Slow Fading Channels Research Articles

Channel-Blind Joint Source-Channel Coding for Wireless Image Transmission.

Joint source-channel coding (JSCC) based on deep learning has shown significant advancements in image transmission tasks. However, previous channel-adaptive JSCC methods often rely on the signal-to-noise ratio (SNR) of the current channel for encoding, which overlooks the neural network's self-adaptive capability across varying SNRs. This paper investigates the self-adaptive capability of deep learning-based JSCC models to dynamically changing channels and introduces a novel method named Channel-Blind JSCC (CBJSCC). CBJSCC leverages the intrinsic learning capability of neural networks to self-adapt to dynamic channels and diverse SNRs without relying on external SNR information. This approach is advantageous, as it is not affected by channel estimation errors and can be applied to one-to-many wireless communication scenarios. To enhance the performance of JSCC tasks, the CBJSCC model employs a specially designed encoder-decoder. Experimental results show that CBJSCC outperforms existing channel-adaptive JSCC methods that depend on SNR estimation and feedback, both in additive white Gaussian noise environments and under slow Rayleigh fading channel conditions. Through a comprehensive analysis of the model's performance, we further validate the robustness and adaptability of this strategy across different application scenarios, with the experimental results providing strong evidence to support this claim.

Message Transmission and Common Randomness Generation Over MIMO Slow Fading Channels With Arbitrary Channel State Distribution

Message Transmission and Common Randomness Generation Over MIMO Slow Fading Channels With Arbitrary Channel State Distribution

Performance analysis of dual‐hop dual‐branch amplify‐and‐forward relaying cooperative diversity system using best‐path selection technique over Nakagami‐m fading channels

AbstractOne of the promising technologies for achieving virtual diversity gains is cooperative relaying. This study considers a dual‐hop dual‐branch cooperative diversity system with an amplify‐and‐forward mechanism where the hop count here means the total number of relays between source and destination which equals two. Utilizing the best‐path selection combining technique, a closed‐form formula for the average bit error rate and outage probability is obtained. Furthermore, between the nodes in the two branches, we consider independent non‐identical Nakagami‐m slow flat fading channels. The Monte Carlo simulation results are confirmed with the analytical ones.

Collaborative Semantic Communication for Edge Inference

We study the collaborative image retrieval problem at the wireless edge, where multiple edge devices capture images of the same object from different angles and locations, which are then used jointly to retrieve similar images at the edge server over a shared multiple access channel (MAC). We propose two novel deep learning-based joint source and channel coding (JSCC) schemes for the task over both additive white Gaussian noise (AWGN) and Rayleigh slow fading channels, with the aim of maximizing the retrieval accuracy under a total bandwidth constraint. The proposed schemes are evaluated on a wide range of channel signal-to-noise ratios (SNRs), and shown to outperform the single-device JSCC and the separation-based multiple-access benchmarks. We also propose a channel state information-aware JSCC scheme with attention modules to enable our method to adapt to varying channel conditions.

Amplify-and-Forward (AF) Relay Techniques in Wireless SC-FDE Systems to Enhance Diversity Gains

This paper introduces an amplify-and-forward (AF) relaying technique that employs phase dithering and intentional delay within single carrier-frequency domain equalizer (SC-FDE) systems. The proposed relaying technique aims to increase the gain of both frequency diversity and time diversity in slow fading channels. To achieve this, the proposed technique introduces random phase rotation and random intentional delay. The relaying scenario assumes two-hop communication with relaying between the source and destination. It is assumed that many nodes are densely distributed, allowing for many relay nodes to participate in relaying. To verify the performance through computer simulation, the number of relays is 1, 2, 3, 5, 15, and 25, and three modulation coding schemes (MCSs) are considered: QPSK with R=1/3, 16QAM with R=3/4, and 8PSK with R=7/8. The simulation results demonstrate that the proposed relaying technique improves the bit error ratio (BER) performance. The performance improves as the number of relays increases.

Tutorial for Space-Time ICI Parallel Cancellation Techniques for OFDM Systems

Orthogonal frequency division multiplexing (OFDM) expects the subcarriers to be orthogonal. However, the factors, such as residual carrier frequency, offset time variations due to Doppler shift or phase noise leads to a loss in the orthogonality between subcarriers and results in inter-carrier interference (ICI). Further developing the parallel cancellation (PC) scheme to mitigate the ICI of OFDM systems, the authors expand this OFDM symbol-based PC scheme into a space-time (ST) coded system. This simple space-time parallel cancellation (STPC) scheme is a technique that combines the useful properties of ST and PC schemes together. Computer simulations indicate that OFDM systems using the STPC scheme outperform the regular PC and ST systems in slow and fast frequency selective fading channels, specifically at a high signal-noise ratio (SNR). Furthermore, the error floor of the STPC-OFDM system is significantly lower than that of the regular ST systems without increasing computational load.

Transmit Power Adaptation for D2D Communications Underlaying SWIPT-Based IoT Cellular Networks

Device-to-device (D2D) communications and simultaneous wireless information and power transfer (SWIPT) technologies are key to Internet of Things (IoT) to achieve massive connectivity and to prolong battery lifetime, respectively. In this article, we propose novel schemes for transmit power adaptation to maximize the average data rate and to minimize the outage probability of D2D communications over fast and slow-fading channels, respectively, where the D2D network coexists with a SWIPT-based IoT cellular network operating with the time-switching protocol. Also, different from the existing works, circuit power consumption for information decoding is taken into account in this article. To solve the formulated nonconvex power adaptation problems, we first derive tractable lower bound and upper bound on the average data rate and outage probability of cellular user (CU), respectively. Then, based on the conservative approximation, power adaptation solutions are determined. Intriguingly, we show that in the proposed schemes, the performance tradeoff between information decoding and energy harvesting at the CU is not degraded despite the reception of the D2D signals (i.e., interfering signals). Furthermore, deriving and analyzing closed-form bounds on the D2D performance, we obtain useful insights into the D2D performance improvement by the proposed power adaptation schemes. Numerical results demonstrate that the proposed schemes outperform the baseline scheme, and verify the obtained insights.

Secrecy Performance Evaluation of Scalable Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach

This paper presents the first performance analysis of physical layer downlink secure transmissions in a scalable cell-free massive MIMO (SCF-mMIMO) system. A stochastic geometry approach is used to model the locations of the access points (APs), user equipments (UEs) and eavesdroppers (Eves) as independent homogeneous Poisson point processes (HPPPs). In addition to applying maximum ratio transmission (MRT) to send the confidential messages, null-space artificial noise is also injected for secrecy enhancement. We analytically characterize the secrecy performance in terms of both the outage-based secrecy transmission rate (STR) and the ergodic secrecy rate (ESR), appropriate for slow quasi-static fading channels and fast block-fading channels, respectively. By utilizing moment matching and Gil-Pelaez inversion theorem, we are able to obtain mathematically tractable approximations for the performance metrics. These approximations are shown to have high accuracy as compared to simulation results. Our numerical results reveal useful design insights that cannot be inferred from existing studies. These insights answer important questions such as whether it is best to deploy as many APs each with fewer antennas and to what extent the artificial noise insertion is beneficial.

Impedance Variation Detection at MISO Receivers

Techniques have been proposed to estimate unknown antenna impedance due to time-varying near-field loading conditions at multiple-input single-output (MISO) receivers. However, it remains unclear when a change occurs and impedance estimation becomes necessary. In this letter, we address this problem by formulating it as a hypothesis test. Our contributions include deriving a generalized likelihood-ratio test (GLRT) detector to decide if the antenna impedance has changed over two groups of packets. This GLRT formulation leads to a novel optimization problem, but we propose a binary search based algorithm to solve it efficiently. Our derived GLRT detector enjoys a better detection and false alarm trade-off when compared with a well-known, reference detector in simulations. As one result, more transmit diversity significantly improves detection accuracy at a given false alarm rate, especially in slow fading channels.

Vandermonde-Based Unitary Precoding Method for Integer-Forcing Design

An integer-forcing linear receiver has significantly better performance than conditional receivers for slow-fading channels because it directly recovers an integer linear combination of signals instead of decoding all signals. The performance in terms of achievable rate, outage probability, and error rate can be improved with a unitary matrix precoder imposed at each channel realization. In this paper, a new special unitary matrix precoding approach is proposed to reduce the computational complexity. Different from the parameterization technique with many parameters, the new method constructs a unitary Vandermonde matrix with only a single parameter. The optimal Vandermonde matrix is determined on the basis of the shortest vector of a lattice generated by the precoding matrix in which the single parameter is searched. Therefore, its complexity is reduced to a polynomial time, whereas the traditional unitary precoder has exponential complexity. Simulation results show that the proposed scheme can achieve the performance similar to the benchmark schemes but with much lower complexity. The scheme offers a good trade-off between performance and complexity.

Joint Task Offloading and Resource Allocation for IoT Edge Computing With Sequential Task Dependency

Incorporating mobile-edge computing (MEC) in the Internet of Things (IoT) enables resource-limited IoT devices to offload their computation tasks to a nearby edge server. In this article, we investigate an IoT system assisted by the MEC technique with its computation task subjected to sequential task dependency, which is critical for video stream processing and other intelligent applications. To minimize energy consumption per IoT device while limiting task processing delay, task offloading strategy, communication resource, and computation resource are optimized jointly under both slow and fast-fading channels. In slow fading channels, an optimization problem is formulated, which is nonconvex and involves one integer variable. To solve this challenging problem, we decompose it as a 1-D search of task offloading decision problem and a nonconvex optimization problem with task offloading decision given. Through mathematical manipulations, the nonconvex problem is transformed to be a convex one, which is shown to be solvable only with the simple Golden search method. In fast-fading channels, optimal online policies depending on the instant channel state are derived even though they are entangled. In addition, it is proved that the derived policy will converge to the offline policy when the channel coherence time is low, which can help save extra computation complexity. Numerical results verify the correctness of our analysis and the effectiveness of our proposed strategies over the existing methods.

DATA TRANSMISSION IN MIMO-OFDM TECHNOLOGIES FOR CURRENT AND FUTURE WIRELESS COMMUNICATION SYSTEMS: FROM THEORY TO PRACTICE

This paper presents a Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) communication system with space-time and space-Frequency block coded (STBC/SFBC) of present generation downlink channel. Space-time block coding (STBC) and space-frequency block coding are transmit diversity schemes used in a wireless communication system to mitigate the effect of channel fading. The system is aimed to reduce the error rate (BER) by mitigating the effect of multipath fading which increase the quality of the system. In the proposed system, 2 transmit and 2 receive antennas are used, to transmit modulated symbols of block N across an OFDM channel, using SFBC Alamouti’s based encoding algorithm (SFBC-OFDM) derives from the basic criteria for space-time block codes (STBC). The signals from the first and second antennas are encoded and transmitted simultaneously in space and frequency over frequency-selective Rayleigh fading channel using two adjacent carriers. The work examines the SFBC and spatial diversity benefits realized based on the BER performance. The result is simulated effectively using MATLAB application software and the BER performance is compared with the conventional STBC-OFDM. It is shown that both STBC and SFBC techniques achieve similar performance with a diversity gain of four (4) over a slow fading channel with 2 antennas at both ends of the link under simple processing across the transmit and receive antennas.

Human Activity Recognition Based on the Fading Characteristics of the On-Body Channel

Several solutions using wearable devices for continuous Human Activity Recognition (HAR) have been proposed up to now, and HAR sensor-based methods are by far the most adopted. However, many data transmission obstacles prevent the viable operation of these systems, such as those related to deep channel fading, the shadowing of body links during movements, packet loss resulting from unpredictable and dynamic body movements, and environmental variations. In this work, a novel HAR approach based solely on on-body Received Signal Strength Indicator (RSSI) measurements of different body channels is presented to discriminate various human activities. In this perspective, a novel hierarchical threshold-based algorithm is proposed to classify RSSI data into two classes. The first one encompasses static movements. The second one groups dynamic movements. In this paper, the features provided to machine learning algorithms are unconventionnaly based on the statistical characterization parameters of the body channel in an indoor environment. These parameters include the average of the slow fading channel component and the fast fading component’s cumulative distribution function (CDF). In addition, the impact of the sliding window size adopted for the extraction of the slow fading component is investigated, as well as the impingement of the placement of the radio nodes on the body for the selection of the best on-body link for the transmission. It is shown that the proposed scheme provides higher accuracy compared to the state of the art radio-based HAR techniques and that the mislabeling problem is reduced by distinguishing between static and dynamic activities. Indeed, an approximate F1 score-based accuracy of 99% is obtained with a demeaning window size of 50 ms, considering the most informative channel.

An adaptive q-Lognormal model towards the computation of average channel capacity in slow fading channels

The characterization of multipath fading and shadowing in wireless communication systems is essential towards the evaluation of various performance measures. It is well known that the statistical characterization of shadowing phenomena is captured by distributions viz., log-normal distribution, gamma distribution and other mixture distributions. However, it is observed that the log-normal distribution fails to characterize the outliers in the fading signal. The extreme fluctuations in the fading signal needs to be characterized efficiently for error free computation of the various performance metrics. In this context, this paper portrays an adaptive generalized Tsallis’ non-extensive q-Lognormal model towards the characterization of various fading channels. This model operates well with the synthesized fading signals and captures the wide range of tail fluctuations to adapt different fading scenarios. The significance and applicability of the proposed novel q-lognormal model in capturing the slow fading channels is validated using different statistical tests viz., chi-square test and symmetric JS measure. Furthermore, essential performance measures viz., the average channel capacity, closed form expression of cumulative distribution function (CDF) in terms of Gauss-Hypergeometric function \({}_2{F_1}\left[ {\mathrm{{a, b, c; z}}} \right] \), moment generating function, higher order moments corresponding to q-Lognormal channel capacity and coefficient of variation is evaluated corresponding to the proposed q-lognormal model performing extensive Monte-Carlo simulation techniques up to \(O(10^7)\).

Game Theory for Anti-Jamming Strategy in Multichannel Slow Fading IoT Networks

The open nature of the wireless communication medium renders it vulnerable to jamming attacks by malicious users. To detect their presence and to avoid such attacks, several techniques are present in the literature. Most of these techniques aim to reduce the effect of the jamming signals by increasing the transmission power or by using complex coordination schemes. However, the implementation of such power consuming techniques might be challenging or not feasible in limited resources Internet-of-Things (IoT) devices. Therefore, a defending strategy against jamming attacks in health monitoring IoT networks is proposed in this article. This strategy operates in orthogonal frequency-division multiplexing channels and takes into consideration the effect of slow fading channels in the strategy design. Specifically, the jamming combating problem is formulated as a Colonel Blotto game where the equilibrium defines the minimization of the worst case jamming effect on the IoT sensors communications. Then, the optimal power allocation strategy for all the potential jammer power ranges is derived by investigating the Nash equilibrium of the game. This proposed strategy is shown to be efficient in combating jamming attacks while minimizing the IoT sensors power consumption.

Wireless Covert Communications Aided by Distributed Cooperative Jamming Over Slow Fading Channels

In this paper, we study covert communications between a pair of legitimate transmitter-receiver against a watchful warden over slow fading channels. There coexist multiple friendly helper nodes who are willing to protect the covert communication from being detected by the warden. We propose an uncoordinated jammer selection scheme where those helpers whose instantaneous channel gains to the legitimate receiver fall below a pre-established selection threshold will be chosen as jammers radiating jamming signals to defeat the warden. By doing so, the detection accuracy of the warden is expected to be severely degraded while the desired covert communication is rarely affected. We then jointly design the optimal selection threshold and message transmission rate for maximizing covert throughput under the premise that the detection error of the warden exceeds a certain level. Numerical results are presented to validate our theoretical analyses. It is shown that the multi-jammer assisted covert communication outperforms the conventional single-jammer method in terms of covert throughput, and the maximal covert throughput improves significantly as the total number of helpers increases, which demonstrates the validity and superiority of our proposed scheme.

Secure physical layer short-packet communication for 5G

Wireless short-packet communication is one of the key technologies for realizing 5G Internet of Things (IoT) applications such as massive machine type communication (mMTC) and ultra-reliable low latency communication (uRLLC). For applications such as the industrial IoT and the Internet of Vehicles, the security of wireless communication is of paramount importance. This paper investigates the secure transmission from the perspective of physical layer security for short-packet communication systems under slow fading channels. A secrecy outage probability (SOP) is defined based on the conclusion of secure short-packet communication information theory, while the reliable throughput with the SOP restriction is established as the secure communication performance metric of the short-packet communication system. On this basis, adaptive and non-adaptive encoder schemes are designed, reliable throughputs under these two encoder schemes can be maximized by designing coding rates and optimizing transmission thresholds with the explicit/partial instantaneous channel state information (CSI) of the legitimate channel, respectively. Whats more, the impacts of main system parameters on the optimal throughput are further analyzed. Numerical results verify the effectiveness of transmission schemes, and verify impacts of main system parameters on the secure performance of the transmission systems with SOP constraints.

A novel low-complexity power allocation algorithm based on the NOMA system in a low-speed environment

For future wireless communication systems, Power Domain Non-Orthogonal Multiple Access (PD-NOMA) using an advanced receiver has been considered as a promising radio access technology candidate. Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput (GMUT) performance. However, most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals (UTs) move in a slow fading channel environment. To resolve such problems, a power allocation method is proposed to considerably reduce the search space of a Full Search Power (FSP) allocation algorithm. The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance. Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process. The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5% compared with the FSP algorithm.

Capacity and BER analysis of BCH and LDPC coded FSO communication system for different channel conditions

Free space optical (FSO) communication is of paramount importance for the design of next-generation 5G+ wireless networks. These are, however, susceptible to degrading effects of atmospheric turbulence. The use of error correcting codes (ECCs) can mitigate the effects of fading caused by atmospheric turbulence. We evaluate the performance of uncoded and coded FSO communication system, where we use Bose Chaudhuri Hocquenghem (BCH) and low-density parity-check codes for the coded system. Both the systems under consideration are based on intensity-modulation and direct detection. We investigate the performance of a coded communication system under various channel conditions, viz., slow fading and fast fading gamma–gamma channels for different turbulence regimes and subsequently, obtain the coding gain. We derive the expressions of channel capacity for a fast fading channel and outage capacity for a slow fading channel. We conclude that ECCs deteriorate the bit error rate performance in a slow fading channel. However, for this kind of channel, the combination of ECCs with an interleaver reduces the burst errors and improves the performance which leads to positive coding gain. In a fast fading channel, coding gain is not much and it remains almost same in different turbulence conditions. The analytical results are supported by simulation study.

A Simple Cooperative Diversity Method Based on Deep-Learning-Aided Relay Selection

Opportunistic relay selection (ORS) has been recognized as a simple but efficient method for mobile nodes to achieve cooperative diversity in slow fading channels. However, the wrong selection of the best relay arising from outdated channel state information (CSI) in fast time-varying channels substantially degrades its performance. With the proliferation of high-mobility applications and the adoption of higher frequency bands in 5G and beyond systems, the problem of outdated CSI will become more serious. Therefore, the design of a novel cooperative method that is applicable to not only slow fading but also fast fading is increasingly of importance. To this end, we develop and analyze a deep-learning-aided cooperative method coined predictive relay selection (PRS) in this article. It can remarkably improve the quality of CSI through fading channel prediction while retaining the simplicity of ORS by selecting a single opportunistic relay so as to avoid the complexity of multi-relay coordination and synchronization. Information-theoretic analysis and numerical results in terms of outage probability and channel capacity reveal that PRS achieves full diversity gain in slow fading wireless environments and substantially outperforms the existing schemes in fast fading channels.