Channel Fading Coefficients Research Articles

Statistical beamforming for cell free massive MIMO under mixed LoS/ NLoS channels

In CF-mMIMO systems, the access point density is assumed to be comparable to, or much larger than the user density, leading to the possibility of existence of LoS links between the UEs and the APs. In this paper, we compare the rates achievable by CF-mMIMO systems under probabilistic LoS/ NLos channels, with and without acquiring the channel state information (CSI) of the fast fading components. We show that, under sufficiently large AP densities, statistical beamforming that does not require the knowledge about the fast fading components of the channels, performs almost at par with full beamforming, that utilizes the information about the fast fading channel coefficients, thus potentially avoiding the need for training during every frame. We validate our results via detailed Monte Carlo simulations, and also elaborate the conditions under which statistical beamforming can be successfully employed in massive MIMO systems with LoS/ NLoS channels.

ALAMOUTI SPACE-TIME CODING FOR VEHICULAR COMMUNICATIONS IN THE PRESENCE OF CHANNEL ESTIMATION ERRORS

In this paper, the error performance of the Alamouti space-time coding (STC) scheme is investigated for vehicle-to-vehicle (V2V) communication systems over imperfect cascaded fading channels. In vehicular communication systems, perfect knowledge of the channel state information is not available to the users at all times due to the rapid movement of communicating vehicles and fast change of the rich scattering environment which makes the fading effects in wireless channels more severe. Therefore, in the analysis, we consider the erroneous estimation of the channel gain, which is more realistic for practical scenarios. For this purpose, we first derive the moment-generation function (MGF) of the channel fading coefficient with estimation error in the case of the cascaded Nakagami-m fading conditions. Then, using the MGF, we obtain the closed-form symbol-error-rate (SER) expressions of Alamouti STC with two transmitting and L receiving antennas for the M-PSK and M-QAM modulation schemes. Then, the exact ergodic capacity expression is derived for the proposed system. Furthermore, the analytical results are verified through Monte-Carlo simulations. Numerical results show that the SER performance of V2V communication systems can be improved significantly by using Alamouti STC even in case of harsh fading conditions and full channel-state information is not available due to estimation errors.

Examination of the Bi-LSTM Based 5G-OFDM Wireless Network Over Rayleigh Fading Channel Conditions

Fifth generation (5G) wireless networks’ system performance is dependent on having perfect knowledge of the channel state information (CSI). Deep learning (DL) has helped improve both the end-to-end reliability of 5G and beyond fifth generation (B5G) networks and the computational complexity of these networks. This work uses the Bi-linear long short-term memory (Bi-LSTM) scheme to examine the overall performance of the 5G orthogonal frequency division multiplexing (OFDM) technology. The least squares (LS) channel estimation scheme is a famous scheme employed to estimate the fading channel coefficients due to their lower complexity without the prior CSI. However, this scheme has an exceedingly high CSI error. Using pilot symbols (PS) and loss functions, this work has proposed the Bi-LSTM 5G OFDM estimators to improve the channel estimation obtained by the LS approach. All simulation analysis uses convex optimization (CO) software (CVX software) and stochastic gradient descent (SGD). When combined with many PS (72) and a cross-entropy loss function, the proposed Bi-LSTM outperforms the long-short-term memory (LSTM) cross-entropy, LS, and minimum mean square error (MMSE) estimators in low, medium, and high signal-to-noise ratio (SNR) regimes. The computational and training times of Bi-LSTM and LSTM DL estimators are also compared. Because of its DNN design, it can evaluate massive datasets, find hidden statistical patterns and characteristics, establish underlying relationships, and transfer what it has learnt to other contexts. Statistical analysis of the bit error rate (BER) reveals that Bi-LSTM outperforms the MMSE in terms of accurate channel prediction.

Security analysis and secured access design for networks of image remote sensing

The secured access is studied in this paper for the network of the image remote sensing. Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sensor to the central collection point. In order to enhance the sensing quality for the remote uploading, the passive reflection surface technique is employed. If one eavesdropper that exists nearby this sensor is keeping on accessing the same networks, he may receive the same image from this sensor. Our goal in this paper is to improve the SNR of legitimate collection unit while cut down the SNR of the eavesdropper as much as possible by adaptively adjust the uploading power from this sensor to enhance the security of the remote sensing images. In order to achieve this goal, the secured energy efficiency performance is theoretically analyzed with respect to the number of the passive reflection elements by calculating the instantaneous performance over the channel fading coefficients. Based on this theoretical result, the secured access is formulated as a mathematical optimization problem by adjusting the sensor uploading power as the unknown variables with the objective of the energy efficiency maximization while satisfying any required maximum data rate of the eavesdropper sensor. Finally, the analytical expression is theoretically derived for the optimum uploading power. Numerical simulations verify the design approach.

A Bipartite Graph Neural Network Approach for Scalable Beamforming Optimization

Deep learning (DL) techniques have been intensively studied for the optimization of multi-user multiple-input single-output (MU-MISO) downlink systems owing to the capability of handling nonconvex formulations. However, the fixed computation structure of existing deep neural networks (DNNs) lacks flexibility with respect to the system size, i.e., the number of antennas or users. This paper develops a bipartite graph neural network (BGNN) framework, a scalable DL solution designed for multi-antenna beamforming optimization. The MU-MISO system is first characterized by a bipartite graph where two disjoint vertex sets, each of which consists of transmit antennas and users, are connected via pairwise edges. These vertex interconnection states are modeled by channel fading coefficients. Thus, a generic beamforming optimization process is interpreted as a computation task over a weighted bipartite graph. This approach partitions the beamforming optimization procedure into multiple suboperations dedicated to individual antenna vertices and user vertices. Separated vertex operations lead to scalable beamforming calculations that are invariant to the system size. The vertex operations are realized by a group of DNN modules that collectively form the BGNN architecture. Identical DNNs are reused at all antennas and users so that the resultant learning structure becomes flexible to the network size. Component DNNs of the BGNN are trained jointly over numerous MU-MISO configurations with randomly varying network sizes. As a result, the trained BGNN can be universally applied to arbitrary MU-MISO systems. Numerical results validate the advantages of the BGNN framework over conventional methods.

An intelligent reflecting surfaces based iterative PhC‐MIMO system for atmospheric optical channels

AbstractOptical intelligent reflecting surface (IRS) is regarded as a forward‐looking technology to deal with line‐of‐sight limitations in optical wireless communications. This paper proposes an iterative photon counting nonorthogonal multiple access‐multiple‐input–multiple‐output (NOMA‐MIMO) system based on optical IRS. By analyzing the geometric and misalignment losses under turbulence effect in the optical IRS‐based atmospheric channel, we construct the channel fading coefficient matrix of the NOMA‐MIMO system. At the receiver, a novel iterative parallel interference cancellation algorithm based on logarithmic likelihood ratio is developed for signal detection. Through the simulation of bit error rate (BER), the reliability of the proposed system is proved. Quantitatively, the BER performance can achieve at the dBJ per bit for the scenario of MIMO system. Furthermore, the numerical results of the external information transfer process indicated that the proposed system has a rapid convergence performance.

A Novel ISAC Transmission Framework Based on Spatially-Spread Orthogonal Time Frequency Space Modulation

In this paper, we propose a novel integrated sensing and communication (ISAC) transmission framework based on the spatially spread orthogonal time frequency space (SS-OTFS) modulation by considering the fact that communication channel strengths cannot be directly obtained from radar sensing. We first propose the concept of SS-OTFS modulation, where the key novelty is the angular domain discretization enabled by the spatial spreading/de-spreading. This discretization gives rise to simple and insightful effective models for both radar sensing and communication, which results in simplified designs for the related estimation and detection problems. In particular, we design simple beam tracking, angle estimation, and power allocation schemes for radar sensing, by utilizing the special structure of the effective radar sensing matrix. Meanwhile, we provide a detailed analysis on the pair-wise error probability (PEP) for communication, which unveils the key conditions for both precoding and power allocation designs for communication. Based on those conditions, we design a symbol-wise precoding scheme for communication based only on the delay, Doppler, and angle estimates from radar sensing, without the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge of the communication channel fading coefficients, and also propose a suitable power allocation. Furthermore, we notice that radar sensing and communication requires different power allocations. Therefore, we discuss the performances of both the radar sensing and communication with different power allocations and show that the power allocation should be designed leaning towards radar sensing in practical scenarios. The effectiveness of the proposed ISAC transmission framework is verified by our numerical results, which also agree with our analysis and discussions.

Achievable Rate Upper-Bounds of Uplink Multiuser OTFS Transmissions

In this letter, we study the achievable rates adopting two delay-Doppler (DD) domain multiples access (MA) schemes for uplink orthogonal time frequency space (OTFS) transmissions, namely delay division multiple access (DDMA) and Doppler division multiple access (DoDMA). To shed light on the system performance, we establish the achievable rate upper-bounds for both DDMA and DoDMA in comparisons to that of the conventional orthogonal frequency division multiple access (OFDMA). In particular, we show that both DDMA and DoDMA have more robust signal-to-interference-plus-noise ratio (SINR) performances against channel fluctuations compared to OFDMA and this robustness leads to higher achievable rates for both DDMA and DoDMA. To be more specific, we find that the achievable rate upper-bounds for OTFS depend only on the channel fading coefficients of different paths and the multi-user interference (MUI), while the delay and Doppler shifts also have significant impacts on that of the conventional OFDMA. Our simulation results are consistent with our derivations and demonstrate a noticeable improvement of the achievable rates for both DDMA and DoDMA over OFDMA.

The Role of Correlation in the Doubly Dirty Fading MAC With Side Information at the Transmitters

We investigate the impact of fading correlation on the performance of the doubly dirty fading multiple access channel (MAC) with non-causally known side information at transmitters. Using Copula theory, we derive closed-form expressions for the outage probability (OP) and the coverage region under positive/negative dependence conditions. We show that a positive dependence structure between the fading channel coefficients is beneficial for the system performance, as it improves the OP and extends the coverage region compared to the case of independent fading. Conversely, a negative dependence structure has a detrimental effect on both performance metrics.

Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment

This paper proposes a deep learning approach to the adaptive and sequential beamforming design problem for the initial access phase in a mmWave environment with a single-path channel. For a single-user scenario where the problem is equivalent to designing the sequence of sensing beamformers to learn the angle of arrival (AoA) of the dominant path, we propose a novel deep neural network (DNN) that designs the adaptive sensing vectors sequentially based on the available information so far at the base station (BS). By recognizing that the AoA posterior distribution is a sufficient statistic for solving the initial access problem, we use the posterior distribution as the input to the proposed DNN for designing the adaptive sensing strategy. However, computing the posterior distribution can be computationally challenging when the channel fading coefficient is unknown. To address this issue, this paper proposes to use an estimate of the fading coefficient to compute an approximation of the posterior distribution. Further, this paper shows that the proposed DNN can deal with practical beamforming constraints such as the constant modulus constraint. Numerical results demonstrate that compared to the existing adaptive and non-adaptive beamforming schemes, the proposed DNN-based adaptive sensing strategy achieves a significantly better AoA acquisition performance.

Performance of optical space shift keying under jamming.

In this paper, the effect of jamming in a free-space optical (FSO) communication system that employs optical space shift keying (OSSK) is studied. The optical link suffers from saturated atmospheric turbulence (AT). Hence, the channel fading coefficients follow negative exponential probability density function (PDF). Along with additive Gaussian noise, the jammer, under consideration, is an additional source of noise, and jamming signals also suffer from saturated AT. Thus, the jamming channel also follows the negative exponential PDF. A multiple-input single-output (MISO) FSO system is used to mitigate the effects of jammer and channel fading. Explicitly, we employ a 2×1 MISO-OSSK system for analysis and derive a closed-form expression of bit error rate (BER) of the considered system. Moreover, the jammer's effect is also studied numerically under the gamma-gamma (GG) fading channel.

Nelder-Mead Simplex Channel Estimation for the RF-DNA Fingerprinting of OFDM Transmitters Under Rayleigh Fading Conditions

The Internet of Things (IoT) is a collection of Internet connected devices capable of interacting with the physical world and computer systems. It is estimated that the IoT will consist of approximately fifty billion devices by the year 2020. In addition to the sheer numbers, the need for IoT security is exacerbated by the fact that many of the edge devices employ weak to no encryption of the communication link. It has been estimated that almost 70% of IoT devices use no form of encryption. Previous research has suggested the use of Specific Emitter Identification (SEI), a physical layer technique, as a means of augmenting bit-level security mechanism such as encryption. The work presented here integrates a Nelder-Mead based approach for estimating the Rayleigh fading channel coefficients prior to the SEI approach known as RF-DNA fingerprinting. The performance of this estimator is assessed for degrading signal-to-noise ratio and compared with least square and minimum mean squared error channel estimators. Additionally, this work presents classification results using RF-DNA fingerprints that were extracted from received signals that have undergone Rayleigh fading channel correction using Minimum Mean Squared Error (MMSE) equalization. This work also performs radio discrimination using RF-DNA fingerprints generated from the normalized magnitude-squared and phase response of Gabor coefficients as well as two classifiers. Discrimination of four 802.11a Wi-Fi radios achieves an average percent correct classification of 90% or better for signal-to-noise ratios of 18 and 21 dB or greater using a Rayleigh fading channel comprised of two and five paths, respectively.

Optimization of secondary user capacity in a centralized cooperative cognitive radio network with primary user under priority

AbstractThe primary objective of cognitive radio is to maximize the spectrum utilization and the capacity of secondary users under standard parametric constraints. The radiometer, or energy detection, is one of the convenient methods of spectrum sensing under a cooperative communication framework. However, the selection of a suitable threshold is a major issue in order to optimize the secondary user capacity considering primary user on priority. In this article, we investigate a double threshold energy detection scheme and obtain an analytical model for optimum thresholding in diverse fading conditions under the constraint of the probability of detection. We use a meta‐heuristic optimization algorithm, namely, the particle swarm optimization with an aging leader and challengers, to observe the effect of varying threshold levels in fusion region, signal to noise ratio (SNR) levels of primary user, and calculate the normalized achievable capacity of secondary user for various fading channels. The results show that, with increasing value of threshold within the decision region, the probability of detection decreases while the normalized secondary user capacity is enhanced. Conversely, the probability of detection increases and the normalized secondary user capacity decreases with increasing values of the SNR level. We also observe the effect of receiver diversity with maximal ratio combining for Nakagami‐m fading channel coefficients. The result shows that the probability of detection and normalized capacity decrease with an increase of the number of receiver branches.

Impact of Intra-Cluster Angular Spread on the Performance of NLoS Millimeter Wave Links With Imperfect Beam Alignment

Beam misalignment is an unavoidable occurrence in millimeter wave (mmWave) wireless communication systems which causes a drop in achievable spectral efficiency (SE) and adversely affects the link-level performance. Spatial parameters of the mmWave propagation channel, especially angle distributions of multi-path components are vital in assessing the loss in achievable capacity due to imperfect beam alignment in such systems. In this paper, we present a tractable approach to quantify the achievable SE of beamformed Non-Line-of-Sight (NLoS) links in mmWave fading channels with intra-cluster angular spread. We derive the expression for achievable SE of a point-to-point mmWave NLoS link after accounting for random beam misalignment errors at the transmitter as well as receiver end. Using analytic approximations, we consider the impact of antenna beam pattern parameters, and use a comprehensive mmWave channel model for performance evaluation. The analysis provides realistic bounds on achievable SE since the intra-cluster angular spread of rays at both ends is taken into account. We provide insights into the interplay between antenna half power beam width, the degree of misalignment, channel fading coefficient, channel coherence parameter and the angular spread of rays to demonstrate the decisive impact of intra-cluster spread on the performance of mmWave point-to-point NLoS links.

Interference Cancellation, Channel Estimation, and Symbol Detection for Communications on Overlapping Channels

In this paper, we propose the joint interference cancellation, fast fading channel estimation, and data symbol detection for a general interference setting where the interfering source and the interfered receiver are unsynchronized and occupy overlapping channels of different bandwidths. The interference must be canceled before the channel estimation and data symbol detection of the desired communication are performed. To this end, we have to estimate the Effective Interference Coefficients (EICs) and then the desired fast fading channel coefficients. We construct a two-phase framework where the EICs and desired channel coefficients are estimated using the joint maximum likelihood-maximum a posteriori probability (JML-MAP) criteria in the first phase; and the MAP based data symbol detection is performed in the second phase. Based on this two-phase framework, we also propose an iterative algorithm for interference cancellation, channel estimation and data detection. We analyze the channel estimation error, residual interference, symbol error rate (SER) achieved by the proposed framework. We then discuss how to optimize the pilot density to achieve the maximum throughput. Via numerical studies, we show that our design can effectively mitigate the interference for a wide range of SNR values, our proposed channel estimation and symbol detection design can achieve better performances compared to the existing method. Moreover, we demonstrate the improved performance of the iterative algorithm with respect to the non-iterative counterpart.

Blind Signal Detection Under Synchronization Errors for FSO Links With High Mobility

We consider the use of free-space optical communication for fast moving platforms such as high-speed trains, where the sampling clock offset is randomly changing, in addition, the receiver does not have any information on the instantaneous channel fading coefficient. By employing multiple samplers at the receiver, we propose a class of sequence detection methods for the case of On-Off keying (OOK) signaling without using any training sequence. First, we study maximum likelihood-based detection, which has a relatively high-computational complexity. Second, by employing generalized likelihood ratio test, we propose a more practical blind sequence detection method of reduced complexity. To further reduce the computational complexity, third, we propose a novel scheme that uses two wavelengths at the transmitter and differential blind detection at the receiver. Fourth, to benefit from diversity gain with this differential scheme, we consider the use of sufficiently different wavelengths along with sufficient spatial separation between the transmitters and/or the receivers, where we propose an efficient blind detection method. The pros and cons of the proposed detection methods are contrasted through numerical results and their processing loads are compared.

Generalized channel estimation and data detection for MIMO multiplexing FSO parallel channels over limited space

In this paper, to increase the data rate of free-space optical (FSO) links, we consider multiple parallel FSO links arranged over a specified space (transceivers arranged over two rings with specified radius). Due to its ease of implementation, stability, and low cost, intensity modulation with direct detection (IM/DD) based on On–Off-Keying (OOK) is widely employed in practical terrestrial FSO links. For long-haul FSO links, avalanche photo diodes (APDs) are commonly used, which provide an internal gain in photo-detection, allowing larger transmission ranges, as compared with PIN photo-detector counterparts. Over the considered general case, firstly, we propose maximum likelihood (ML)-based detection methods when the receivers are aware of the instantaneous channel fading coefficients (CSI). Secondly, we propose an efficient OOK data detection method for a more practical case when the instantaneous CSI is not available at the receiver. For this state, initially, the channel coefficients are estimated by employing some pilot symbols and then, we use the channel estimated coefficients to detect OOK signals. For a specified space, due to crosstalk between parallel channels and pointing errors, performance of proposed data detection methods depends on the optimum value for beam waist. By providing Monte-Carlo simulation results, the optimum value of beam waist is obtained for various channel conditions. To evaluate the BER performance, we also provide analytical results and derive an analytical expression for the considered MIMO multiplexing scheme. The validity of our analytical results are confirmed by Monte-Carlo simulations.

Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems

SummaryIn realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity.

Receiver Design for OOK Modulation Over Turbulence Channels Using Source Transformation

For coherent detection of ON-OFF keying (OOK) symbols in free-space optical (FSO) communications, the receiver requires the instantaneous channel fading coefficients. To accurately detect OOK symbols over FSO channels without requiring transmission of pilot symbols, in the first part of this letter, we propose an expectation-maximization (EM)-based sequence detection (SD) method with low implementation complexity which is shown to be particularly suitable for fast FSO communication systems. In the second part of this letter, to remove the error floor and to improve the accuracy of the proposed detector, by utilizing a source information transformation we propose an EM-based SD for this state which significantly outperforms than classical EM-based method.

Reliable Control Against Sensor Failures for Markov Jump Systems With Unideal Measurements

The problem of state-feedback reliable control against sensor failures for Markov jump nonlinear systems taking into account the mixed time delays is investigated in this paper. To describe the phenomenon of imperfect transmission between the system and the controller, a mode-dependent stochastic measurement fading model is adopted. By introducing two mutually independent and mode-dependent fading channel coefficients, the undulation of communication workload caused by the change of system mode can be accurately described. Also, the mixed time delays including the discrete and the infinite distributed delays are considered. Our goal is to design a reliable controller, which can guarantee the passivity of the closed-loop control system even when some sensors experience faults or failures. To realize this reliable controller, we introduce an additional matrix and utilize some inequality techniques. By using Lyapunov function technique, the gain of the designed controller can be solved. The merits and effectiveness of the developed design scheme are verified by a simulation example.