a two-phase codebook design empowered by artificial intelligence (AI)-based techniques, where angular and distance ingredients are resolved respectively at each phase, functioning in tandem for facilitating an efficient beam training at reduced pilot overhead. Then from the 3rd generation partnership project (3GPP) standardization perspective, we share potential design rationales influencing standardization, along with a novel signaling procedure for HMIMO beam sweeping.

In high-mobility scenarios, affine frequency division multiplexing with index modulation (AFDM-IM) has attracted significant attention due to its ability to convey information by combining active subcarrier indices with constellation symbols. Motivated by the spatial multiplexing concept in multiple-input multiple-output (MIMO) systems, in this paper, we propose the MIMO-AFDM-IM scheme to enhance spectral efficiency (SE) and bit error rate (BER) performance. Three detection methods are introduced to address the exponential complexity of Maximum Likelihood (ML) detection in MIMO-AFDM-IM. These methods aim to strike a balance between detection accuracy and computational complexity. Additionally, the average bit error probability (ABEP) of the MIMO-AFDM-IM scheme is derived to assess its performance. Computer simulations are carried out under time-varying multipath conditions, and the results demonstrate the superiority of the proposed MIMO-AFDM-IM over MIMOAFDM and AFDM-IM across various system configurations.

As a superior multicarrier technique utilizing chirp signals for high-mobility communications, affine frequency division multiplexing (AFDM) is envisioned to be a promising candidate for sixth-generation (6G) wireless networks. AFDM is based on the discrete affine Fourier transform (DAFT) with two adjustable parameters of the chirp signals, termed the pre-chirp and post-chirp parameters, respectively. Whilst the post-chirp parameter complies with stringent constraints to combat the time-frequency doubly selective channel fading, we show that the pre-chirp counterpart can be flexibly manipulated for an additional degree of freedom. Therefore, this paper proposes a novel AFDM scheme with the pre-chirp index modulation (PIM) philosophy (AFDM-PIM), which can implicitly convey extra information bits through dynamic pre-chirp parameter assignment, thus enhancing both spectral and energy efficiency. Specifically, we first demonstrate that the subcarrier orthogonality is still maintained by applying distinct pre-chirp parameters to various subcarriers in the AFDM modulation process. Inspired by this property, we allow each AFDM subcarrier to carry a unique pre-chirp signal according to the incoming bits. By such an arrangement, extra bits can be embedded into the index patterns of pre-chirp parameter assignment without additional energy consumption. We derive asymptotically tight upper bounds on the average bit error probability (BEP) of the proposed schemes with the maximum-likelihood detection, and validate that the proposed AFDM-PIM can achieve full diversity under doubly dispersive channels. Based on the derived result, we further propose an optimal pre-chirp alphabet design to enhance the bit error rate (BER) performance via intelligent optimization algorithms. Simulation results demonstrate that the proposed AFDM-PIM outperforms the classical benchmarks.

Affine frequency division multiplexing (AFDM) and orthogonal AFDM access (O-AFDMA) are promising techniques based on chirp signals, which are able to suppress the performance deterioration caused by Doppler shifts in high-mobility scenarios. However, the high peak-to-average power ratio (PAPR) in AFDM or O-AFDMA is still a crucial problem, which severely limits their practical applications. In this paper, we propose a discrete affine Fourier transform (DAFT)-spread AFDMA scheme based on the properties of the AFDM systems, named DAFT-s-AFDMA to significantly reduce the PAPR by resorting to the DAFT. We formulate the transmitted time-domain signals of the proposed DAFT-s-AFDMA schemes with localized and interleaved chirp subcarrier allocation strategies. Accordingly, we derive the guidelines for setting the DAFT parameters, revealing the insights of PAPR reduction. Finally, simulation results of PAPR comparison in terms of the complementary cumulative distribution function (CCDF) show that the proposed DAFT-s-AFDMA schemes with localized and interleaved strategies can both attain better PAPR performances than the conventional O-AFDMA scheme.

Action recognition algorithms have gained significant attention in recent years, which can be indispensable for a plethora of cutting-edge applications like extended reality or Metaverse. These services often pose stringent requirement on immediate sensing and cognition of the surroundings, which necessitates immediate classifications of the captured actions (e.g., video data) that classical signal processing methods can hardly attain. In this paper, we introduced a residual artificial neural network with two-stream structure to further improve the accuracy of action recognition algorithm. Specifically, two residual networks (ResNet101) are trained separately, one by spatial RGB image streams, and another by optical flow streams. The two-strem network outputs are then fed into a fusion classifier, in which information extracted by spatial network and temporal network jointly determines the classification result. Moreover, in the training process, hyper-parameters setting and optimizer selection are performed numerically to achieve optimal performance. Finally, the recognition accuracy of the proposed algorithm has been compared to other existing widely-employed counterparts, where UCF101 data set is utilized for training and testing. Simulations validates aiming that the network can achieve higher recognition accuracy than traditional algorithms, and the two-stream method shows its superiority over the single-network counterpart.

Affine frequency division multiplexing (AFDM), tailored as a novel multicarrier technique utilizing chirp signals for high-mobility communications, exhibits marked advantages compared to traditional orthogonal frequency division multiplexing (OFDM). AFDM is based on the discrete affine Fourier transform (DAFT) with two modifiable parameters of the chirp signals, termed as the pre-chirp parameter and post-chirp parameter, respectively. These parameters can be fine-tuned to avoid overlapping channel paths with different delays or Doppler shifts, leading to performance enhancement especially for doubly dispersive channel. In this paper, we propose a novel AFDM structure with the pre-chirp index modulation (PIM) philosophy (AFDM-PIM), which can embed additional information bits into the prechirp parameter design for both spectral and energy efficiency enhancement. Specifically, we first demonstrate that the application of distinct pre-chirp parameters to various subcarriers in the AFDM modulation process maintains the orthogonality among these subcarriers. Then, different prechirp parameters are flexibly assigned to each AFDM subcarrier according to the incoming bits. By such arrangement, aside from classical phase/amplitude modulation, extra binary bits can be implicitly conveyed by the indices of selected prechirping parameters realizations without additional energy consumption. At the receiver, both a maximum likelihood (ML) detector and a reduced-complexity ML-minimum mean square error (ML-MMSE) detector are employed to recover the information bits. It has been shown via simulations that the proposed AFDM-PIM exhibits superior bit error rate (BER) performance compared to classical AFDM, OFDM and IM aided OFDM algorithms.

Integrated sensing and communication (ISAC) is recognized as one of key enabling technologies for the Meta-verse. To enhance both communication data rate and sensing accuracy, the exploitation of millimeter wave (mmWave) and terahertz (THz) frequencies becomes mandatory due to huge amount of spectrum resources. To combat the severe path-loss at mmWave/THz band, large-scale antenna arrays are usually employed to form directional beams. However, the ultra-broad bandwidth induces undesirable beam squint (BS) effects, where the beams from different subcarriers point to diverse angles, leading to the communication performance loss. Fortunately, this BS effect can be leveraged to facilitate the multi-angle super-resolution sensing with minimal beam sweeping overhead. Against this background, we propose a novel multicarrier waveform design methodology for the BS-assisted ISAC systems, which optimizes the frequency resource allocation between sensing and communications to reach a good dual-functional performance trade-off. To mitigate mutual interference, both functions are assigned non-overlapping subcarriers. The subcarrier assignment design is formulated as a mixed integer programming problem to maximize the communication throughput while ensuring the required sensing range and resolution, which involves high complexity to get an exact solution. To this end, we propose a two-stage iterative update algorithm to obtain a quasi-optimal solution with low computational complexity. Numerical results demonstrate that our proposed methodology achieves high-rate communication and high-resolution sensing simultaneously with relatively low overhead.

The Extremely-large Aperture Reconfigurable In-telligent Surface (RIS) stands out as a promising technology for future 6G communications. However, existing far-field or near-field channel models struggle to adapt effectively to channel estimation in the context of Extremely-large Aperture RIS-assisted wireless communication under a hybrid field. To address this challenge, this paper introduces an efficient hybrid-field channel estimation scheme tailored for Extremely-large Aperture RIS-assisted wireless communication. In this scheme, we initially extend the one-dimensional polar coordinate dictionary to a full-dimensional spherical coordinate dictionary to achieve a more uniform distribution of grid points in the spherical coordinate-domain. Subsequently, we propose a hybrid passive/active RIS architecture, utilizing a limited number of Radio Frequency (RF) chains to acquire channel observations. Finally, we introduce a hybrid-field channel estimation scheme designed to estimate both far-field and near-field components. Simulation results demonstrate that the proposed scheme outperforms purely far-field or near-field schemes.

Integrated sensing and communication (ISAC) is expected to be a promising technology in the sixth-generation (6G) wireless networks for its ability to alleviate resources shortage and excessive hardware expenses. One typical representative for ISAC waveforms is the orthogonal frequency division multiplexing (OFDM) waveform, which divides the time-frequency resources into orthogonal resource elements (REs). In order to satisfy their diverse design requirements and mitigate mutual interference, the communication and sensing subsystems can be assigned with different REs, which necessitates effective allocation strategies of different resources across time and frequency domains. In this article, a cross-domain multicarrier waveform design method-ology is proposed, which optimizes the RE assignment and power allocation strategies for the OFDM-based ISAC system. Specifically, for sensing performance enhancement, the unit cells of the ambiguity function (AF) of the sensing components are spe-cially shaped to achieve a “locally” perfect auto-correlation (AC) property within a predefined region of interest (RoI) in the Delay-Doppler domain. Afterwards, the irrelevant cells outside the RoI, which can determine the sensing power allocation strategy, are optimized alternatively with the communication power allocation strategy to maximize the throughput for the communication purpose. Numerical results demonstrate the superiority of the cross-domain multicarrier waveform design, which also provides useful guidelines for parameter settings of the proposed OFDM-based ISAC system.

Orthogonal frequency division multiplexing (OFDM) has been widely recognized as the representative waveform for 5G wireless networks, which can directly support sensing/positioning with existing infrastructure. To guarantee superior sensing/positioning accuracy while supporting high-speed communication simultaneously, the dual functions tend to be assigned with different resource elements (REs) due to their diverse design requirements. This motivates optimization of resource allocation/waveform design across time, frequency, power and delay-Doppler domains. Therefore, this article proposes two cross-domain waveform optimization strategies for effective convergence of OFDM-based communication and sensing/positioning, following communication- and sensing-centric criteria, respectively. For the communication-centric design, to maximize the achievable data rate, a fraction of REs are optimally allocated for communication according to prior knowledge of the communication channel. The remaining REs are then employed for sensing/positioning, where the sidelobe level and peak-to-average power ratio are suppressed by optimizing its power-frequency and phase-frequency characteristics for sensing performance improvement. For the sensing-centric design, a ‘locally’ perfect auto-correlation property is ensured for accurate sensing and positioning by adjusting the unit cells of the ambiguity function within its region of interest (RoI). Afterwards, the irrelevant cells beyond RoI, which can readily determine the sensing power allocation, are optimized with the communication power allocation to enhance the achievable data rate. Numerical results demonstrate the superiority of the proposed waveform designs.

With the emergence of communication services with stringent requirements such as autonomous driving or on-flight Internet, the sixth-generation (6G) wireless network is envisaged to become an enabling technology for future transportation systems. In this paper, two ways of interactions between 6G networks and transportation are extensively investigated. On one hand, the new usage scenarios and capabilities of 6G over existing cellular networks are firstly highlighted. Then, its potential in seamless and ubiquitous connectivity across the heterogeneous space-air-ground transportation systems is demonstrated, where railways, airplanes, high-altitude platforms and satellites are investigated. On the other hand, we reveal that the introduction of 6G guarantees a more intelligent, efficient and secure transportation system. Specifically, technical analysis on how 6G can empower future transportation is provided, based on the latest research and standardization progresses in localization, integrated sensing and communications, and security. The technical challenges and insights for a road ahead are also summarized for possible inspirations on 6G enabled advanced transportation.

Reconfigurable intelligent surface (RIS) has drawn extensive attentions as a promising alternative for classical phased-array antennas at the massive multiple-input multiple-output (MIMO) transmitter, leading to cost-effective data transmission that is especially desirable at terahertz (THz) frequencies. In this article, we consider a multi-user MIMO (MU-MIMO) system equipped with a RIS-assisted transmitter: A RIS array is illuminated by unmodulated THz carriers through a feeding antenna, which is equally divided into a number of subarrays (SAs). Each activated SA serves one unique user equipment (UE) via directional beams. Then we develop a spectrum- and energy- efficient MU-MIMO scheme for THz communications by performing index modulation (IM) on the array-of-SA structure of the RIS, abbreviated as RIS-SA-IM. Specifically, the indices of the RIS-SAs allocated to different UEs, defined as SA allocation pattern (SAPs), are flexibly controlled by the information bits at each symbol period. Hence, aside from classical amplitude/phase modulation, additional energy-free bits (referred to asindex bits) can be conveyed implicitly by the chosen SAP at the transmitter, thus attaining superior enhancement on spectrum- and energy-efficiencies. Furthermore, we design a distributed mapping rule between the SAPs and index bits, which guarantees that the index information for each UE is exclusively determined by the index of its allocated RIS-SA. Hence, the proposed mapping rule can enable localized demodulation of the index bits without inter-UE data exchange. In particular, a general form of the distributed mapping rule is provided based on the binary-tree structure, which can be extended to arbitrary number of UEs and index bits. Additionally, the error performance of the proposed RIS-SA-IM is evaluated through pairwise error probability (PEP) calculations. Theoretical and simulation results demonstrate the superiority of our proposed RIS-SA-IM over its classical non-IM-aided counterpart.

A reactive jamming attack, which performs spec-trum jamming only during legal signal transmission based on the knowledge of sensor behaviors, poses a significant threat to wireless sensing networks (WSNs). In this paper, a novel deceiving approach is proposed for defending reactive jamming in dynamic WSNs. Specifically, when the maximum transmission power is given, we first formulate the anti-jamming process as an optimization problem to maximize the average received power while eliminating the effects of the jamming attack. Then the interaction between reactive jamming and legitimate sensors is modeled with the Markov decision process (MDP). Finally, a deep Q network (DQN) based jamming deceiving method is proposed to solve the formulated optimization problem. Simulation results show that the proposed anti-jamming scheme can converge quickly and is superior to the classical counterparts in terms of the mean of received signal power.

The programmable metasurface (MTS), which can enhance the signal quality by flexibly manipulating the electromagnetic (EM) responses of reflected waves, has emerged as a promising technology for multiple-input multiple-output (MIMO) transmission due to its superior energy efficiency and cost-effective hardware implementations. In this paper, we consider a multi-user MIMO (MU-MIMO) system equipped with a MTS-based multi-feed transmitter, where an array of metallic elements is split into several subarrays (SAs), each irradiated by a unique radio-frequency (RF) feed. Additionally, each user is allocated with one unique RF-feed-SA pair for data services. Then we develop a novel index modulation (IM) scheme based on this array-of-SA (AoSA) structure of the MTS, named as MTS-SA -IM. More specifically, the allocation strategy of the SAs to different users, termed as SA allocation pattern (SAP), is flexibly controlled by the information bits. In other words, aside from classical amplitude/phase modulation bits, additional binary bits, referred to as index bits, can be embedded into the indices of the allocated SAs without extra power consumption, leading to enhancement of both spectrum and energy efficiencies. Furthermore, we propose a distributed mapping rule design between the index bits and SAPs, which guarantees that the index bits at each user are exclusively dependent on the index of its own allocated SA. By constructing a binary-tree structure, a general form of the proposed distributed mapping rule is generated recursively, which can be extended to the cases of arbitrary number of users. Simulation results demonstrate that the proposed MTS is capable of achieving desirable performance gain over its classical counterpart.

Unmanned aerial vehicle (UAV) equipped with large-scale antenna array constitutes a promising relaying candidate for reliable and secure satellite-terrestrial communication. Due to the limitation of energy consumption, a novel UAV architecture with one-bit analog-to-digital converters (ADCs) and one-bit digital-to-analog converters (DACs) is proposed firstly. Leveraging the additive quantization noise model, the exact closed-form expressions of both ergodic capacity and ergodic achievable secrecy rate are derived for UAV-assisted satellite-terrestrial communication systems using large-scale antenna array with one-bit ADCs/DACs. To enhance the transmission capacity and combat the eavesdropper simultaneously, maximum-ratio combining (MRC) is used by UAV to receive signals from satellite and location-based beamforming (LBB) is adopted by UAV to forward signals to destination, where the beamformer is optimized based on the derived expression of the ergodic achievable secrecy rate. Simulation results validate the accuracy of our analytical ergodic achievable secrecy rate, and demonstrate that our proposed MRC/LBB scheme has better secrecy rate than its conventional location-based counterpart.

The convergence of radar sensing and communication applications in the millimeter-wave (mmWave) and low terahertz (THz) bands has been envisioned as a promising technology, since it incorporates high-rate data transmission of hundreds of gigabits per second (Gbps) and mm-level radar sensing in a spectrum- and cost-efficient manner, by sharing both the frequency and hardware resources. However, the joint radar sensing and communication (JRC) system faces considerable challenges in the mmWave and low-THz scale, due to the peculiarities of the propagation channel and radio-frequency (RF) front ends. To this end, the waveform design for the JRC systems in mmWave and low-THz bands with ultra-broad bandwidth is investigated in this paper. Firstly, by considering the JRC design based on the co- existence concept, where both functions operate in a time-domain duplex (TDD) manner, a novel multi-subband quasi-perfect (MS-QP) sequence, composed of multiple perfect subsequences on different subbands, is proposed for target sensing, which achieves accurate target ranging and velocity estimation, whilst only requiring cost-efficient low-rate analog-to-digital converters (A/Ds) for sequence detection. Furthermore, the root index of each perfect subsequence is designed to eliminate the influence of strong Doppler shift on radar sensing. Finally, a data-embedded MS-QP (DE-MS-QP) waveform is constructed through time-domain extension of the MS-QP sequence, generating null frequency points on each subband for data transmission. Unlike the co- existence-based JRC system in TDD manner, the proposed DE-MS-QP waveform enables simultaneous interference-free sensing and communication, whilst inheriting all the merits from MS-QP sequences. Numerical results validate the superiority of the proposed waveforms regarding the communication and sensing performances, hardware cost as well as flexibility of the resource allocation between the dual functions.

Terahertz (THz) wireless communication is envisioned as a promising technology, which is capable of providing ultra-high-rate transmission up to Terabit per second. However, some hardware imperfections, which are generally neglected in the existing literature concerning lower data rates and traditional operating frequencies, cannot be overlooked in the THz systems. Hardware imperfections usually consist of phase noise, in-phase/quadrature imbalance, and nonlinearity of power amplifier. Due to the time-variant characteristic of phase noise, frequent pilot insertion is required, leading to decreased spectral efficiency. In this paper, to address this issue, a novel pilot design strategy is proposed based on index modulation (IM), where the positions of pilots are flexibly changed in the data frame, and additional information bits can be conveyed by indices of pilots. Furthermore, a turbo receiving algorithm is developed, which jointly performs the detection of pilot indices and channel estimation in an iterative manner. It is shown that the proposed turbo receiver works well even under the situation where the prior knowledge of channel state information is outdated. Analytical and simulation results validate that the proposed schemes achieve significant enhancement of bit-error rate performance and channel estimation accuracy, whilst attaining higher spectral efficiency in comparison with its classical counterpart.

TeraHertz (THz) communication has drawn increasing interest from both academic and industrial fields due to its capability of attaining data transmission over 100 Gb/s. To generate THz-band carriers, one promising low-cost electronic approach is the frequency-multiplier-last architecture, which however induces undesirable nonlinearity. Another substantial issue in THz communication systems is the residual hardware impairment in the mixer and power amplifier (PA), which are usually neglected under low-rate scenarios, but considered to be pronounced in the ultra-high-speed THz wireless links. With the existence of all these radio-frequency (RF) imperfections at the transmitter, conventional receiver design for lower-frequency bands is no longer applicable. In this paper, a single-carrier THz communication system utilizing the frequency-multiplier-last architecture is investigated. By jointly considering the overall RF imperfections of the mixer, the PA, and the frequency multiplier at the transmitter, a sophisticated mathematical model of the induced distortions on transmitted THz signals is provided. Based on the model, a low-complexity closed-form minimum mean Euclidean distance (MMED) channel estimator is firstly derived. Afterwards, the aggregate distortions plus thermal noise on the THz signals are approximated as a signal-dependent and spatially-colored noise term, where a closed-form quasi-maximum-likelihood (quasi-ML) detector is developed for the THz communication system. Simulation results demonstrate that our proposed receiver design is capable of significantly enhancing the performance of the THz system compared with its conventional counterparts, in terms of channel estimation accuracy and bit-error rate (BER).

Vehicular ad hoc network (VANET) is a promising technology for intelligent transportation systems, where dedicated short range communication (DSRC) is usually used for inter-vehicle communications. When the vehicle density is high, the randomly access feature of the carrier sense multiple access with collision avoidance (CSMA/CA) mechanism in DSRC will lead to the increased channel contention delay. Therefore, visible light communication (VLC) can be introduced to form a heterogeneous VLC-DSRC network for delay reduction. Although VLC has no contention delay, one VLC link can only be established between two adjacent vehicles, which might increase the delay caused by multi-hop communications. In this paper, a delay-minimization link selection scheme is proposed to select appropriate links for vehicles according to actual situations and minimize average delay. Simulation results demonstrate that the proposed scheme outperforms the considered benchmarks in terms of average transmission delay.

Three-dimensional visible light positioning (3D-VLP) is capable of achieving superior locating accuracy in comparison with other existing positioning techniques, such as global positioning system (GPS) and Wi-Fi-based method, which draws much attention from the researchers. In this paper, a novel 3D-VLP scheme using regression neural network is proposed to provide accurate and real-time positioning service. In the proposed method, the angle of arrival (AOA) vectors corresponding to the light-emitting diodes (LEDs) are obtained by the image sensor of the receiver and then fed into a regression neural network, which directly outputs the positioning results. Simulations are carried out to validate the superiority of the proposed method. It’s observed that, in spite of the inevitable quantization error in the positioning process, the mean positioning error is still as accurate as 1.1 cm. In addition, the proposed positioning method is more robust to camera’s height, and takes only 0.27ms to calculate the position, which could be used for real-time locating.

In indoor environment, a hybrid network consisting of light fidelity (LiFi) and wireless fidelity (WiFi) is capable of retaining both the high-speed data transmission and the ubiquitous coverage, where the network access type of users can be optimized to improve the performance. Since visible light communication mainly depends on the line-of-sight (LoS) transmission, it is susceptible to channel blockage, which should be considered by users to select the appropriate type of network access. In the existing literature, LiFi channel blockage parameters are regarded as known for users to determine the access type. However, in practical scenarios, the estimation of blockage parameters lags behind their variations, and users can not get the real-time blockage information. In this paper, a support-vector-machine- based (SVM-based) network access type decision scheme is proposed in hybrid LiFi and WiFi networks. By taking the correlation of blockage parameters between adjacent periods into account, SVM is adopted to achieve high equivalent data rate when accurate blockage parameters are unknown. Simulation results demonstrate that the proposed scheme outperforms the considered benchmarks under different scenarios in terms of the equivalent data rate performance.

Media-based modulation (MBM) has become a promising technology for wireless communications, which offers significant throughput enhancement and superior performance due to the channel diversity gain achieved by RF mirrors. In this paper, the physical-layer security (PLS) issue is investigated for the single-input-multiple-output MBM (SIMO-MBM) system, and a secure SIMO-MBM system is proposed. Especially, by considering time-division duplexing (TDD) mode, based on its channel reciprocity property, both the data symbol bits and the index bits are protected from the eavesdropper by using the amplitude and phase information of the legitimate channel states as the secret key. For performance evaluation, the bit error rate (BER) of the eavesdropper as well as the system secrecy mutual information are investigated, and Monte Carlo simulations are carried out. Simulation results demonstrate that, the proposed secure SIMO-MBM system is capable of efficiently preventing data leakage whilst ensuring reliable data transmission.

A 3D positioning method based on visible light communication is proposed. Compared to the previous methods, we only need three light emitting diodes (LEDs) with known coordinates to obtain the object position without the priori knowledge of the receiver's height and tile angle. The gradient descent method and vector method are used to obtain the coordinate and inclination of the object (i.e., camera). To validate the effectiveness of our methods, the relation of mean positioning error caused by the discrete camera sensor pixel and the system parameters (i.e., focal length of the camera, pixel density and height of the receiver) is analyzed. Simulation results show the quantization error is about 5 cm.

Orthogonal frequency division multiplexing (OFDM) with index modulation has emerged as a promising complementary technique for next-generation networks due to its high energy efficiency. In this paper, zero-padded tri-mode index modulation aided OFDM (ZTM-OFDM) is proposed, where subcarriers are partitioned into subblocks. Explicitly, only a fraction of subcarriers are utilized for modulation with two distinguishable constellation alphabets in each OFDM subblock, whilst the others remain empty. By such strategy, additional bits can be conveyed by the subcarrier indices corresponding to the two constellation sets (denoted as index pattern). At the receiver, a maximum-likelihood (ML) detector and a two-stage log-likelihood ratio (LLR) detector with reduced complexity are proposed for demodulation. The proposed ZTM-OFDM is capable of enhancing the spectral and energy efficiency compared with other index modulated OFDM schemes. Theoretical analysis based on the minimum Euclidean distance and Monte Carlo simulation results validate that the proposed ZTM-OFDM can attain performance gain over conventional OFDM and other index modulated OFDM schemes.

Visible light communication (VLC) has become a promising complement to its radio-frequency (RF) counterpart. In VLC systems, orthogonal frequency division multiplexing (OFDM) has drawn much attention due to its high data rate, simple equalization and robustness to the inter-symbol interference (ISI). In this paper, we present a comparative performance evaluation of several classical optical OFDM schemes, including DC-biased optical OFDM (DCO-OFDM), asymmetrically clipped optical OFDM (ACO-OFDM), pulse-amplitude-modulated discrete multitone (PAM-DMT), unipolar OFDM (U-OFDM) and Flip OFDM. Since DCO-OFDM suffers from energy efficiency loss due to addition of DC-bias, whilst ACO-OFDM, PAM-DMT and U-OFDM/Flip OFDM are spectrally inefficient due to their unique frame structures, the state-of-the-art energy- and spectrum- efficient optical OFDM schemes are investigated, including asymmetrically clipped DC-biased optical OFDM (ADO-OFDM), hybrid ACO-OFDM (HACO-OFDM), asymmetrically clipped absolute value optical OFDM (AAO-OFDM), the spectral and energy efficient OFDM (SEE-OFDM), layered ACO-OFDM (LACO-OFDM), enhanced U-OFDM (eU-OFDM), optical OFDM with index modulation (O-OFDM-IM) and optical dual-mode index modulation aided OFDM (DM-OFDM). In this paper, their principles are firstly illustrated, then performance comparisons are conducted for those optical OFDM schemes in terms of spectral efficiency, energy efficiency and computational complexity. Since light emitting diodes (LEDs) need to support both the illumination and communication simultaneously, dimming control should be considered in VLC systems. Therefore, dimmable optical OFDM for practical VLC systems incorporating illumination is also addressed.