Temporal Channel Variations Research Articles

Blind Physical-Layer Authentication Based on Composite Radio Sample Characteristics

The promising physical-layer authentication (PLA) scheme enjoys low computational complexity and provides a lightweight solution for the wireless transmission security problem. However, the ideal but impractical assumptions are made on the priori knowledge in the traditional PLA schemes, which fail because the priori knowledge can be interfered by the impersonation attacks. Hence, a blind PLA scheme featured by the composite radio sample characteristics, active monitoring slots, and blind hypotheses tests is proposed in this paper. In particular, the intrinsic location-specific channel response integrated with the transmitter-specific signal knowledge is sampled during the active monitoring slots and is used to conduct minimum error (ME) and Neyman-Pearson (NP) hypothesis tests. The authentication reliability is enhanced significantly by jointly using the ME and NP criteria. For both the stationary and the non-stationary signal cases, our theoretical analysis shows that the temporal channel variations, the spatial channel correlations and the spectral bandwidth contribute to improve the authentication reliability. Our simulation results not only demonstrate the effectiveness of the proposed PLA scheme, but also indicate the possible scenarios in which ME outperforms NP, and NP outperforms ME.

Modified Integral Equation Method With Time-Varying Factors for Low-Frequency Ground-Wave Propagation Delay Prediction

A large amount of long-term measurements illustrate that the propagation delay of low-frequency (LF) ground-wave exhibits complex temporal variation properties. In this letter, we present a modified integral equation (IE) method to be capable of predicting the temporal variation of propagation delay. The modified method introduces suitable time-varying conductivity and refractivity models to characterize the temporal variation of propagation channel in terms of two aspects of ground and atmosphere. Comparisons between the modified method and experiment data along two actual propagation paths show good agreement. The effect of the time-varying factors controlling the conductivity and refractivity on propagation delay is further analyzed. It is found that compared to the refractivity, the time-varying factors in the conductivity have greater influence on the propagation delay.

A Method for Underwater Acoustic Key Detection Based on OFDM Pilot Sequences

The traditional physical layer key generation technology uses channel temporal variation, reciprocity, and spatial decorrelation to realize key distribution and fast update. However, due to the complex, time-varying and time-delayed features, the underwater acoustic channel environment often changes during channel detection, resulting in impaired channel reciprocity. To solve this problem, this paper proposes an orthogonal frequency division multiplexing pilot structure based on the features of underwater acoustic time-varying multipath channel. The structure can complete key detection when channel reciprocity is impaired, promotes the consistency of observation sequences, and reduces the key disagreement rate. The theoretical deduction proves the validity of the proposed method under an underwater acoustic multipath time-varying channel. Also, the simulation results verify the feasibility of the proposed method.

Efficient multiplexing using delayed CSI in few-mode fiber links

The constant demand for high data rates has resulted in few-mode optical fiber (FMF) based multiplexed systems an attractive solution. While the separability of FMF modes permits effective multiplexing, modal dispersion limits data rates. Conventional signal processing based approaches to compensate for modal dispersion incur significant computational complexity. On the other hand of principal modes (PMs) can mitigate dispersion with very little compensation requirements at the receiver. However, in the presence of high mode-dependent losses (MDL), the PMs’ performance degrades significantly. In this paper, we propose the use of a polar decomposition based scheme, wherein the impairments of the fiber can be viewed as a cascade of a dispersive system and a lossy (MDL) system. Compensating for the MDL using polar decomposition permits the use of PMs with near optimal performance. Further, we discuss effective quantization techniques to track the variation of PMs and propose effective low-rate feedback mechanisms for PM feedback to the transmitter for optimized transmission, with interpolation across WDM channels to reduce the feedback burden. Finally, we also discuss the impact of delay in feedback on achievable rate when the fiber channel undergoes temporal variation. Simulations reveal that the polar decomposition and quantized PM approach yields effective data rates for various fiber conditions, even with temporal channel variations, thereby indicating that this would be a promising solution for low complexity multiplexing based FMF systems.

Training Length Adaptation for Reinforcement Learning-Based Detection in Time-Varying Massive MIMO Systems With One-Bit ADCs

This study elucidates a reinforcement learning (RL)-based detection with one-bit analog-to-digital converters (ADCs) in time-varying massive multiple-input and multiple-output channels. In one-bit ADCs, conventional channel estimation exhibits poor performance owing to nonlinear quantization. The RL-based detection alleviates this degradation by learning the true likelihood probability during data transmission. However, in time-varying channels, the learned likelihood probability is inconsistent with the true likelihood probability due to temporal channel variations. This inconsistency can cause severe performance degradation. To effectively exploit the learned likelihood probability, we propose a training length adaptation method that determines an appropriate training length based on the channel conditions. To achieve this, we consider an optimization problem that minimizes the training length while guaranteeing the performance of RL-based detection. The solution of the optimization problem is obtained by an explicit form based on simple approximations, and it reveals that the optimal training length depends on the change in the likelihood probability. Simulation results demonstrate that the proposed method efficiently reduces the training length when a rapid change in likelihood probability is produced in fading channels. Moreover, this reduction contributes to improving the spectral efficiency by an avoiding undesirable learning process. Consequently, the spectral efficiency of the proposed method can be significantly increased compared to that of conventional RL-based detection. For instance, the proposed method achieves 1.76 times higher spectral efficiency than the conventional method at 30 km/h.

Physical Layer Authentication Jointly Utilizing Channel and Phase Noise in MIMO Systems

In this paper, we propose a physical layer authentication scheme in heterogeneous coexist multiple-input-multiple-output (MIMO) systems. This scheme utilizes two physical layer features in terms of location-specific channel gains and transmitter-specific phase noise caused by imperfect oscillators to identify transmitters. Three properties of the proposed scheme: covertness, robustness, and security, are analyzed in detail. By using a maximum-likelihood estimator (MLE) and extended Kalman filter (EKF), we estimate channel gains and phase noise, and formulate variances of estimation errors. We also quantize the temporal variations of channel gains and phase noise through the developed quantizers. Based on quantization results and theories of hypothesis testing and stochastic process, we then derive the closed-form expressions for false alarm and detection probabilities with the consideration of quantization errors. Simulations are carried out to validate the theoretical results of the two probabilities. Based on theoretical models, we further demonstrate that the proposed scheme makes it possible for us to flexibly control authentication performance by adjusting thresholds (for channel gain, phase noise, and decision, respectively) to achieve a required authentication performance in specific MIMO applications.

On the using of Rényi’s quadratic entropy for physical layer key generation

As a promising way for establishing secret keys, physical layer key generation has been broadly studied, which typically extracts secret keys with wireless channel characteristics. The existing schemes proved that temporal channel variations, channel reciprocity and spatial de-correlation of wireless channel greatly affected the performance of physical layer key generation. In this paper, the application of collision entropy (Rényi’s quadratic entropy) for improving physical layer key generation is discussed. Specifically, after collecting sufficient channel measurements, a channel measurement evaluation mechanism based on collision entropy is implemented to determine the adequacy of these measurements. Consequently, some consecutive measurements with smaller collision entropies are dropped and the reserved measurements are applied as input of the following process. Based on the evaluation mechanism, an adaptive and efficient key generation scheme is proposed. The proposed scheme consists of five components: channel probing, the evaluation mechanism, the adaptive quantization, information reconciliation and privacy amplification. To validate this scheme, several experiments in real environments are conducted. Different from the existing schemes, the received signal strength (RSS) measurements derived by heterogeneous devices are used as channel measurements. The results show that: (1) compared with homogeneous devices, RSS sequences of heterogeneous devices have more discrepancies and these discrepancies make key generation more challenging; (2) the proposed evaluation mechanism can effectively reduce bit mismatch rate and enhance the efficiency of information reconciliation; (3) compared with other schemes, the proposed key generation scheme can efficiently generate shared secret keys between heterogeneous transceivers in real environments.

Temporal Autocorrelation of Small-Scale Fading Using Leaky Coaxial Cable in Confined Space

In this letter, a narrow-band measurement at 1.8 GHz was conducted in a tunnel-like environment in order to investigate the temporal variation of small-scale fading with leaky coaxial cable (LCX) propagation. Both the vertically and horizontally polarized LCXs were used to generate different small-scale fading behavior which determines the channel temporal variation. Temporal variation was determined by statistical analysis in terms of coherence time extracted from empirical temporal autocorrelation of received signal power. Results show that larger coherence time exists in co-polarization transmission which has higher K-factor than cross-polarization transmission. This was also illustrated by a positive correlation between coherence time and K-factor. By using Akaike information criterion, Rice and Weibull are the best distributions to fit the amplitude of small-scale fading for co-polarization and cross-polarization, respectively. In addition, the corresponding Nakagami-Rice and Weibull autocorrelation functions were parameterized to well model small-scale temporal autocorrelation of received signal power measured in co-polarization and cross-polarization, respectively.

MISO Channel Estimation and Tracking from Received Signal Strength Feedback

Downlink channel estimation is an important task in any wireless communication system, and 5G massive multiple-input multiple-output in particular—because the receiver must estimate and feed back to the transmitter a high-dimensional multiple-input single-output (MISO) vector channel for each receiving element. This is a serious burden in terms of mobile computation and power, as well as uplink communication overhead. The starting point of this paper is that all existing and emerging wireless communication systems provide basic Received Signal Strength (RSS) / Channel Quality Indicator (CQI) feedback to compensate for temporal channel variations. Is it possible to estimate and track the vector MISO channel from RSS/CQI feedback alone? This paper shows that the answer is affirmative, if one employs time-varying beamforming and phase modulation together with phase retrieval ideas from optics and crystallography. Three efficient algorithms that cover different model assumptions are proposed to track the vector MISO channel on the transmitter's side using only RSS/CQI feedback. Numerical simulation results under various settings validate the efficacy of the proposed algorithms in tracking a slowly time-varying vector MISO channel. Interestingly, this is the first application of phase retrieval where assuming independent and identically distributed Gaussian measurement vectors can be practically justified.

Exploiting Temporal Correlation in Wireless Channel for Energy-Efficient Communication

Widespread adoption of Internet-of-Things (IoT) technology depends on cost-affordability of the devices and convenience of their usage in terms of long life. Energy-efficiency of the miniaturized wireless IoT devices is a key to the cost and convenience factors. While there have been a few prior studies on wireless channel adaptive communication strategies, in this paper we relook at the problem aiming at effectively characterizing the wireless fading channel and devising energy-efficient link-layer retransmission strategy suitable for IoT devices. In particular, we propose a new channel-adaptive strategy that depends on the rate of variation of wireless channel irrespective of the underlying channel fading distribution. We further show that the concept of average fade duration dependent retransmission is a special case of the proposed strategy. Extensive simulations show that the proposed scheme most effectively characterizes the temporal variations of wireless channel in comparison with the other existing schemes. Performance of the proposed retransmission strategy is compared with the competitive protocols using the Markov model. Numerical results demonstrate that, the proposed scheme offers a gain of about 9% in terms data throughput and about 12% in terms of energy efficiency in comparison to its nearest existing benchmark scheme.

The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and Its Implications

Millimeter wave (mmWave) has great potential in realizing high data rates, thanks to the large spectral channels. It is considered as a key technology for fifth-generation (5G) wireless networks and is already used in wireless LAN (e.g., IEEE 802.11ad). Using mmWave for vehicular communications, however, is often viewed with some skepticism due to a misconception that the Doppler spread would become too large at these high frequencies. This is not necessarily true when directional beams are employed. In this paper, closed-form expressions relating the channel coherence time and beamwidth are derived. Unlike prior work that assumed perfect beam pointing, the pointing error due to the receiver motion is incorporated to show that there exists a nonzero optimal beamwidth that maximizes the coherence time. We define a novel concept of beam coherence time, which is an effective measure of beam alignment frequency. Using the derived correlation function, the channel coherence time, and the beam coherence time, an overall performance metric considering both the channel time variation and the beam alignment overhead is derived. Using this metric, it is shown that beam realignment in every beam coherence time performs better than beam realignment in every channel coherence time.

Physical Layer Authentication Enhancement Using Two-Dimensional Channel Quantization

A novel physical layer authentication enhancement scheme is proposed in this paper by integrating multipath delay characteristics of wireless channels into the channel impulse response (CIR)-based physical layer authentication framework. In order to simplify the decision rule for authentication, a two-dimensional (2-D) quantization method is developed to preprocess the channel variations. More specifically, two one-bit quantizers are used to quantize the temporal channel variations in the dimensions of channel amplitude and path delay, respectively. Under a simple hypothesis testing, a new test statistic is developed based on the sum of outputs of the two quantizers. For performance analysis, false alarm rate (FAR) and probability of detection (PD) are defined based on the developed test statistic, and their closed-form expressions are derived as well. An optimization problem is defined for finding optimal parameters of the proposed scheme based on exhaustive search method. Monte Carlo simulations are utilized to evaluate the performance of the proposed scheme. Compared with other existing method in the literature, the proposed scheme outperforms significantly in spoofing detection.

Time reversal communication over doubly spread channels

Conventional time reversal can mitigate multipath delay dispersion by temporal focusing. But it is not applicable to time-varying channels with a Doppler spread. Although recently time reversal communication has been adapted to time-variant channels, the modified technique requires frequent channel updates to track channel variations and cannot handle large Doppler spread, which means that it cannot achieve frequency focusing. In this paper, two time reversal receivers for underwater acoustic communications over doubly spread channels are proposed. The proposed approach, which can be interpreted as time-frequency channel matching, is based on the channel spreading function rather than impulse response adopted by the existing techniques; this leads to much less frequent channel updates. Unlike existing methods that only correct a single Doppler shift, the proposed approach uses a rake-like structure to compensate for multiple Doppler shifts and hence can eliminate severe Doppler spread induced by temporal channel variations. Simulation results verify the effectiveness of the proposed approach, indicating that it can simultaneously counteract delay and Doppler spreads, achieving both temporal and frequency focusing.

Time reversal communication over doubly spread channels

Conventional time reversal can mitigate multipath delay dispersion by temporal focusing. But it is not applicable to time-varying channels with a Doppler spread. Although recently time reversal communication has been adapted to time-variant channels, the modified technique requires frequent channel updates to track channel variations and cannot handle large Doppler spread, which means that it cannot achieve frequency focusing. In this paper, two time reversal receivers for underwater acoustic communications over doubly spread channels are proposed. The proposed approach, which can be interpreted as time-frequency channel matching, is based on the channel spreading function rather than impulse response adopted by the existing techniques; this leads to much less frequent channel updates. Unlike existing methods that only correct a single Doppler shift, the proposed approach uses a rake-like structure to compensate for multiple Doppler shifts and hence can eliminate severe Doppler spread induced by temporal channel variations. Simulation results verify the effectiveness of the proposed approach, indicating that it can simultaneously counteract delay and Doppler spreads, achieving both temporal and frequency focusing.

Modeling and Simulation of Temporal Variation of Channel and Noise in Indoor Power-Line Network

Broadband power-line communication (PLC) technologies are one of the main parameters of digital convergence voice-data-video in the home environment. These technologies use the power-line network as a propagation and a communication medium. Its transmission quality depends on the frequency behavior of the propagation medium and the connected household electrical appliances. The impedance of those devices and noise levels has a great impact on the PLC systems. In this paper, a simulator for indoor power-line channels is presented. In this paper, a new approach is presented for modeling temporal variations of noise and channel on indoor power lines. A three-conductor power cable (phase, neutral, and ground) is modeled by a circuit of four elements (resistor R, inductor L, capacitance C, conductance G). The RLCG parameters are deduced from the impedance measurement in open circuit and in short circuit. The cable model is validated in time and frequency domains. Then, the temporal variation of periodic noise is modeled by a stochastic approach. The global model, combining both channel and noise variations, is validated by comparing SPICE simulation and measurement results.

Impact of Wireless Channel Temporal Variation on MAC Design for Body Area Networks

We investigate the impact of wireless channel temporal variations on the design of medium access control (MAC) protocols for body area networks (BANs). Our measurements-based channel model captures large and small time-scale signal correlations, giving an accurate picture of the signal variation, specifically, the deep fades which are the features that mostly affect the behavior of the MAC. We test the effect of the channel model on the performance of the 802.15.4 MAC both in contention access mode and TDMA access mode. We show that there are considerable differences in the performance of the MAC compared to simulations that do not model channel temporal variation. Furthermore, explaining the behavior of the MAC under a temporal varying channel, we can suggest specific design choices for the emerging BAN MAC standard.

Coherent underwater communication using passive time reversal over multipath channels

Passive time reversal exploits underwater acoustic channels’ spatial and temporal diversity. It can refocus multipath propagated signal at the receiver and can be realized simply by the passive phase conjugation (PPC) method. By the temporal focusing, time delay spread caused by multipath propagation is mitigated for spectral efficient coherent communications. However, the PPC method is unable to eliminate multipath and is limited by channel variations. An adaptive equalizer is therefore needed to compensate residual multipath after refocusing and to track channel temporal variations. Spatial diversity is obtained by using a vertical receiving array. In this paper we used 4-hydrophone array and demonstrated that the adaptive decision feedback equalization in conjunction with PPC significantly decreased the bit error rate.

Adaptive spatial multiplexing for time‐varying correlated MIMO channels

AbstractThis work presents an adaptive spatial multiplexing scheme for time‐varying correlated multiple‐input multiple‐output (MIMO) channels. Unlike the conventional spatially uncorrelated block fading channel model, both temporal channel variation in each data block and spatial correlation are considered in the design. The proposed system continuously transmits packets with identical structure. Each packet consists of a training phase followed by a data transmission phase. The training signal is used to estimate instantaneous channel state at the receiver. In each symbol period of data transmission phase, the transmitter simultaneously transmits multiple data streams, which are decoded at the receiver based on the estimated channel state. The transmitter is assumed to know only the channel statistics, with which the power and rate for each data stream as well as the number of data streams are adjusted in each symbol period to achieve a target bit error rate (BER). The results reveal that the throughput‐maximising transmission strategy makes a judicious diversity‐multiplexing tradeoff by allocating power to an optimum number of data streams. Moreover, the packet length is also optimised based on the temporal channel variation rate. The simulation results demonstrate that the throughput can be significantly enhanced by the optimum packet length. Copyright © 2009 John Wiley & Sons, Ltd.

Robust receiver design for MIMO single-carrier block transmission over time-varying dispersive channels against imperfect channel knowledge

We consider MIMO single-carrier block transmission over time-varying multipath channels, under the assumption that the channel parameters are not exactly known but are estimated via the least-squares training technique. While the channel temporal variation is known to negate the tone-by-tone frequency-domain equalization facility, it is otherwise shown that in the time domain the signal signatures can be arranged into groups of orthogonal components, leading to a very natural yet efficient group-by-group symbol recovery scheme. To realize this figure of merit we propose a constrained-optimization based receiver which also takes into account the mitigation of channel mismatch effects caused by time variation and imperfect estimation. The optimization problem is formulated in an equivalent unconstrained generalized-sidelobe-canceller setup. This enables us to directly model the channel mismatch effect into the system equations through the perturbation technique and, in turn, to further exploit the statistical assumptions on channel temporal variation and estimation errors for deriving a closedform solution. Within the considered framework the proposed robust equalizer can be combined with the successive interference cancellation mechanism for further performance enhancement. Flop count evaluation and numerical simulation are used to evidence the advantages of the proposed scheme.

MIMO Wireless Linear Precoding

This article provides a tutorial of linear precoding for a frequency- flat, single-user MIMO wireless system, examining both theoretical foundations and practical issues. The article first discusses principles for CSIT (channel-side information at the transmitter) acquisition and develops a dynamic CSIT model, which spans perfectly to statistical CSIT, taking into account channel temporal variation. It then presents the capacity benefits of CSIT and information theoretic arguments for exploiting the CSIT by linear precoding. A precoded system structure is then described, involving an encoder and a linear precoder. Criteria for designing the precoder are then discussed, followed by specific designs for different CSIT scenarios.