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A distributed congestion control must be adaptable to varying target communication ranges as cellular V2X (C-V2X) is evolving to support flexible coverage suitable for various service scenarios. This study proposes range-adaptive distributed power control (Ra-DPC) based on deep reinforcement learning (DRL) with the Monte Carlo policy gradient algorithm. A key finding is that the agents learn Ra-DPC more effectively when the cumulative interference power of the subchannels is adopted as the state of the DRL model, rather than the channel busy ratio. The proposed Ra-DPC algorithm performs better in energy efficiency and packet delivery ratio than the existing technologies.

Effective networking over wireless media has become extremely essential today as communication between massive Internet of things (IoT) devices is on an increase, thereby leading to a limited spectrum resource for utilisation. Specifically, for healthcare infrastructure in a remote or critical situation, providing uninterrupted communication between the macro base station and IoT devices or user nodes is imperative. However, owing to their limited spectral capacity, unmanned aerial vehicles (UAVs)-based networks can provide an efficient solution and utilise both licensed and unlicensed bands for communication among users or devices. In this paper, our focus is on cache-enabled cognitive networking for secondary users (SUs) that accredits precise communication delivery for critical healthcare systems that are performed by the cognitive UAV (CUAV). In addition, we develop a caching strategy wherein a CUAV is capable of caching relevant information from high-power (HP) and moderate-power (MP) devices in its local and cloud storage by applying a non-orthogonal multiple-access method. In the downlink scenario, the CUAV proactively transmits the requested HP and MP information to the designated SUs considering this entire model over two states, namely effectual state and interference state, which we can realise by any presence or absence of interference. To maximise this system’s energy efficiency, we formulate an optimisation problem to minimise the transmission power and satisfy the target performance in terms of throughput for SUs. We solve the optimisation issue using the Lagrangian approach and the Karush-Kuhn-Tucker conditions. In all simulations, the energy efficiency during the effectual state renders an average performance of approximately 400% better than that of the interference state.

The integration of unmanned aerial vehicles (UAVs) into spectrum sensing cognitive communication networks can offer many benefits for massive connectivity services in 5G communications and beyond; hence, this work analyses the performance of non-orthogonal multiple access-based cognitive UAV-assisted ultra-reliable and low-latency communications (URLLCs) and massive machine-type communication (mMTC) services. An mMTC service requires better energy efficiency and connection probability, whereas a URLLC service requires minimising the latency. In particular, a cognitive UAV operates as an aerial secondary transmitter to a ground base station by sharing the unlicensed wireless spectrum. To address these issues, we derive the analytical expressions of throughput, energy efficiency, and latency for mMTC/URLLC-UAV device. We also formulate an optimisation problem of energy efficiency maximisation to satisfy the needs of URLLC latency and mMTC throughput and solve it using the Lagrangian method and the Karush-Kuhn-Tucker conditions. The algorithm is presented by jointly optimising the transmission powers of the mMTC and URLLC users. The derived expressions and algorithm are then used to evaluate the performance of the proposed system model. The numerical results show that the proposed algorithm improves the energy efficiency and satisfies the latency requirement of the mMTC/URLLC-UAV device.

The millimeter wave band is becoming popular for mobile broadband usage such as fifth-generation (5G) mobile and mobile satellite services utilizing earth stations in motion (ESIM). According to the 2019 World Radiocommunication Conference (WRC-19), the 5G and ESIM systems will operate in adjacent frequency bands bounded by 27.5 GHz; therefore, the adjacent channel compatibility between ESIM and 5G should be verified. Both, the minimum coupling loss (MCL) and Monte-Carlo (MC) methods are applied to assess the worst and most practical interference effects, respectively, for all types of ESIM including the following: maritime ESIM (M-ESIM), land ESIM (L-ESIM), and aeronautical ESIM (A-ESIM). The distance and guard band between the two systems are indicated by the compatibility conditions. In addition to the conventional interference-to-noise ratio (I/N), the throughput loss of a 5G system is proposed to assess the performance degradation caused by the ESIM interference. Two orthogonal frequency division multiplexing (OFDM) waveforms are proposed to suppress ESIM power leakage into an adjacent channel. A mathematical expression regarding the power spectral density (PSD) and frequency dependent rejection (FDR) is derived for these waveforms, suggesting that the interference can be alleviated. A measured single carrier waveform of a commercial ESIM equipment is used as the benchmark against the proposed OFDM waveforms. The windowed OFDM is able to reduce the guard band by 50-77%. The results obtained for various elevation angles of the ESIM antenna are determined to be applicable to various regions globally.

In this study, a new method is proposed to confirm the possibility of coexistence between the existing satellite services and potential fifth-generation (5G) cellular services in the millimeter-wave band according to the frequency-designation agenda of International Mobile Telecommunications (IMT)-2020 for 5G. To evaluate the accumulated interference power of numerous 5G systems distributed globally at a satellite receiver, we extend the satellite's interference reception area to the entire coverage area, from which only the land area is extracted using the geospatial terrain data of Earth in three dimensions. This enables more accurate interference assessment than conventional methods that only consider the footprint of the satellite's 3-dB beamwidth. We also place the IMT-2020 (5G) systems in the coverage area using the IMT-2020 parameters and modeling documents for the International Telecommunication Union's coexistence study. The propagation loss is modeled considering the clutter loss, building entry loss, and attenuation from atmospheric gases. Subsequently, we analyze the interference power received by a fixed satellite service (FSS) satellite operating in the same band and an Earth exploration satellite service (EESS) passive sensor operating in an adjacent channel. Our simulation shows that the FSS satellite receives up to 7.9dB more interference than that obtained from the existing method. Although this is a substantial difference, we find that the protection criteria is still satisfied. However, all EESS passive sensors do not meet the protection criteria in most scenarios, and additional frequency separation or interference mitigation techniques are required to protect these sensors. The proposed method is also applicable to the analysis of non-terrestrial network interference from airships, balloons, unmanned aerial vehicles, etc.

The fifth-generation (5G) cellular mobile communications look promising with features that can help improving consumer experience and satisfaction. To be able to provide these features, more spectrum is required according to the Shannon-Hartley theorem. Spectrum is, however, a finite and scarce resource, and it can be allocated to a new service only when the spectral coexistence with other incumbents is ensured. New waveforms for 5G that differ from the conventional orthogonal frequency-division multiplexing (OFDM) are required in order to have a superior performance in terms of out-of-band emissions and to be able to utilize the fragmented spectrum in different bands. We developed the analytical models for evaluating the out-of-band emissions of the conventional cyclic prefix (CP)-OFDM as well as its alternatives: windowed OFDM and filtered OFDM, using their signal spectral modeling. The resulting expressions for the power spectral density (PSD) and the frequency-dependent rejection (FDR) involve simple closed-form expressions or easily computable integrals. We applied the expressions to the advanced minimum coupling loss model for assessing the feasibility of the spectral coexistence between the potential 5G systems (with linearized or nonlinear power amplifier) and the incumbent radar systems. The numerical simulation results indicate that both the windowed OFDM and filtered OFDM guarantee the coexistence at the low expense of the spectrum utilization and their coexistence performance can be reduced and reversed with nonlinearity distortion of the power amplifier.

This study investigates the co-existence of fifth generation (5G) mobile communication systems and fixed service (FS) in the 28-GHz band through the utilization and modification of an existing spectrum-sharing method known as the advanced minimum coupling loss (A-MCL) model. The proposed model is based on the power spectral density (PSD) overlap between the 5G orthogonal frequency-division multiplexing (OFDM)-based system and the FS. Spectrum-sharing studies typically need 5G parameters, such as the spectrum emission mask (SEM); however, no such information is available for the new system to achieve accurate results. The proposed model is suitable for spectrum-sharing studies between 5G and other wireless systems without the need for the 5G SEM. Moreover, the existing model is implemented in a new application (i.e., 5G) in the 28-GHz band with different 5G bandwidths. Furthermore, the FS parameters and its frequency allocation are selected based on the Canadian standards to obtain preliminary results for the co-existence between the 5G system and the FS. Results show that co-existence is feasible when certain distances are applied, especially with higher 5G bandwidths (such as 0.5 and 1 GHz) when the 5G system acts as an interferer. In addition, the antenna position plays a major role in reducing the required separation distances between the victim receiver and the interfering transmitter. This model can be used for any future mobile generation such as the sixth generation (6G) mobile system if its PSD is known. This study is concurrent with the worldwide spectrum-sharing studies requested by the International Telecommunication Union for WRC-19.

This paper studies the performance of a half-duplex (HD) two-way relay (TWR) in power line communication (PLC) over a log-normal fading channel with impulsive noise. We consider the two common relaying protocols: amplify-and-forward (AF) and decode-and-forward (DF). For the DF relaying, we apply physical-layer network coding (PNC) and analog-network coding (ANC) to the PLC TWR. We derive analytic expressions for the average sum capacity and the outage probability of the system. The Monte Carlo simulations are provided throughout to validate our analysis. The analytical results show a tight approximation to the simulation results. We compare the one-way relay (OWR) to the TWR and show that the HD spectral efficiency loss incurred by the OWR can be sufficiently mitigated in PLC. However, the outage probability of the TWR is inferior to that of the OWR. To enhance the outage performance of the PLC TWR, we implement a hybrid PLC/wireless (HPW) system, where all nodes are equipped with the PLC and wireless capabilities. Data transmission occurs over the two parallel links. The diversity in the transmission allows the TWR to improve its outage performance in the AF and DF protocols. The impact of the impulsive noise, inherent to the PLC channels, is also highlighted in the simulation results. It is shown that the impulsive noise severely impairs system performance.

The 3rd Generation Partnership Project (3GPP) narrowband Internet of Things (NB-IoT) over non-terrestrial networks (NTN) is the most promising candidate technology supporting 5G massive machine-type communication. Compared to geostationary earth orbit, low earth orbit (LEO) satellite communication has the advantage of low propagation loss, but suffers from high Doppler shift. The 3GPP proposes Doppler shift pre-compensation for each beam region of the satellite. However, user equipment farther from the beam center has significant residual Doppler shifts even after pre-compensation, which degrades link performance. This study proposes residual Doppler shift compensation by adding demodulation reference signal symbols and reducing satellite beam coverage. The block error rate (BLER) data are obtained using link-level simulation with the proposed technique. Since the communication time provided by a single LEO satellite moving fast is short, many LEO satellites are necessary for seamless 24-h communication. Therefore, with the BLER data, we analyze the link budget for actual three-dimensional orbits with a maximum of 162 LEO satellites. We finally investigate the effect of the proposed technique on performance metrics such as the per-day total service time and maximum persistent service time, considering the number of satellites and the satellite spacing. The results show that a more prolonged and continuous communication service is possible with significantly fewer satellites using the proposed technique.

A High Altitude Platform Station (HAPS) can facilitate high-speed data communication over wide areas using high-power line-of-sight communication; however, it can significantly interfere with existing systems. Given spectrum sharing with existing systems, the HAPS transmission power must be adjusted to satisfy the interference requirement for incumbent protection. However, excessive transmission power reduction can lead to severe degradation of the HAPS coverage. To solve this problem, we propose a multi-agent Deep Q-learning (DQL)-based transmission power control algorithm to minimize the outage probability of the HAPS downlink while satisfying the interference requirement of an interfered system. In addition, a double DQL (DDQL) is developed to prevent the potential risk of action-value overestimation from the DQL. With a proper state, reward, and training process, all agents cooperatively learn a power control policy for achieving a near-optimal solution. The proposed DQL power control algorithm performs equal or close to the optimal exhaustive search algorithm for varying positions of the interfered system. The proposed DQL and DDQL power control yields the same performance, which indicates that the actional value overestimation does not adversely affect the quality of the learned policy.

In 2015, the international telecommunication union (ITU) proposed 11 candidate millimeterwave bands between 24 and 86 GHz for the deployment of future fifth mobile generation (5G) broadband systems. Furthermore, the ITU called for spectrum-sharing studies in these bands. Since 5G specifications are not yet defined, the utilization of radio spectrum by 5G mobile systems will assist in identifying these specifications. This paper introduces Malaysia as a case study for the deployment of 5G systems. This includes a discussion of the current status of the Malaysian telecommunication market. Then, we investigate the current services that are already deployed in the proposed bands. Our investigation shows that the fixed (F) service is the most deployed as a primary service in the candidate bands. For this reason, a preliminary spectrum-sharing study is conducted on the basis of a modified 5G spectrum-sharing model to evaluate the feasibility of coexistence between 5G and F services in the 28-GHz band. Our modified methodology can be used for spectrum-sharing studies between 5G and any other services for an initial spectrum-sharing investigation. The results show that the F service will be severely affected by the 5G system transition in the 28-GHz band, especially in the base station (BS)-to-BS sharing scenario. The best band from the perspective of current spectrum allocation for 5G systems is the 45-GHz (i.e., 45.5-47 GHz) band, since it is already reserved for mobile service for primary allocation and not utilized. This paper is carried out concurrently with current worldwide efforts investigating spectrum sharing, as requested by the ITU in agenda item 1.13 for the next world radio conference 2019.

Affinity propagation (AP) clustering with low complexity and high performance is suitable for radio remote head (RRH) clustering for real-time joint transmission in the cloud radio access network. The existing AP algorithms for joint transmission have the limitation of high computational complexities owing to re-sweeping preferences (diagonal components of the similarity matrix) to determine the optimal number of clusters as system parameters such as network topology. To overcome this limitation, we propose a new approach in which preferences are fixed, where the threshold changes in response to the variations in system parameters. In AP clustering, each diagonal value of a final converged matrix is mapped to the position (x,y coordinates) of a corresponding RRH to form two-dimensional image. Furthermore, an environment-adaptive threshold value is determined by adopting Otsu’s method, which uses the gray-scale histogram of the image to make a statistical decision. Additionally, a simple greedy merging algorithm is proposed to resolve the problem of inter-cluster interference owing to the adjacent RRHs selected as exemplars (cluster centers). For a realistic performance assessment, both grid and uniform network topologies are considered, including exterior interference and various transmitting power levels of an RRH. It is demonstrated that with similar normalized execution times, the proposed algorithm provides better spectral and energy efficiencies than those of the existing algorithms.

Although various linear log-distance path loss models have been developed for wireless sensor networks, advanced models are required to more accurately and flexibly represent the path loss for complex environments. This paper proposes a machine learning framework for modeling path loss using a combination of three key techniques: artificial neural network (ANN)-based multi-dimensional regression, Gaussian process-based variance analysis, and principle component analysis (PCA)-aided feature selection. In general, the measured path loss dataset comprises multiple features such as distance, antenna height, etc. First, PCA is adopted to reduce the number of features of the dataset and simplify the learning model accordingly. ANN then learns the path loss structure from the dataset with reduced dimension, and Gaussian process learns the shadowing effect. Path loss data measured in a suburban area in Korea are employed. We observe that the proposed combined path loss and shadowing model is more accurate and flexible compared to the conventional linear path loss plus log-normal shadowing model.

Recently, research into autonomous driving and traffic safety has been drawing a great deal of attention. To realize autonomous driving and solve traffic safety problems, wireless access in vehicular environments (WAVE) technology has been developed, and IEEE 802.11p defines the physical (PHY) layer and medium access control (MAC) layer in the WAVE standard. However, the IEEE 802.11p frame structure, which has low pilot density, makes it difficult to predict the properties of wireless channels in a vehicular environment with high vehicle speeds; thus, the performance of the system is degraded in realistic vehicular environments. The motivation for this paper is to improve the channel estimation and tracking performance without changing the IEEE 802.11p frame structure. Therefore, we propose a channel estimation technique that can perform well over the entire SNR range of values by changing the method of channel estimation accordingly. The proposed scheme selectively uses two channel estimation schemes, each with outstanding performance for either high-SNR or low-SNR signals. To implement this, an adaptation algorithm based on a preamble is proposed. The preamble is a signal known to the transmitter−receiver, so that the receiver can obtain channel estimates without demapping errors, evaluating performance of the channel estimation schemes. Simulation results comparing the proposed method to other schemes demonstrate that the proposed scheme can selectively switch between the two schemes to improve overall performance.