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Unmanned Aerial Vehicles (UAVs) have attacted much attention in the field of wireless communication due to its agility and altitude. UAVs can be used as low-altitude aerial base stations (UAV-BSs) to provide communication services for ground devices (GDs) in various scenarios, such as emergency communication and traffic offloading in hotspots. However, due to the limited communication ranges and high prices of commercial UAV-BSs, covering a target area all the time with sufficient UAVs is quite challenging, especially under dynamic environment. We need to design the trajectory of the UAV-BSs to optimize system performance. Most existing works focus on the energy-efficient coverage and throughput maximization but ignore the fairness of communication service, especially the fairness at user-level. Besides, reinforcement learning is suitable for solving decision problems in dynamic environments. However, most existing works use centralized deep reinforcement learning (DRL) approaches. Due to the scalability and low time complexity, a distributed DRL approach is more suitable for multiple UAV-BSs communication system in dynamic environment. Unlike previous works, we characterize the fairness at user-level based on proportional fairness scheduling and formulate a weighted-throughput maximization problem via designing UAV-BSs’ trajectory. Then we model the dynamic deploymentproblem of UAV-BSs as a Markov game and propose a multi-agent deep reinforcement learning-based distributed UAV-BSs control approach named MAUC. MAUC approach adopts the framework of centralized training with distributed execution. Simulation results show that the MAUC can improve fairness of communication service by sacrificing a small amount of throughput. [ABSTRACT FROM AUTHOR]

With the remarkable advances in wireless communications and mobile electronic technologies, traveling users have been demanding continuous and seamless Internet access to enjoy multimedia services such as video streaming, voice over IP, online gaming, and so on, through handheld smart devices. Providing ubiquitous wireless connectivity to mobile users is indispensable to support continuous online services when vehicles move across various kinds of access networks. However, the high vehicle velocity and complex user mobility in the urban environment impose great challenges on designing an efficient mobility management scheme. In this article, we study the packet loss issue in IP mobility support for vehicular networks. We first give detailed descriptions of some major mobility management solutions. Then, we analyze user mobility models in the urban environment and identify the packet loss issue when traveling users roam across various access networks. By flexibly utilizing tunneling and buffering technologies, we correspondingly design a comprehensive solution to eliminate packet loss in each handover scenario of the urban environment. Finally, performance comparisons between the proposed scheme and related proposals have been conducted, which demonstrate a noteworthy potential of the presented scheme in eliminating packet loss and improving handover performance in urban vehicular communications. [ABSTRACT FROM AUTHOR]

This paper proposes a new method for reducing the peak-to-average power ratio of the single-carrier frequency-division multiple access system. The method is an integration of the tone injection (TI) and tone reservation (TR) techniques. A recommended method that uses TI to improve TR's low data transmission rate problem that is caused by the reservation of subcarriers. Additionally, to reduce the massive amount of computation required by the combined needs of TI and TR, an iterative flipping algorithm was adopted for this purpose. Simulation results indicate that the proposed method is not only capable of effectively improving the peak-to-average power ratio-reduction efficiency of the single-carrier frequency-division multiple access system but it can also improve the data transmission rate of the conventional TR technique. [ABSTRACT FROM AUTHOR]

A space and terrestrial integrated network (STIN) converges satellite communication networks, mobile wireless networking, and the Internet, has greatly extended the scope of cyberspace. The STIN is composed of diverse network elements and supports various access technologies, and the coordinations in the hybrid networks can better support complex and changeable communication tasks. Furthermore, the STIN takes advantage of the merits of low delay and large bandwidth in terrestrial networks, and achieves global coverage without the limitation of geographic conditions, which can support positioning and navigation, emergency relief, space exploration, and so on. However, the research on STIN is still confronted with some fundamental challenges including time-varying network topology, high satellite mobility, large end-to-end delay, scalability, and so on. In this article, we present a composite architecture that integrates space and terrestrial network components for providing anytime anywhere communications by utilizing the software defined networking and mobile edge computing paradigms, which not only facilitates the network management and increases network flexibility, but also provides improved quality of service for global multimedia services. Additionally, we identify a number of challenging issues associated with the proposed STIN architecture, including mobility management, resource management, routing, traffic steering, security, and so on, a [ABSTRACT FROM AUTHOR]

A new formulation of the fundamental load impedance circuit in the z-plane is employed to study transformers. The design employs prototypes of transfer function, parametric modelling techniques, and optimisation methods; a model describing multisection transmission-line transformers is proposed to match load impedance for use in wireless and mobile communication applications. Configuration of the transformer consists of multisection serial transmission lines. This transformer was designed on a PCB FR4 substrate featuring a permittivity of 4.4, a loss tangent of 0.0245, and a thickness of 1.6 mm. Microstrip line circuits were fabricated to verify the feasibility of the technique. The simulation and measurement results show that real and complex load impedances can be matched simultaneously at three different frequency bands. The characteristic impedance values of the transmission lines synthesising the transformers were adjusted according to the autoregressive process by using optimisation algorithms. The experimental results are in agreement with theoretical values. [ABSTRACT FROM AUTHOR]

SUMMARY Orthogonal frequency division multiplexing (OFDM) is a popular transmission technique in wireless communication. Although already widely addressed in many studies, OFDM still has flaws, one of which is the occurrence of high peak-to-average power ratio (PAPR) in the transmission signal. The partial transmit sequence (PTS) technique is one method adopted to reduce high PAPR in OFDM systems. However, as PTS utilizes phase factors to generate multiple candidate signals, large amounts of calculation and time are required to search the candidate signal with the minimal PAPR, which will then be adopted as the final transmission signal. This paper proposes a novel PAPR reduction method, which can be applied in OFDM systems with M-ary phase-shift keying modulation. It not only requires less computation but also possesses error correction capabilities. More precisely, the proposed method is to divide a block-coded modulation code into the direct sum of a correcting subcode for encoding information bits and a scrambling subcode for generating phase factors. Our proposed method is a suboptimal technique with low computation, because it uses a genetic algorithm with a partheno-crossover operator as the transmitted signal selection mechanism. Simulation results show our proposed method has better PAPR performance than the GA-PTS scheme. Based on the simulation results in Figures 5 and 6, it is evident that our proposed method can be employed in any OFDM system by using M-PSK modulation.Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A multiband coplanar waveguide-fed slot antenna design is proposed for use in wireless and mobile communication applications. This antenna was designed on a single-layer printed circuit board FR4 substrate featuring a permittivity εr = 4.4, a loss tangent tan δ = 0.0245 and a thickness of h = 1.6 mm. The antenna consists of a T-shaped signal strip and a U-shaped conducting strip placed on the upper side of the T-shaped signal strip. After simply tuning the slot parameters of the ground plane, the proposed antenna can be used in the following operations: wireless local area networks at 2.4/5.2/5.8 GHz, worldwide interoperability for microwave access at 2.5/3.5/5.5 GHz and wideband code division multiple access at 1.92-2.17 GHz. The -10 dB bandwidth measured for the proposed antennas was 109.2% (1.85-6.3 GHz). The bandwidth was enhanced by choosing suitable combinations of the upper and lower ground slots. The geometrical parameters were examined to optimise the performance of the proposed antenna. The results of the return loss, far-field H- and E-planes radiation patterns, gain and radiation efficiency of the proposed antenna are presented and discussed herein. The antenna size of the radiation area and the ground plane was 50 × 50 mm2. Detailed simulations and experiments were conducted to optimise broadband operations, and the measured results concurred with the simulated results. [ABSTRACT FROM AUTHOR]

A dual-band bow-tie-shaped CPW-fed slot antenna design for wireless communication applications is proposed. The antenna consists of a signal strip, two conducting strips and bow-tie- shaped slots. With simple tuning geometrical parameters, the proposed antenna is suitable for WLAN 2.4/5.2/5.8 GHz bands. This antenna is designed on a single-layer PCB FR4 substrate with permittivity ∈r = 4.4, loss tangent tan δ = 0.0245 and thickness h = 1.6 mm. The antenna size of the radiating area and ground plane is 60 x 45 mm². The measured results show a positive agreement with the simulated results. [ABSTRACT FROM AUTHOR]

To provide a comprehensive network access service to wireless users, a network operator may operate different types of wireless networks (such as GPRS, Wi-Fi, HSDPA, UMTS, WiMAX and 3GPP LTE) simultaneously to become a heterogeneous wireless network operator, such as Vodafone and T-Mobile. With convenience of accessing wireless networks, ubiquitous services would stimulate the bandwidth expenditure in the network backbone. Lots of various demanded traffic from heterogeneous access networks may converge toward Internet through the common backbone in the operator. Efficiently utilizing the common backbone can offer a better quality of service to users and maximize the revenues for the operator. To our best knowledge, few studies had ever been made in such a contemporary wireless network environment in the past. In this study, we propose solutions to efficiently allocate the bandwidth for user requests and fully utilize the unused bandwidth in the network backbone owned by the heterogeneous wireless network operator. Our simulation results show that our scheme can increase the utilization of the backbone bandwidth, shorten the request completion time for users and generate more revenue for the operator. [ABSTRACT FROM AUTHOR]

As a key candidate technique for fifth-generation (5G) mobile communication systems, non-orthogonal multiple access (NOMA) has attracted considerable attention in the field of wireless communication. Successive interference cancellation (SIC) is the main NOMA detection method applied at receivers for both uplink and downlink NOMA transmissions. However, SIC is limited by the receiver complex and error propagation problems. Toward this end, we explore a high-performance, high-efficiency tool—deep learning (DL). In this paper, we propose a learning method that automatically analyzes the channel state information (CSI) of the communication system and detects the original transmit sequences. In contrast to existing SIC schemes, which must search for the optimal order of the channel gain and remove the signal with higher power allocation factor while detecting a signal with a lower power allocation factor, the proposed deep learning method can combine the channel estimation process with recovery of the desired signal suffering from channel distortion and multiuser signal superposition. Extensive performance simulations were conducted for the proposed MIMO-NOMA-DL system, and the results were compared with those of the conventional SIC method. According to our simulation results, the deep learning method can successfully address channel impairment and achieve good detection performance. In contrast to implementing well-designed detection algorithms, MIMO-NOMA-DL searches for the optimal solution via a neural network (NN). Consequently, deep learning is a powerful and effective tool for NOMA signal detection. [ABSTRACT FROM AUTHOR]