High frequency (HF) communication, commonly covering frequency range between 3 and 30 MHz, is an important wireless communication paradigm to offer over-the-horizon or even global communications with ranges up to thousands of kilometers via skywave propagation with ionospheric refraction. It has widespread applications in fields such as emergency communications in disaster areas, remote communications with aircrafts or ships and non-light-of-the-sight military operations. This tutorial article overviews the history of HF communication, demystifies the recent advances, and provides a preview of the next few years, which the authors believe will see fruitful outputs towards wideband, intelligent and integrated HF communications. Specifically, we first present brief preliminaries on the unique features of HF communications to facilitate general readers in the communication community. Then, we provide a historical review to show the technical evolution on the three generations of HF communication systems. Further, we highlight the key challenges and research directions. We hope that this article will stimulate more interests in addressing the technical challenges on the research and development of future HF radio communication systems.

As the earliest invented and utilized communication approach, shortwave, known as high frequency (HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in efficient manner becomes one of the key challenges in HF communication. Spectrum prediction infers the future spectrum status from history spectrum data by exploring the inherent correlations and regularities. The investigation of HF electromagnetic environment data reveals the correlations and predictability of HF frequency band in both time and frequency domain. To solve this problem, we develop a Spectrum Prediction-based Frequency Band Pre-selection (SP-FBP) for HF communications. The pre-selection of HF frequency band mainly incorporated in prediction of HF spectrum occupancy and prediction of HF usable frequency, which provide the frequency band ranking of spectrum occupancy and alternative frequency for spectrum sensing, respectively. Performance evaluation via real-world HF spectrum data shows that SP-FBP significantly improves the efficiency of finding quality frequency in HF communications.

High frequency (HF) communication is widely spread due to some merits like easy deployment and wide communication coverage. Spectrum prediction is a promising technique to facilitate the working frequency selection and enhance the function of automatic link establishment. Most of the existing spectrum prediction algorithms focus on predicting spectrum values in a slot-by-slot manner and therefore are lack of timeliness. Deep learning based spectrum prediction is developed in this paper by simultaneously predicting multi-slot ahead states of multiple spectrum points within a period of time. Specifically, we first employ supervised learning and construct samples depending on long-term and short-term HF spectrum data. Then, advanced residual units are introduced to build multiple residual network modules to respectively capture characteristics in these data with diverse time scales. Further, convolution neural network fuses the outputs of residual network modules above for temporal-spectral prediction, which is combined with residual network modules to construct the deep temporal-spectral residual network. Experiments have demonstrated that the approach proposed in this paper has a significant advantage over the benchmark schemes.

Channelization typically realized by digital filter banks is an important topic in high frequency (HF) communication and software defined radios (SDR) areas. Channelization has a rigorous requirement for the characteristic of frequency response, e.g., steep transitional band and sharp decay. To address this issue, we investigated the feasibility and implementation of applying fast filter bank (FFB) in channelization in this paper. We analyzed the butterfly structure of FFB similar with fast Fourier transform (FFT), in which prototype sub-filters are cascaded to achieve a low complexity. Hence, it is suitable for designing filter bank with steep transitional band and sharp decay in stop-band. Moreover, we designed a pipelined structure of FFB to achieve a balance between area and performance. Design example shows that FFB has lower computational complexity compared with the other filter banks.

High frequency sky wave communication suffers from poor performance including poor link quality and low link success rate. To enhance performance, diversity technology is proposed in the high frequency communication network (HFCN) in this paper. First, we present the benefits and the challenges by introducing diversity technology into the existing HFCN. Secondly, to exploit the benefits fully and overcome the challenges, we propose a system structure suitable for deploying diversity technology in HFCN in large scale, based on the cloud radio access network and software defined network. Moreover, we present a general structure for the real-time updating frequency management system that plays a more important role especially when resource consuming (e.g., frequency) diversity technology is deployed. Thirdly, we investigate the key techniques enabling diversity technology deployment. Finally, we point out the future research directions to help the HFCN with diversity work more efficiently and intelligently.

This paper investigates the channel diversity problem in high frequency (HF) communication systems. Due to the limited HF spectrum resources, a HF communication system with shared channels is considered, where each user equipment (UE) has individual communication demand. In order to maximize the communication probability of the whole system, a matching-potential game framework is designed. In detail, the channel diversity problem is decomposed into two sub-problems. One is channel-transmitter matching problem, which can be formulated as a many-to-one matching game. The other is the transmitter allocation problem which decides the transmission object that each transmitter communicates with under channel-transmitter matching result, and this sub-problem can be modeled as a potential game. A multiple round stable matching algorithm (MRSMA) is proposed, which obtains a stable matching result for the first sub-problem, and a distributed BR-based transmitter allocation algorithm (DBRTAA) is designed to reach Nash Equilibrium (NE) of the second sub-problem. Simulation results verify the effectiveness and superiority of the proposed method.

The high-frequency(HF) communication is one of essential communication methods for military and emergency application. However, the selection of communication frequency channel is always a difficult problem as the crowded spectrum, the time-varying channels, and the malicious intelligent jamming. The existing frequency hopping, automatic link establishment and some new anti-jamming technologies can not completely solve the above problems. In this article, we adopt deep reinforcement learning to solve this intractable challenge. First, the combination of the spectrum state and the channel gain state is defined as the complex environmental state, and the Markov characteristic of defined state is analyzed and proved. Then, considering that the spectrum state and channel gain state are heterogeneous information, a new deep Q network (DQN) framework is designed, which contains multiple sub-networks to process different kinds of information. Finally, aiming to improve the learning speed and efficiency, the optimization targets of corresponding sub-networks are reasonably designed, and a heterogeneous information fusion deep reinforcement learning (HIF-DRL) algorithm is designed for the specific frequency selection. Simulation results show that the proposed algorithm performs well in channel prediction, jamming avoidance and frequency channel selection.

A multiple-access networking scheme based on the new dynamic spectrum anti-jamming system is proposed in this paper. The network consists of a center node and multiple user nodes. The center node detects spectrum holes in the operation band periodically according to the user performance target. Detected spectrum holes are allocated to users who request communication. Throughput of this networking scheme is analyzed over a high-frequency (HF) interference channel. The effect of error correction coding and spectrum hole information transmission error is discussed. Throughput of this scheme and conventional frequency-hopping multiple-access (FHMA) scheme are compared. Results show that user performance increase leads to throughput decrease, which can be offset by error correction coding. If spectrum hole information transmission is in error, the throughput is not affected much as long as the bit error rate is below 10-2. Furthermore, throughput of this scheme is obviously superior to the throughput of FHMA scheme.

In underground mines, visible light communication (VLC) system is a promising method to realize effective communication, which supports communication and illumination at the same time. Therefore, adequate research of underlying physical propagation phenomenon should be carried out to realize VLC system in underground mines. To design VLC system and evaluate its performance, accurate and efficient channel models, including large-scale fading and scattering characteristics, are needed to be established. However, the characteristics of the underlying VLC channels about fading and scattering have not been sufficiently investigated yet. In this paper, a path loss channel model, based on the recursive model, is proposed precisely. Its path loss exponent is determined by three different trajectories, which is studied in the mining roadway and working face environment. Besides, the shadowing effect for VLC has been modelled by a Bimodal Gaussian distribution in underground mines. Considering the number of transmitters in line-of-sight (LoS) as well as non-line-of-sight (NLoS) scenarios, our simulation illustrates the fact that, as the curve fitting technique is employed, the path loss displays a linear behavior in log-domain. The path loss expression is derived, it is related to the distance. Finally, root mean square (RMS) delay spread and Mie scattering in underground mines are analyzed.

How to achieve transmissions in an energy-efficient way in multi-hop decode and forward (DF) relay cognitive radio sensor networks (CRSNs) is important since sensor nodes in CRSNs are usually battery powered. This paper aims to maximize energy efficiency (EE) by joint optimizing sensing time and power allocation in multi-channels & multi-hops DF relay CRSNs under constraints on outage probability and sensing performance. First, we design a channel selection scheme for sensing according to the available probabilities of multi channels. Second, we analyze the expected throughput and energy consumption and formulate the EE problem as a concave/concave fractional program. Third, coordinate ascent and Charnes-Cooper Transformation (CCT) methods are used to transform the nonlinear fractional problem into an equivalent concave problem. Subsequently, the closed form of outage probability is derived and the convergence rate of the iterative algorithm is analyzed. Finally, simulation results show that the proposed scheme can achieve effective EE.

A radio wave driven by Orbital angular momentum (OAM) is called a vortex radio and has a helical wavefront. The differential helical wavefronts of several vortex radios are closely related to their topological charges or mode numbers. In physics, two or more radio waves with different mode numbers are orthogonal to their azimuth angles. With the development of radio communication technologies, some researchers have been exploring the OAM-based multi-mode multiplexing (multi-OAM-mode multiplexing) technologies in order to enhance the channel spectrum efficiency (SE) of a radio communication system by using the orthogonal properties of vortex radios. After reviewing the reported researches of OAM-based radio communication, we find that some breakthroughs have been made in the combination of OAM and traditional Multi-Input-Multi-Output (MIMO). However, the existing technology is not sufficient to support OAM-based MIMO system to achieve maximum the channel SE. To maximize the spectrum efficiency of OAM-based MIMO system, we present a reused multi-OAM-mode multiplexing vortex radio (RMMVR) MIMO system, which is based on fractal uniform circular arrays (UCAs). The scheme described in this study can effectively combine multi-OAM-mode multiplexing with MIMO spatial multiplexing. First, we present the generation of RMMVR MIMO signals. Second, under line-of-sight (LOS) propagation conditions, we derive the channels of the RMMVR MIMO system. Third, we separate the RMMVR MIMO signals using an orthogonal separation method based on full azimuth sampling. Finally, we introduce the method for calculating the channel capacity of the RMMVR MIMO system. Theoretical analysis shows that the scheme proposed in this study is feasible. Moreover, the simulation results show that spatial and mode diversity are obtained by exploiting fractal UCAs. However, to enhance the channel SE of RMMVR MIMO system, an interference cancellation method needs to be introduced for zero-mode vortex radios, and some methods of multi-OAM-mode beams convergence and mode power optimization strategy should be introduced in the future.

Energy efficiency (EE) of cellular networks has attracted considerable attention recently. However, EE of relay-assisted cellular networks where the macro base stations (MBSs) are equipped with the multi-antenna has not been thoroughly addressed. This paper considered the downlink transmission of multi-antenna relay-assisted cellular networks, meanwhile, a strategic sleep scheme was used in relay stations (RSs), which dynamically adjusted the RS working mode according to whether the number of users serviced by the relay exceeds a given threshold. A geometric model was built to derive the coverage probability and mean achievable rate from the MBSs to user (UE), the MBS to RS, the RS to UE links and analyze the system EE. It is shown that the energy efficiency of cellular network with strategic sleep RS is slightly higher than that of cellular network with non-sleeping strategy. Furthermore, the MBS equipped with multi-antenna has better impact on energy efficiency and spectral efficiency than the MBS with single antenna.

To improve the bit error rate (BER) performance of multiple input multiple output (MIMO) systems with low complexity, a three-branch transmission scheme employing 8-weighted-type fractional Fourier transform (8-WFRFT) module is proposed. In the proposed scheme, the original signal is first decomposed into eight sub-signals and then merged into three component signals by the same carrier pattern. The three signals have mathematical constraint relations among themselves that can counteract the channel fading. They are simultaneously transmitted via three independent antennas after delay regulating. At the receiver, an inverse 8-WFRFT module is employed to obtain the estimated original signal by processing the received signal. Then, the bit error rate (BER) performance, transmitting power, transmission rate, power spectrum and computational complexity of the proposed scheme are analysed in detail. Numerical results show that the proposed scheme has a superior performance compared to STBC based three-antenna transmission scheme, in terms of BER performance.

Non-orthogonal multiple access (NOMA) is a new access method to achieve high performance gains in terms of capacity and throughput, so it is currently under consideration as one of the candidates for fifth generation (5G) technologies. NOMA utilizes power domain in order to superimpose signals of multiple users in a single transmitted signal. This creates a lot of interference at the receive side. Although the use of successive interference cancellation (SIC) technique reduces the interference, but to further improve the receiver performance, in this paper, we have proposed a joint Walsh-Hadamard transform (WHT) and NOMA approach for achieving better performance gains than the conventional NOMA. WHT is a well-known code used in communication systems and is used as an orthogonal variable spreading factor (OVSF) in communication systems. Application of WHT to NOMA results in low bit error rate (BER) and high throughput performance for both low and high channel gain users. Further, it also reduces peak to average power ratio (PAPR) of the user signal. The results are discussed in terms of comparison between the conventional NOMA and the proposed technique, which shows that it offers high performance gains in terms of low BER at different SNR levels, reduced PAPR, high user throughput performance and better spectral efficiency.

In order to solve the problem of inaccurate synchronization for distributed multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system in both multipath and low signal to noise ratio (SNR) channels, a golay pair aided timing synchronization (GPATS) method is proposed in this paper. A new synchronous training sequence based on the golay pair with guard interval is designed in GPATS method. By utilizing the unique properties of the new training sequence, the different timing point and the inter-transmitter delays (ITD) are obtained at the receiver. Simulation results show that, compared with the traditional synchronization approaches, the proposed algorithm can provide high accuracy in detecting different time offsets caused by the distributed transmitters of the MIMO-OFDM system, especially over multipath and low SNR channels.

The uplink achievable rate of massive multiple-input-multiple-output (MIMO) systems, where the low-resolution analog-to-digital converters (ADCs) are assumed to equip at the base station (BS), is investigated in this paper. We assume that only imperfect channel station information is known at the BS. Then a new MMSE receiver is designed by taking not only the Gaussian noise, but also the channel estimation error and quantizer noise into account. By using the Stieltjes transform of random matrix, we further derive a tight asymptotic equivalent for the uplink achievable rate with proposed MMSE receiver. We present a detailed analysis for the number of BS antennas through the expression of the achievable rates and validate the results using numerical simulations. It is also shown that we can compensate the performance loss due to the low-resolution quantization by increasing the number of antennas at the BS.

This paper proposes a cross-layer design to enhance the location privacy under a coordinated medium access control (MAC) protocol for the Internet of Vehicles (IoV). The channel and pseudonym resources are both essential for transmission efficiency and privacy preservation in the IoV. Nevertheless, the MAC protocol and pseudonym scheme are usually studied separately, in which a new MAC layer semantic linking attack could be carried out by analyzing the vehicles’ transmission patterns even if they change pseudonyms simultaneously. This paper presents a hierarchical architecture named as the software defined Internet of Vehicles (SDIV). Facilitated by the architecture, a MAC layer aware pseudonym (MAP) scheme is proposed to resist the new attack. In the MAP, RSU clouds coordinate vehicles to change their transmission slots and pseudonyms simultaneously in the mix-zones by measuring the privacy level quantitatively. Security analysis and extensive simulations are conducted to show that the scheme provides reliable safety message broadcasting, improves the location privacy and network throughput in the IoV.

With correlating with human perception, quality of experience (QoE) is also an important measurement in evaluation of video quality in addition to quality of service (QoS). A cross-layer scheme based on Lyapunov optimization framework for H.264/AVC video streaming over wireless Ad hoc networks is proposed, with increasing both QoE and QoS performances. Different from existing works, this scheme routes and schedules video packets according to the statuses of the frame buffers at the destination nodes to reduce buffer underflows and to increase video playout continuity. The waiting time of head-of-line packets of data queues are considered in routing and scheduling to reduce the average end-to-end delay of video sessions. Different types of packets are allocated with different priorities according to their generated rates under H.264/AVC. To reduce the computational complexity, a distributed media access control policy and a power control algorithm cooperating with the media access policy are proposed. Simulation results show that, compared with existing schemes, this scheme can improve both the QoS and QoE performances. The average peak signal-to-noise ratio (PSNR) of the received video streams is also increased.

This paper presents a deep neural network (DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.