Multicarrier Communication Research Articles

Active-RIS Enhances the Multi-User Rate of Multi-Carrier Communications

Active-RIS Enhances the Multi-User Rate of Multi-Carrier Communications

Integrated Sensing and Communication With Delay Alignment Modulation: Performance Analysis and Beamforming Optimization

Delay alignment modulation (DAM) has been recently proposed to enable manipulable channel delay spread for efficient single- or multi-carrier communications. In particular, with perfect delay alignment, inter-symbol interference (ISI) can be eliminated even with single-carrier (SC) transmission, without relying on sophisticated channel equalization. The key ideas of DAM are <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">delay pre-compensation</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">path-based beamforming</i> , so that all multi-path signal components may arrive at the receiver simultaneously and be superimposed constructively, rather than causing the detrimental ISI. Compared to the classic orthogonal frequency division multiplexing (OFDM) transmission, DAM-enabled SC communication has several appealing advantages, including low peak-to-average-power ratio (PAPR) and high tolerance for Doppler frequency shift, which renders DAM also appealing for radar sensing. Therefore, in this paper, DAM is investigated for integrated sensing and communication (ISAC) systems. We first study the output signal-to-noise ratios (SNRs) for ISI-free SC communication and radar sensing, respectively, and then derive the closed-form expressions for DAM-based sensing in terms of the ambiguity function (AF) and integrated sidelobe ratio (ISR). Furthermore, we study the beamforming design problem for DAM-based ISAC to maximize the communication SNR while guaranteeing the sensing performance in terms of the sensing SNR and ISR. Finally, we provide performance comparison between DAM and OFDM for ISAC, and it is revealed that DAM signal may achieve better communication and sensing performance, thanks to its low PAPR, reduced guard interval overhead, as well as higher tolerance for Doppler frequency shift. Simulation results are provided to show the great potential of DAM for ISAC.

Delay Alignment Modulation: Manipulating Channel Delay Spread for Efficient Single- and Multi-Carrier Communication

Delay Alignment Modulation: Manipulating Channel Delay Spread for Efficient Single- and Multi-Carrier Communication

Multicarrier Communication for UHF RFID: Increased Reliability and Coverage for UHF RFID Systems

Multicarrier Communication for UHF RFID: Increased Reliability and Coverage for UHF RFID Systems

Resource Allocation for Multicarrier Communication in the Finite Blocklength Regime

Resource Allocation for Multicarrier Communication in the Finite Blocklength Regime

An Efficient Cross-Layer Authentication Scheme for Secure Communication in Vehicular Ad-Hoc Networks

Intelligent transportation systems contribute to improved traffic safety by facilitating real-time communication between vehicles and infrastructures. In this context, message authentication is crucial to safeguard vehicular ad-hoc networks (VANETs) from malicious attacks. The current state-of-the-art for authentication in VANETs relies on conventional cryptographic primitives, introducing significant computation and communication overheads. This paper presents a cross-layer authentication scheme for vehicular communication, incorporating the short-term reciprocal features of the wireless channel for re-authenticating the corresponding terminal, reducing the overall complexity and computation and communication overheads. The proposed scheme comprises four steps: S1. Upper-layer authentication is used to determine the legitimacy of the corresponding terminal at the first time slot; S2. Upon the verification result, a location-dependent shared key with a minimum number of mismatched bits is extracted between both terminals; S3. Using the extracted key and under binary hypothesis testing, a PHY challenge-response algorithm for multicarrier communication is proposed for re-authentication; S4. In the case of false detection, the key extraction step (S2) is re-executed after adapting the quantisation levels at different conditions of channel non-reciprocity based on the feedback from the re-authentication step (S3). Simulation results show the effectiveness of the proposed scheme even at small signal-to-noise ratios. In addition, the immunity of the proposed scheme is proved against active and passive attacks, including signatures' unforgeability against adaptive chosen message attacks in the random oracle model. Finally, a comprehensive comparison in terms of computation and communication overheads demonstrates the superiority of the proposed scheme over its best rivals.

Adaptive switching for communication profiles in underwater acoustic modems based on reinforcement learning

The underwater acoustic (UWA) channel is a complex and stochastic process with large spatial and temporal dynamics. This work studies the adaptation of the communication strategy to channel dynamics. Specifically, a set of communication strategies are considered, including Frequency-Hopped Binary Frequency Shift Keying (FH-BFSK), Single-Carrier (SC) communication, and multicarrier communication. Based on the channel condition, a reinforcement learning (RL) algorithm, the Deep Deterministic Policy Gradient (DDPG) method along with a Gumbel-softmax scheme is employed for intelligent and adaptive switching among those communication strategies. The adaptive switching is performed on a transmission block-by-block basis, with the goal of maximizing long-term system performance. The reward function is defined based on the energy efficiency (EE) and the spectral efficiency (SE) of the communication strategies. Simulation results and experimental data processing results reveal that the proposed method outperforms a random selection method and a direct feedback method in time-varying channels.

Multicarrier Acoustic Communications in Multiuser and Interference-Limited Regimes

In this article, we address the design of a multicarrier communication system based on orthogonal frequency-division multiplexing and direct sequence spread spectrum. The design targets operation in the low-signal-to-noise-ratio regimes and multiuser settings. Specifically, coding is employed across carriers such that channel estimation and signal detection are coupled. We consider both coherent and differentially coherent detection and extend the principles to multichannel reception. A custom-designed frequency synchronization technique is proposed to counteract the motion-induced Doppler frequency shifting effect. Using the recordings from the 2010 Mobile Acoustic Communication Experiment, where signals were transmitted in the 10.5–15.5-kHz acoustic band in shallow water, with relative motion up to 1.5 m/s, we demonstrate the system performance in terms of the mean squared error and bit error rate in data detection. Further employing Polar and low-density parity-check coding, we show that the proposed methods provide excellent performance while maintaining low computational complexity, making them suitable for a practical implementation.

End-to-End Underwater Acoustic Communication Based on Autoencoder with Dense Convolution

To address the problems of the high complexity and poor bit error rate (BER) performance of traditional communication systems in underwater acoustic environments, this paper incorporates the theory of deep learning into a conventional communication system and proposes data-driven underwater acoustic filter bank multicarrier (FBMC) communications based on convolutional autoencoder networks. The proposed system is globally optimized by two one-dimensional convolutional (Conv1D) modules at the transmitter and receiver, it realizes signal reconstruction through end-to-end training, it effectively avoids the inherent imaginary interference of the system, and it improves the reliability of the communication system. Furthermore, dense-block modules are constructed between Conv1D layers and are connected across layers to achieve feature reuse in the network. Simulation results show that the BER performance of the proposed method outperforms that of the conventional FBMC system with channel equalization algorithms such as least squares (LS) estimation and virtual time reversal mirrors (VTRM) under the measured channel conditions at a certain moment in the Qingjiang River.

BER Reduction and Capacity Enhancement with Novel Guard Sequence Selection for Multi-Carrier Communication

Orthogonal frequency division multiplexing (OFDM) is an efficient multicarrier scheme that uses different types of guard intervals such as cyclic prefix (CP) and known symbol padding (KSP) (zero padding (ZP), unique word (UW), etc.) in block formation. Among these guard intervals, CP varies for each block, while other guard intervals remain fixed from block to block. These guard intervals efficiently perform channel estimation, synchronization and remove inter-block interference (IBI); nevertheless, none of the existing schemes develop any relationship between the guard interval (sequence) and the data symbols on different subcarriers of the OFDM block. We present a new idea of selecting the guard interval based on the data symbols of a subset of subcarriers in the block and exploit the high auto-correlation of the selected guard sequence to improve the bit error rate (BER) performance of the system. The results based on a fair comparison show that our enhanced orthogonal frequency division multiplexing (eOFDM) scheme inherits significant improvements in BER and the capacity of a multicarrier system as compared to the existing techniques.

Adaptive chaotic map-based key extraction for efficient cross-layer authentication in VANETs

Vehicle-to-everything (V2X) communication is expected to offer users available and ultra-reliable transmission, particularly for critical applications related to safety and autonomy. In this context, establishing a secure and resilient authentication process with low latency and high functionality may not be achieved using conventional cryptographic methodologies due to their significant computation costs. Recent research has focused on employing the physical (PHY) characteristics of wireless channels to develop efficient discrimination techniques to overcome the shortcomings of crypto-based authentication. This paper presents a cross-layer authentication scheme for multicarrier communication, leveraging the spatially/temporally correlated wireless channel features to facilitate key verification without exposing its secrecy. By mapping the time-stamped hashed key and masking it with channel phase responses, we create a PHY-layer signature, allowing for verifying the sender's identity while employing the correlated channel responses between subcarriers to verify messages' integrity. Furthermore, we developed a Diffie-Hellman secret key extraction algorithm that employs the computationally intractable problems of the Chebyshev chaotic mapping for channel probing. Thus, terminals can extract high entropy shared keys that can be used to create dynamic PHY-layer signatures, supporting forward and backward secrecy. We evaluated the scheme's security strength against active/passive attacks. Besides theoretical analysis, we designed a 3-Dimensional (3D) scattering Doppler emulator to investigate the scheme's performance at different speeds of a moving vehicle and signal-to-noise ratios (SNRs) for a realistic vehicular channel. Theoretical and hardware implementation analyses proved the capability of the proposed scheme to support high detection probability at SNR ≥ 0 dB and speed ≤ 45 m/s.

Underwater Acoustic Channel Tracking with Cluster Variation Learning for Acoustic Mobile OFDM Communication

In this paper, we propose a channel tracking method with cluster variation learning in multicarrier communications, by exploiting the cluster-specific channel coherence for time-varying underwater acoustic (UWA) channels. We develop a cluster variation model due to the cluster-specific channel coherence. In the cluster variation model, the path delay and the Doppler scale assemble the range and the velocity in the target movement. Inspired by the target tracking for its movement, we propose a channel tracking method which can incorporate the cluster variation model with the measurement model efficiently through Kalman filtering. The cluster variation model can learn its parameters block by block through pilots, therefore reduce its model mismatch adaptively. The proposed method has a moderate computational complexity, since it eliminates the explicit Doppler scale estimation and Doppler variation model comparing to the conventional channel estimation. Using simulated data as well as experimental data in mobile UWA communications with one phone element, we study the system performance in term of mean square error (MSE) and symbol error rate (SER) performance, and show that the proposed channel tracking method improves the performance significantly.

Analysis of Multi Carrier Modulation techniques for 5G Physical Layer Communications

The more enchanting Multicarrier Communication (MCM) techniques like Fifth Generation (5G), Long Term Evolution (LTE) and Fourth Generation (4G) are the enhancing techniques that contribute the progress of wireless communication systems. The most effective way to save resources in 5G is to make efficient use of all existing discontinuous spectrums, which maximizes Spectrum Efficiency (SE). A valid comparison of many 5G MCM techniques is made in this work, namely Universal Filter Multi Carrier (UFMC), Filter Bank Multi Carrier (FBMC) and Orthogonal Frequency Division Modulation (OFDM). Various Key Performance Indicators (KPI) such as Bit Error Ratio (BER), Signal to Interference Ratio (SIR), Power Spectral Density (PSD) and ratio between Peak Power and Average Power, Throughput, and Spectral Efficiency (SE) are evaluated and compared under various realistic channels. UFMC Modulation technique is compatible with existing channel estimation and detection techniques and further improves SE. The SE of FBMC has been improved by 2% with Hermite filter when compared to PHYSDAS, RRC prototype filters. It has been observed that FBMC offered better SIR, Throughput, also a complex design of filter reduced BER and PAPR.

Resource Allocation in STAR-RIS-Aided Networks: OMA and NOMA

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is a promising technology that aids in achieving full-space coverage on both sides of the surface, by splitting the incident signal into transmitted and reflected signals. This paper investigates the resource allocation problem in a STAR-RIS-assisted multi-carrier communication networks. To maximize the system sum-rate, a joint optimization problem comprising of the channel assignment, power allocation, and transmission and reflection beamforming at the STAR-RIS for orthogonal multiple access (OMA) is first formulated. To solve this challenging problem, we first propose a channel assignment scheme utilizing matching theory and then invoke the alternating optimization-based method to optimize the resource allocation policy and beamforming vectors iteratively. Furthermore, the sum-rate maximization problem for non-orthogonal multiple access (NOMA) with flexible decoding orders is investigated. To efficiently solve it, we first propose a location-based matching algorithm to determine the sub-channel assignment, where a transmitted user and a reflected user are grouped on a sub-channel. Based on this <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">transmission-and-reflection</i> sub-channel assignment strategy, a three-step approach is proposed, which involves the optimization of decoding orders, beamforming-coefficient vectors, and power allocation, by employing semidefinite programming, convex upper bound approximation, and geometry programming, respectively. Numerical results unveil that: 1) For OMA, a general design that includes the same-side user-pairing for channel assignment is preferable, whereas for NOMA, the proposed transmission-and-reflection scheme can achieve comparable performance to the exhaustive search-based algorithm. 2) The STAR-RIS-aided NOMA network significantly outperforms networks employing conventional RISs and OMA.

Energy Harvesting for TDS-OFDM in NOMA-Based Underwater Communication Systems.

Non-orthogonal multiple access (NOMA) is considered a promising multiple access technique for fifth generation (5G) mobile networks and tactical internet due to its high spectral efficiency. Thanks to the high spectral efficiency of NOMA, it can be a strong candidate suitable for the limited channel bandwidth of underwater acoustic communication. The NOMA transmitter is employing superposition coding (SC). The NOMA receiver is based on the successive interference cancellation (SIC) technique. The multicarrier NOMA adopts orthogonal frequency division multiplexing (OFDM) as a multicarrier modulation (MCM) technique; however, conventional cyclic prefix OFDM (CP-OFDM) and zero padding (ZP-OFDM) have inefficient spectral efficiency. Thanks to efficient synchronization and high energy-spectral efficiency of the time-division synchronization OFDM (TDS-OFDM), it is a significant attractive candidate for underwater multicarrier communication. However, wasting the power transmission of long guard intervals in the battery-based underwater communication is represented as one of the TDS-OFDM main drawbacks. Harvesting energy and improving the energy efficiency of acoustic-based TDS-OFDM-NOMA represent high achievement goal battery recharging challenges due to the ocean environment. This paper proposes time switching simultaneous wireless information and power transfer (TS-SWIPT) to harvest the energy of transmitted power over the guard interval in the TDS-OFDM-NOMA scheme. The proposed energy harvested scheme harvests the energy from the wasted power in the long guard interval and improves the energy efficiency of the TDS-OFDM multicarrier scheme. This study demonstrates the superiority of the proposed TDS-OFDM-NOMA over the underwater acoustic channel by revealing high energy efficiency, high spectral efficiency, better bit error rate performance, and high system data throughput.

On the Exposure Dose Minimization of Multi-Antenna Multi-Carrier System Users

From the fourth generation (4G) of cellular systems onward, wireless personal devices (WPDs) support multi-input multi-output (MIMO) communication. However, the impact of MIMO communication on the electromagnetic field (EMF) of WPD users has yet to be fully understood and analyzed at the system level. In this paper, we first provide a generic model for assessing the individual exposure dose of multi-antenna WPD users in a multi-user multi-carrier communication system. An optimization framework for minimizing this exposure dose is then developed based on our exposure model. This framework helps us to identify a new criterion, i.e., the ratio between the normalized exposure dose and the channel to noise ratio (CNR), as the main system level criterion for minimizing the individual exposure dose of multi-antenna WPD users. This criterion is further integrated in the design of two novel centralized resource allocation schemes that take advantage of the multiple antennas at the WPD to minimize the per-user exposure dose, when full or limited knowledge of each user channel is available. Our new schemes can significantly reduce the individual exposure dose of WPD users (by approximately 80%) in comparison with the most relevant existing resource allocation schemes. Our results also provide insights into the logarithmic relationship between the per-user exposure dose and the number of receive antennas (or the number of time slots), and how such a parameter can be exploited to further reduce the exposure and/or provide a higher SE while maintaining a low exposure dose.

OTFS vs. OFDM in the Presence of Sparsity: A Fair Comparison

Many recent works in the literature declare that Orthogonal Time-Frequency-Space (OTFS) modulation is a promising candidate technology for high mobility communication scenarios. However, a truly fair comparison with its direct concurrent and widely used Orthogonal Frequency-Division Multiplexing (OFDM) modulation has not yet been provided. In this paper, we present such a fair comparison between the two digital modulation formats in terms of achievable communication rate. In this context, we explicitly address the problem of channel estimation by considering, for each modulation, a pilot scheme and the associated channel estimation algorithm specifically adapted to sparse channels in the Doppler-delay domain, targeting the optimization of the pilot overhead to maximize the overall achievable rate. In our achievable rate analysis we consider also the presence of a guard interval or cyclic prefix. The results are supported by numerical simulations, for different time-frequency selective channels including multiple scattering components and under non-perfect channel state information resulting from the considered pilot schemes. This work does not claim to establish in a fully definitive way which is the best modulation format, since such choice depends on many other features which are outside the scope of this work (e.g., legacy, intellectual property, ease and know-how for implementation, and many other criteria). Nevertheless, we provide the foundations to properly compare multi-carrier communication systems in terms of their information theoretic achievable rate potential, within meaningful and sensible assumptions on the channel models and on the receiver complexity (both in terms of channel estimation and in terms of soft-output symbol detection).

Data-Driven Signal Detection for Underwater Acoustic Filter Bank Multicarrier Communications

By contraposing the signal detection for filter bank multicarrier (FBMC) communications with the underwater acoustic (UWA) channel, this paper analyzes the traditional imaginary interference problem and proposes a deep learning-based method. The neural network with feature extraction and automatic learning ability is employed to replace the demodulation modules to recover transmitted signals without explicit channel estimation and equalization. Sufficient data sets are generated according to the measured channel conditions in Qingjiang river, the optimization of network parameters is finished by constraining cost function in offline training, and the signal detection is carried out directly with the well-trained network in online testing. The system performance of various supervised learning models such as multilayer perceptron (MLP), convolutional neural network (CNN), and bidirectional long short-term memory (BLSTM) network is compared under different data sizes, network parameters, and prototype filters. The simulation results show that the bit error rate (BER) performance of the proposed signal detection is better than that of the classic one, which indicates that deep learning is a promising tool in UWA communication systems.

Precoder and Decoder Co-Designs for Radar and Communication Spectrum Sharing.

The coexistence of radar and communication systems is necessary to facilitate new wireless systems and services due to the shortage of the useful radio spectrum. Moreover, changes in spectrum regulation will be introduced in which the spectrum is allocated in larger chunks and different radio systems need to share the spectrum. For example, 5G NR, LTE and Wi-Fi systems have to share the spectrum with S-band radars. Managing interference is a key task in coexistence scenarios. Cognitive radio and radar technologies facilitate using the spectrum in a flexible manner and sharing channel awareness between the two subsystems. In this paper, we propose a nullspace-based joint precoder–decoder design for coexisting multicarrier radar and multiuser multicarrier communication systems. The maximizing signal interference noise ratio (max-SINR) criterion and interference alignment (IA) constraints are employed in finding the precoder and decoder. By taking advantage of IA theory, a maximum degree of freedom upper bound for the -radar-communication-user interference channel can be achieved. Our simulation studies demonstrate that interference can be practically fully canceled in both communication and radar systems. This leads to improved detection performance in radar and a higher rate in communication subsystems. A significant performance gain over a nullspace-based precoder-only design is also obtained.

Communications Survival Strategies for Industrial Wireless Control

Industrial wireless control systems are mainly designed on the premise of time-sensitive ultra-reliable low-latency communications (URLLC). With the introduction of survival time to the quality of service requirements of such systems, the design paradigm has evolved from typical link reliability (i.e., minimizing packet error rate), to service availability, that is, minimizing the chance of burst errors, which can cause loss of communication for longer than survival time. In this article, we address the implications of this evolution and present a set of survival time strategies that are designed to guarantee end-to-end dependable industrial wireless control. To ensure service availability, transmissions are divided into normal and survival modes. The presented strategies include scheduling and link adaptation that are designed to target the differences between these modes of operation, traffic prioritization to enhance service availability for users in survival mode, and more efficient multi-node, multi-path, and multi-carrier communications techniques.