Shaking table test study on performance and functionality of a typical telecommunication room after earthquakes

Large numbers of basic transceiver stations,where the telecommunication room is one of the main components,comprise an important part of the telecommunication system.After earthquakes,considerable economic loss from telecommunication systems is often associated with seismic damage and functional loss of the telecommunication room.However,research related to this has been limited.In this study,shaking table tests were conducted for a full-scale typical telecommunication room,including a light-steel house and the necessary communication and power supply equipment.The tests not only focused on the seismic damage to all the structures but also considered the functions of the communication and power supply of the equipment.The interactions between these facilities and their effects on communication function were also investigated.Compared with the damage to structures,the interruption of the power supply due to earthquakes is a weak link.Finally,the damage indexes,together with their threshold values of different damage states for the communication and power supply equipment,were derived from the test results.The results of this research can contribute to the literature gaps regarding seismic performance studies of telecommunication rooms,and can serve as a valuable reference for future research on its seismic fragility and economic losses evaluation.

Channel Capacity and Power Allocation of MIMO Visible Light Communication System

In this paper,the channel capacity of the multiple-input multiple-output(MIMO)visible light communication(VLC)system is investigated under the peak,average optical and electrical power constraints.Finding the channel capacity of MIMO VLC is shown to be a mixed integer programming problem.To address this open problem,we propose an inexact gradient projection method to find the channel capacity-achieving discrete input distribution and the channel capacity of MIMO VLC.Also we derive both upper and lower bounds of the capacity of MIMO VLC with the closed-form expressions.Furthermore,by considering practical discrete constellation inputs,we develop the optimal power allocation scheme to maximize transmission rate of MIMO VLC system.Simulation results show that more discrete points are needed to achieve the channel capacity as SNR increases.Both the upper and lower bounds of channel capacity are tight at low SNR region.In addition,comparing the equal power allocation,the proposed power allocation scheme can significantly increase the rate for the low-order modulation inputs.

Load Balancing-Based Routing Optimization Mechanism for Power Communication Networks

In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.

Performance Evaluation for Medium Voltage MIMO-OFDM Power Line Communication System

Power line communication(PLC)provides intelligent electrical functions such as power quality measurement,fault surveys,and remote control of electrical network.Most of research works have been done in low voltage(LV)scenario due to the fast development of in-home PLC.The aim of this paper is to evaluate the link-level performance of a medium voltage(MV)MIMO-OFDM communication system based on transmission link under underground power line channel.The MIMO channel is modeled as a modified multipath model in the presence of impulsive noise and background noise.We first perform a measurement on the practical MV MIMO channel parameters for a section of buried cable of 1 km long in Ganzhou city,Jiangxi province,China.Based on the measured channel,we design the frame structure based on an IEEE standard for broadband over power line networks[1]to support MV MIMO-OFDM transmission.According to designed frame structure,we design an encoder and a decoder for a dual binary tail-biting turbo code and optimize some key decoder parameters for low bit error rate performance.Finally,the link-level performance for both spatial multiplexing and spatial diversity are evaluated.Numeral results show that MV MIMO-OFDM is a promising approach to provide both high data rate and link reliability for PLC.

Power Allocation for NOMA in D2D Relay Communications

Non-orthogonal multiple access(NOMA)is considered as one of the key technologies for the fifth generation(5G)wireless communications.The integration of NOMA and device-to-device(D2D)communications has recently attracted wide attention.In this paper,a relaying D2D communications assisted with cooperative relaying systems using NOMA(DRC-NOMA)is considered.We analyze the ergodic sum-rate for the proposed system and then derive the closed-form expressions.In addition,an optimal power allocation strategy maximizing the ergodic sum-rate is proposed based on these analysis results.Numerical results show the good agreement between the results of analysis and Monte Carlo method.The proposed DRC-NOMA has a great improvement of the ergodic sum-rate in the small regime of average channel gain of D2D pair.

Joint Trajectory and Power Optimization for Securing UAV Communications Against Active Eavesdropping

Due to both of jamming and eavesdropping,active eavesdroppers can induce more serious security threats to unmanned aerial vehicle(UAV)-enabled communications.This paper considers a secure UAV communication system including both the downlink(DL)and uplink(UL)transmissions,where the confidential information is transmitted between a UAV and a ground node in the presence of an active eavesdropper.We aim to maximize the average secrecy rates of the DL and UL communications,respectively,by jointly optimizing the UAV trajectory and the UAV/ground node’s transmit power control over a given flight period.Due to the non-convexity of the formulated problems,it is difficult to obtain globally optimal solutions.However,we propose efficient iterative algorithms to obtain high-quality suboptimal solutions by applying the block coordinate descent and successive convex optimization methods.Simulation results show that the joint optimization algorithms can effectively improve the secrecy rate performance for both the DL and UL communications,as compared with other baseline schemes.The proposed schemes can be considered as special cases of UAV-assisted non-orthogonal multiple access(NOMA)networks.

Covert Communication in Integrated High Altitude Platform Station Terrestrial Networks

In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.

Coalitional game based resource allocation in D2D-enabled V2V communication

The joint resource block(RB)allocation and power optimization problem is studied to maximize the sum-rate of the vehicle-to-vehicle(V2V)links in the device-to-device(D2D)-enabled V2V communication system,where one feasible cellular user(FCU)can share its RB with multiple V2V pairs.The problem is first formulated as a nonconvex mixed-integer nonlinear programming(MINLP)problem with constraint of the maximum interference power in the FCU links.Using the game theory,two coalition formation algorithms are proposed to accomplish V2V link partitioning and FCU selection,where the transferable utility functions are introduced to minimize the interference among the V2V links and the FCU links for the optimal RB allocation.The successive convex approximation(SCA)is used to transform the original problem into a convex one and the Lagrangian dual method is further applied to obtain the optimal transmit power of the V2V links.Finally,numerical results demonstrate the efficiency of the proposed resource allocation algorithm in terms of the system sum-rate.

A FAST BIT-LOADING ALGORITHM FOR HIGH SPEED POWER LINE COMMUNICATIONS

Adaptive bit-loading is a key technology in high speed power line communications with the Orthogonal Frequency Division Multiplexing (OFDM) modulation technology. According to the real situation of the transmitting power spectrum limited in high speed power line communications, this paper explored the adaptive bit loading algorithm to maximize transmission bit number when transmitting power spectral density and bit error rate are not exceed upper limit. With the characteristics of the power line channel, first of all, it obtains the optimal bit loading algorithm, and then provides the improved algorithm to reduce the computational complexity. Based on the analysis and simulation, it offers a non-iterative bit allocation algorithm, and finally the simulation shows that this new algorithm can greatly reduce the computational complexity, and the actual bit allocation results close to optimal.

Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond technologies.The random movement of mobile terminals in the indoor environment is a challenge in the VLC system.The model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)algorithm.The optimized optical attocells were examined and compared with previous models.This novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 dB.The bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,respectively.The optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,respectively.As the results of the proposed model are optimal,it is suitable for standard office and room model applications.

Guarding Legal Communication with Smart Jammer:Stackelberg Game Based Power Control Analysis

This paper investigates a power control problem in a jamming system,where a separate smart jammer is deployed to ensure the communication security of the legal user.However,due to power leakage,the smart jammer may incur unintentional interference to legal users.The key is how to suppress illegal communication while limit the negative impact on legal user.A jamming counter measure Stackelberg game is formulated to model the jamming power control dynamic of the system.The smart jammer acts as a leader to sense and interfere illegal communications of the illegal user,while the illegal user acts as a follower.In the game,the impact of uncertain channel information is taken into account.According to whether illegal user considers the uncertain channel information,we investigate two scenarios,namely,illegal user can obtain statistical distribution and accurate information of interference channel gain and its own cost,respectively.This work not only proposes a jamming counter measure iterative algorithm to update parameters,but also gives two solutions to obtain the Stackelberg equilibrium(SE).The power convergence behaviours under two scenarios are analyzed and compared.Additionally,brute force is used to verify the accuracy of the SE value further.

A Joint Power and Bandwidth Allocation Method Based on Deep Reinforcement Learning for V2V Communications in 5G

Vehicular communications have recently attracted great interest due to their potential to improve the intelligence of the transportation system.When maintaining the high reliability and low latency in the vehicle-to-vehicle(V2V)links as well as large capacity in the vehicle-to-infrastructure(V2I)links,it is essential to flexibility allocate the radio resource to satisfy the different requirements in the V2V communication.This paper proposes a new radio resources allocation system for V2V communications based on the proximal strategy optimization method.In this radio resources allocation framework,a vehicle or V2V link that is designed as an agent.And through interacting with the environment,it can learn the optimal policy based on the strategy gradient and make the decision to select the optimal sub-band and the transmitted power level.Because the proposed method can output continuous actions and multi-dimensional actions,it greatly reduces the implementation complexity of large-scale communication scenarios.The simulation results indicate that the allocation method proposed in this paper can meet the latency constraints and the requested capacity of V2V links under the premise of minimizing the interference to vehicle-to-infrastructure communications.

Wireless communication and wireless power transfer system for implantable medical device

Traditional magnetically coupled resonant wireless power transfer technology uses fixed distances between coils for research,to prevent fluctuations in the receiving voltage,and lead to reduce transmission efficiency.This paper proposes a closed-loop control wireless communication wireless power transfer system with a wearable four-coil structure to stabilize the receiving voltage fluctuation caused by changes in the displacement between the coils.Test results show that the system can provide stable receiving voltage,no matter how the distance between the transmitting coil and the receiving coil is changed.When the transmission distance is 20 mm,the power transfer efficiency of the system can reach 18.5%under the open-loop state,and the stimulus parameters such as the stimulation period and pulse width can be adjusted in real time through the personal computer terminal.

DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

It is essential to maximize capacity while satisfying the transmission time delay of unmanned aerial vehicle(UAV)swarm communication system.In order to address this challenge,a dynamic decentralized optimization mechanism is presented for the realization of joint spectrum and power(JSAP)resource allocation based on deep Q-learning networks(DQNs).Each UAV to UAV(U2U)link is regarded as an agent that is capable of identifying the optimal spectrum and power to communicate with one another.The convolutional neural network,target network,and experience replay are adopted while training.The findings of the simulation indicate that the proposed method has the potential to improve both communication capacity and probability of successful data transmission when compared with random centralized assignment and multichannel access methods.

Modeling of OFDM Based Transceiver for Broadband Powerline Communication

In the recent past power line communication has emerged as an attractive choice for high speed data transfer and is looked upon as inexpensive and reliable media suitable for broadband internet access, home and office automation, in-vehicle data communication etc. In this paper we present an architecture for the physical layer of a PLC transceiver based on Orthogonal Frequency Division Multiplexing (OFDM) and the impact on multipath distortion for PLC transmission in terms of bit error rate. Since there is no standard PLC channel model available, a widely accepted multipath channel model is used for simulation purpose. Simulation results as well as FPGA synthesis verify the effectiveness of the proposed architecture for PLC modem design at 110 Mbps data rate.

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

Elliptical Cell Based Beamforming Design with an Improved β-Fairness Power Allocation for HSR Communication Systems

In this paper,a beamforming scheme to improve the coverage in high-speed railway communication systems is investigated.A dedicated coverage model,where the coverage cell is an ellipse rather than the traditional circular or linear,is considered.Based on the elliptical coverage cell,an optimization problem for the beamforming design is formulated to maximize the percentage of railway coverage,subject to the constraints on equal expected designed propagation gain(the gain obtained by a combination of designed beam and propagation channel)on the elliptical curve,i.e.,the expectation of designed propagation gain on the elliptical curve are all equal.Considering that the coverage can be improved by increasing the minimum designed propagation gain on the railway,the problem can be recast to maximizing the equal expected designed propagation gain on the elliptical curve.Subsequently,a beamforming design with an improved β-fairness power allocation,where the optimization problem is formulated to maximize the minimum expected received power over time with the constraints on elliptical cell based beamforming and mobile service amount,is proposed to further improve the coverage.An alternating iteration algorithm is developed to find the optimal beamforming vector and the instantaneous transmit power.Through numerical results,it is found that the beamforming designed on the elliptical curve covers longer railway than beamforming designed on the railway directly,and the coverage of elliptical cell based beamforming can be increased with the eccentricity.In addition,beamforming with the improvedβ-fairness power allocation can further improve the railway coverage and mobile service amount simultaneously.Moreover,it is shown that the larger eccentricity of the ellipse with appropriately chosen BS location,the larger coverage distance.

Wearable Antenna for Power Efficient On-Body and Off-Body Communications

A novel dual-band and diverse radiation pattern antenna is proposed for power efficient on-body and off-body communications intended for various applications in healthcare and sport monitoring. The antenna is dual band at 2.45 GHz (ISM band) with omnidirectional radiation pattern over the body surface to communicate power efficiently with other co-located body worn devices and at 1.9 GHz (PCS band), it has directive radiation pattern towards off the body to communicate from on-body device to off-body devices. The free space and on-body performances of the antenna are investigated by both simulation and experiment. The antenna shows very good on-body radiation efficiency of 58% at 2.45 GHz and 61% at 1.9 GHz. Good on-body gain is noticed at both frequency bands. Results show that the gain of the proposed antenna increases by 4.7% at 2.45 GHz and 3.2% at 1.9 GHz when placed on the body.

Resource Allocation and Power Control Policy for Device-to-Device Communication Using Multi-Agent Reinforcement Learning

Device-to-Device(D2D)communication is a promising technology that can reduce the burden on cellular networks while increasing network capacity.In this paper,we focus on the channel resource allocation and power control to improve the system resource utilization and network throughput.Firstly,we treat each D2D pair as an independent agent.Each agent makes decisions based on the local channel states information observed by itself.The multi-agent Reinforcement Learning(RL)algorithm is proposed for our multi-user system.We assume that the D2D pair do not possess any information on the availability and quality of the resource block to be selected,so the problem is modeled as a stochastic non-cooperative game.Hence,each agent becomes a player and they make decisions together to achieve global optimization.Thereby,the multi-agent Q-learning algorithm based on game theory is established.Secondly,in order to accelerate the convergence rate of multi-agent Q-learning,we consider a power allocation strategy based on Fuzzy C-means(FCM)algorithm.The strategy firstly groups the D2D users by FCM,and treats each group as an agent,and then performs multi-agent Q-learning algorithm to determine the power for each group of D2D users.The simulation results show that the Q-learning algorithm based on multi-agent can improve the throughput of the system.In particular,FCM can greatly speed up the convergence of the multi-agent Q-learning algorithm while improving system throughput.

Power Allocation Strategy for Secret Key Generation Method in Wireless Communications

Secret key generation(SKG)is an emerging technology to secure wireless communication from attackers.Therefore,the SKG at the physical layer is an alternate solution over traditional cryptographic methods due to wireless channels’uncertainty.However,the physical layer secret key generation(PHY-SKG)depends on two fundamental parameters,i.e.,coherence time and power allocation.The coherence time for PHY-SKG is not applicable to secure wireless channels.This is because coherence time is for a certain period of time.Thus,legitimate users generate the secret keys(SKs)with a shorter key length in size.Hence,an attacker can quickly get information about the SKs.Consequently,the attacker can easily get valuable information from authentic users.Therefore,we considered the scheme of power allocation to enhance the secret key generation rate(SKGR)between legitimate users.Hence,we propose an alternative method,i.e.,a power allocation,to improve the SKGR.Our results show 72%higher SKGR in bits/sec by increasing power transmission.In addition,the power transmission is based on two important parameters,i.e.,epsilon and power loss factor,as given in power transmission equations.We found out that a higher value of epsilon impacts power transmission and subsequently impacts the SKGR.The SKGR is approximately 40.7%greater at 250 from 50 mW at epsilon=1.The value of SKGR is reduced to 18.5%at 250 mW when epsilonis 0.5.Furthermore,the transmission power is also measured against the different power loss factor values,i.e.,3.5,3,and 2.5,respectively,at epsilon=0.5.Hence,it is concluded that the value of epsilon and power loss factor impacts power transmission and,consequently,impacts the SKGR.