Communication Mode Selection Research Articles

Energy‐efficient machine type communication in HetNets under statistical QoS guarantees

AbstractThere has been an unprecedented rise in the Internet‐of‐Things (IoT) in the past decade. One of the underlying reasons for this exponential growth is that IoT allows for massive machine‐type communication (mMTC), which facilities machine‐to‐machine (M2M) communication with minimal human intervention. However, mMTC devices are characterized by resource and energy limitations, and thus require powerful and efficient power allocation methods that do not jeopardize quality‐of‐service (QoS) performance. In this work, a statistical QoS analysis of M2M communication in heterogeneous wireless networks is performed. We propose a communication mode selection (CMS) scheme that selects an uplink transmission link from the available candidate links based on pathloss criteria. The closed‐form expressions for the Effective Capacity and effective energy efficiency (Effective‐EE) of the M2M communication in the heterogeneous wireless network are derived and verified via simulations. The optimal fixed transmission rate that maximizes the Effective Capacity and Effective‐EE is also analytically analyzed. Furthermore, four scenarios are adopted to study the overall Effective Capacity and Effective‐EE of a two‐hop M2M communication link where the transmitter and access point operate under independent and identical QoS constraints. This article also investigates the impact of circuit power and the efficiency of the power amplifier on the achievable Effective‐EE of the communication link.

Communication mode selection and game theoretic bandwidth sharing model for D2D relay communication

Device-to-device (D2D) communication plays a crucial role in achieving successful implementation of 5G+ and 6G wireless networks. The selection of the communication mode is a vital parameter that enables the activation of a communication link through D2D relays. Consequently, this selection can be considered the fundamental functionality responsible for activating the communication mode of transmission within any device-to-device communication network. This research paper proposes a communication mode selection scheme based on a hexagonal cellular structure. The scheme holds significant potential for application in various wireless transmission schemes. Additionally, the paper investigates the issue of bandwidth sharing in device-to-device networks. In future wireless systems, device-centric approaches will be widely adopted, necessitating a key focus on spectrum sharing. The proposed scheme not only facilitates wireless users in sharing their available spectrum with others but also allows them to receive financial rewards in return. This cooperative sharing approach fosters collaboration among wireless users. Furthermore, the paper compares the performance of two utility functions for the purpose of bandwidth sharing. The Cobb-Douglas model is utilized to present the proposed bandwidth-sharing scheme between two users. Simulation experiments are conducted to determine the percentage of bandwidth shared by the two users under various scenarios, including a case where both users share 50% of the bandwidth. The results indicate that the optimal utility function is achieved when one user shares 10% of the bandwidth while the other user shares 90%.

Time-Division ISAC Enabled Connected Automated Vehicles Cooperation Algorithm Design and Performance Evaluation

To overcome the bottleneck of unreliable environment sensing caused by sensor failure and obstacle blockage, the cooperation among connected automated vehicles (CAVs) is crucial for the reliable and efficient raw sensing data sharing in order to guarantee the driving safety. Empowered by the narrow beamwidth and high data rate abilities, the millimeter wave (mmWave) communication technology can substantially improve the environment sensing ability among multiple CAVs. In this paper, a mmWave enabled CAVs cooperation algorithm is designed based on the proposed time-division integrated sensing and communication (TD-ISAC) system for raw sensing data sharing among CAVs. Considering various computing abilities at vehicle and infrastructure, a closed-form solution to the V2V or V2V/V2I cooperative communication mode selection is theoretically achieved based on response delay analysis to guarantee the timeliness of raw sensing data sharing. And the age of information based system status update algorithm is proposed for the V2V/V2I collaborative communication mode. The feasibility of the proposed TD-ISAC system is verified by simulation and hardware testbed results. Based on simulation results, the proposed communication mode selection algorithm can effectively minimize the response time delay in different conditions. The mmWave enabled TD-ISAC hardware testbed is developed and the position error of target detection can be reduced by 18.5 % using the sensing data fusion from two vehicles, while the communication throughput remains over 2.2 Gbps.

Transmit or Backscatter: Communication Mode Selection for Narrowband IoT Systems

Backscatter communication is an energy-efficient communication technique for the Internet of things (IoT) devices. It enables data transmission by reflecting the incident radio signals. In this paper, we propose a communication mode selection scheme for IoT devices that can communicate using either active transmission or backscattering. In the active transmission mode, the IoT devices can transmit data over narrowband subcarriers using power-domain non-orthogonal multiple access (NOMA). In the backscattering mode, which operates over shorter distance than active transmission, nearby user equipment (UE) devices are used as relays. The UEs receive the backscattered signals from the IoT devices and forward them to the base station. We formulate a connection density maximization problem to select the communication mode used by each IoT device. We determine the IoT device pairing for active transmission mode with NOMA and UE-IoT device association for backscattering mode. The formulated problem is a binary integer programming problem. Although it can be solved optimally, the optimal algorithm incurs exponential computational complexity. Hence, we propose a low-complexity suboptimal algorithm to solve this problem. Results show that our proposed algorithm can enhance the connection density of narrowband IoT systems by up to 64% when compared with using single communication mode.

Energy-Efficient Mode Selection and Resource Allocation for D2D-Enabled Heterogeneous Networks: A Deep Reinforcement Learning Approach

Improving energy efficiency has shown increasing importance in designing future cellular system. In this work, we consider the issue of energy efficiency in D2D-enabled heterogeneous cellular networks. Specifically, communication mode selection and resource allocation are jointly considered with the aim to maximize the energy efficiency in the long term. And an Markov decision process (MDP) problem is formulated, where each user can switch between traditional cellular mode and D2D mode dynamically. We employ deep deterministic policy gradient (DDPG), a model-free deep reinforcement learning algorithm, to solve the MDP problem in continuous state and action space. The architecture of proposed method consists of one actor network and one critic network. The actor network uses deterministic policy gradient scheme to generate deterministic actions for agent directly, and the critic network employs value function based Q networks to evaluate the performance of the actor network. Simulation results show the convergence property of proposed algorithm and the effectiveness in improving the energy efficiency in a D2D-enabled heterogeneous network.

A location-aware power control mechanism for interference mitigation in M2M communications over cellular networks

Machine-to-Machine (M2M) communication is considered as a promising technology in fifth-generation (5G) cellular networks to reduce the power consumption and improve energy efficiency. To achieve these benefits, identification of unknown machine location is crucial for mitigating interference. Therefore, this paper proposes a location-aware communication mode selection based power control mechanism for reducing interference in M2M communications over cellular networks. The proposed mechanism depends on the threshold distance while communicating among M2M pair. Consequently, user equipment (UE) selects the proper communication mode in the proposed mechanism. Resource allocation between the M2M UEs (MUEs) and cellular UEs (CUEs) that share the resources in both orthogonal and non-orthogonal ways are analyzed for different modes. A water filling algorithm and Lagrange decomposition scheme based power optimization process are adopted for allocating the proper optimal transmit power to each UE in the proposed mechanism. Simulation results are compared with the non-orthogonal and orthogonal resource sharing scheme based proposed mechanism which shows that the orthogonal resource sharing scheme provides better system performance in the proposed network.

A Distance Based Communication Mode Selection Mechanism for M2M Communications Over Cellular Networks

The implementation of machine-to-machine (M2M) communications in fifth-generation (5G) cellular networks can facilitate with several benefits like enhancement of bandwidth utilization, accommodating large number of users and decreasing traffic load on evolved node B (eNB). Integration of location information of unknown machine in communication mode selection mechanism is the key feature of this research. In this paper, a distance based communication mode selection mechanism using non-orthogonal resource sharing scheme is adopted in the proposed system model. Under the proposed mechanism, the expressions of throughput and RBs utilization policy are derived, which are the key parameters to evaluate the performance in the proposed network. Depending on the mode selection condition, such as threshold distance and threshold SINR between M2M users and regular cellular users, a UE can automatically choose its communication mode in the network. It is supposed that selection of mode before data transfer can improve the system performance. On the other hand, designing of efficient distance assisted proposed resource blocks (RBs) utilization policy reduces the traffic load on the eNB. Extensive simulations are carried out for evaluating the performance of the proposed mechanisms. The system performance is compared with various changeable parameters, such as throughput, mode selection threshold SINR, threshold distance and RBs. Besides, the proposed mechanism provides better network performance as well as reduces the traffic load in the proposed network.

Research on Key Technologies and Innovative Development of Electronic Communication System Based on Serial Communication

Today, with the rapid development of computer technology, communication between computer and modern energy instrument Xinxing is extremely important. Serial communication is widely used in on-line monitoring of process quantity in industrial enterprises. This paper analyzes the characteristics of this serial communication, and expounds the selection of communication mode for computer business, the connection of interface hardware and the programming of software. Ethernet technology is currently widely used in the industrial field. Because computer serial communication has shortcomings such as short communication distances and low transmission speeds, meanwhile, process quantity signals have many types, large differences in value ranges, and continuous changes. The key technical issues such as long-distance transmission of travelling signals, real-time communication and display of process volume change curves must be properly resolved before a practical online monitoring system can be constructed. Or it has important reference value for personnel engaged in serial communication between computers and Ganneng instruments.

Ocean Surface Drifting Buoy System Based on UAV-Enabled Wireless Powered Relay Network.

We design an ocean surface drifting buoy system based on an unmanned aerial vehicle (UAV)-enabled wireless powered relay network in which the UAV acts as mobile hybrid access point that broadcasts energy to all buoys in the downlink and forwards information from the buoys to a ship signal tower (ST) in the uplink. In order to maximize the resource allocation efficiency of the system, due to the different initial energy reserve of the buoys, a novel communication mode selection strategy is proposed. In the direct transmission mode (DT mode), an energy-sufficient buoy transmits information directly to the ST, and in the relay transmission mode (RT mode), an energy-insufficient buoy relays information to the ST through the UAV. By applying the block coordinate descent and successive convex optimization, a joint UAV trajectory and resource allocation algorithm is proposed to maximize the minimum throughput of the buoys to work in the RT mode. Simulation results show that the proposed algorithm can significantly improve the minimum throughput of the ocean surface drifting buoys.

A Reinforcement Learning Method for Joint Mode Selection and Power Adaptation in the V2V Communication Network in 5G

A 5G network is the key driving factor in the development of vehicle-to-vehicle (V2V) communication technology, and V2V communication in 5G has recently attracted great interest. In the V2V communication network, users can choose different transmission modes and power levels for communication, to guarantee their quality-of-service (QoS), high capacity of vehicle-to-infrastructure (V2I) links and ultra-reliability of V2Vlinks. Aiming atV2V communication mode selection and power adaptation in 5G communication networks, a reinforcement learning (RL) framework based on slow fading parameters and statistical information is proposed. In this paper, our objective is to maximize the total capacity of V2I links while guaranteeing the strict transmission delay and reliability constraints of V2V links. Considering the fast channel variations and the continuous-valued state in a high mobility vehicular environment, we use a multi-agent double deep Q-learning (DDQN) algorithm. Each V2V link is considered as an agent, learning the optimal policy with the updated Q-network by interacting with the environment. Experiments verify the convergence of our algorithm. The simulation results show that the proposed scheme can significantly optimize the total capacity of the V2I links and ensure the latency and reliability requirements of the V2V links.

D2D communication mode selection and resource allocation in 5G wireless networks

In order to improve the efficient allocation of resources in the scenario of densely distributed mobile terminals in 5G networks, this paper proposes a resource allocation algorithm based on D2D communication mode selection. First, group D2D users according to their location distribution. Then, according to the priority order of communication needs, users are assigned modes, and the resource allocation is optimized by comparing the signal-to-noise ratio in orthogonal mode, multiplex mode, and cellular mode The simulation analysis of the throughput in the single-cell multi-user scenario shows that the algorithm can achieve the goal of allocating the best communication mode and resources for users with the maximum throughput output as a criterion.

Intelligent Resource Management Based on Reinforcement Learning for Ultra-Reliable and Low-Latency IoV Communication Networks

Internet of Vehicles (IoV) has attracted much interest recently due to its ubiquitous message exchange and content sharing among smart vehicles with the development of the mobile communication and computation technologies. In this paper, we investigate the policy for jointly communication mode selection, resource block assignment, and power control in device-to-device-enabled vehicle-to-vehicle (V2V) based IoV communication networks with the purpose of guaranteeing the strict ultra-reliable and low latency communications requirements of V2V links while maximizing the sum capacity of vehicle-to-infrastructure links. Considering the unknown environments dynamics as well as the continuous-valued state and action space in IoV networks, we exploit a decentralized actor-critic reinforcement learning model with a new reward function to learn the policy by interacting with the environment. Moreover, we propose an efficient transfer actor-critic learning (ETAC) approach to effectively enhance the learning efficiency and improve the learning convergence speed, in order to support reliable and delay-sensitive vehicular services in IoV networks. Simulation results show that the proposed ETAC approach can effectively reduce the generated interference in IoV networks and ensure the latency and reliability requirements of V2V link, as well as achieve the fast convergence speed and high convergence stability, compared with other existing approaches.

D2D Communication Mode Selection and Resource Optimization Algorithm With Optimal Throughput in 5G Network

Aiming at the problem of device-to-device (D2D) communication mode selection and resource optimization under the joint resource allocation mode in the 5G communication network, a probabilistic integrated resource allocation strategy and a quasi-convex optimization algorithm based on channel probability statistical characteristics are proposed. This strategy and algorithm guarantee D2D. Communication maximizes total system throughput while maximizing access. The analysis results show that this algorithm can significantly optimize the total throughput of the system and reduce the communication interference between the users, which proves the rationality and efficiency of the communication model. The research results obtained in Muwen can provide a theoretical basis for analyzing more complex D2D communication systems and provide a numerical basis for designing heuristic algorithms.

A Distributed Approach to Improving Spectral Efficiency in Uplink Device-to-Device-Enabled Cloud Radio Access Networks

Device-to-device (D2D)-enabled cloud radio access networks (C-RANs) are potential solutions for further improving spectral efficiency (SE) and decreasing latency by allowing direct communication between two users. However, due to the need to acquire global channel state information (CSI) and to execute centralized algorithms, heavy burdens are placed on the fronthaul and the baseband unit (BBU) pool. To alleviate these burdens, a distributed approach to mode selection and resource allocation for potential D2D pairs under pre-determined resource allocation of C-RAN users is proposed, in which pairs of users are endowed with decision-making capabilities. The proposed procedure is divided into three stages: communication mode and subchannel selection, utility value determination, and reinforcement-learning-based strategy update. The core idea is that the D2D pairs self-optimize the mode selection and resource allocation without global CSI under several practical constraints. Simulation results show that enabling D2D can significantly improve SE for C-RANs. Furthermore, the impacts of the fronthaul capacity, the centralized signal processing capability of the BBU pool, and the distance between the D2D transmitter and the remote radio head are demonstrated and analyzed.

Joint mode selection and power allocation for better traffic offloading in D2D communications

Device-to-Device (D2D) technology underlying the cellular network is an attractive solution for future generation network to increase cellular traffic offloading. When two devices are close enough, D2D communication allows a direct communication between them without the mediation of the cellular base station. However, since D2D communication shares the same uplink cellular network radio resource, D2D communication mode selection remains challenging to limit the mutual interference between D2D and cellular links. In this paper, a new D2D mode selection scheme based on a new criterion is proposed aiming at maximizing the cellular traffic offload while respecting the quality of service of cellular users. More precisely, we introduce a noise rise parameter which takes into account the cellular link distance, the D2D link distance, and user’s required throughput. The D2D links are admitted under the constraint of a certain noise rise threshold. To further enhance the achieved throughput of D2D users while respecting the overall interference level in the network, a new power control algorithm is also proposed. Simulation results show that our proposed mode selection scheme provides a tradeoff between traffic offloading and the overall radio capacity in the network. They also prove that the D2D communication mode is more attractive at the cell edge and when D2D users are close enough to each other. In addition, we show the effectiveness of our proposed power control scheme as compared to both static and Rate-Adaptive Water Filling power allocation schemes.

QoS-aware interference management for vehicular D2D relay networks

Vehicular network communication technology is currently attracting a considerable amount of attention. We consider a scenario in which vehicular communication nodes share the same spectrum resources and generate interference with other nodes. Compared with traditional interference-avoiding vehicular communications, this paper aims to increase the number of accessed communication links under the premise of satisfying the required QoS. In our research, communication nodes have opportunities to select relay nodes to both help improve their data transmissions and reduce their transmit power in order to decrease interference with other links while still satisfying their QoS requirements. Based on these objectives, we propose an innovative interference management method that considers link selection, power adaption, and communication mode selection simultaneously to maximize the number of communication links with the lowest power cost. Compared with traditional link-selection and power-adaption interference management schemes, the proposed scheme improves QoS satisfaction with high energy efficiency. Simulation results demonstrate both the efficiency and the effectiveness of the proposed scheme.

Resource allocation, interference management, and mode selection in device‐to‐device communication: A survey

AbstractFor us to meet the demands of fifth generation technologies, device‐to‐device (D2D) communication is foreseen to be an important part of fifth generation networks. Device‐to‐device communication brings significant improvement in user's throughput, battery life, communication delay, and resource usage. Device‐to‐device links share the same resource with the cellular links that results in interference between cellular users and D2D user equipments. This interference can be managed by suitable resource allocation algorithms. The selection of D2D or cellular communication mode is also a hot research issue. Many research works are available in literature on the aforementioned issues regarding D2D communication, but there is no survey available in the literature. To facilitate the researchers, we present a detailed and systematic survey on resource allocation, interference management, and mode selection in D2D communication in this paper. Initially, the taxonomy based overview of D2D communication is provided, and the classification of the works is outlined. Then, the works regarding mode selection are reviewed in detail. Furthermore, interference management schemes to handle the interference caused by the underlying nature are also surveyed. Then, the available literature on resource allocation schemes in D2D perspective are presented. Finally, some open research problems are identified that deserve further research.

User Cooperation in Wireless Powered Communication Networks With a Pricing Mechanism

This paper considers user cooperation and a pricing mechanism in a wireless-powered communication network (WPCN) in which two users harvest energy from a dedicated hybrid access point (H-AP), which has a constant power supply and acts as a power station during a downlink (DL). They also independently transmit their information to the H-AP [which acts as an information receiving station during an uplink (UL)] using the individually harvested energy. Based on the “doubly near-far” problem, this paper proposes a cooperative scheme among users in the WPCN. Compared with the source user (SU), the channel conditions for a helping user (HU), which is closer to the H-AP, is usually better for DL energy harvesting and for transmitting UL information. Thus, the HU can use its harvested energy to forward the SU’s information to the H-AP. Furthermore, energy is usually scarce for each user in a WPCN; therefore, the HU is under no obligation to accept the SU’s cooperative request and can choose to act selfishly to conserve resources. This paper presents a new pricing strategy to motivate the HU to sell its excess energy to help an SU complete a UL information transfer. Two transmission protocols are investigated: in the ideal case, the energy expenditure of the SU equals the energy used by the HU to relay information; in the normal case, the HU seeks additional profit. This paper formulates the SU’s expenditures and relay data in the ideal case as an optimization problem. An investigation of relay placement and the SU communication mode selection problem are also discussed. The numerical results show that the proposed pricing strategy can significantly reduce the expected costs to the SU and improve the reliability of user UL communications in a WPCN.

Communication Mode Selection and Pricing Mechanism for Relaying Based Device-to-Device Communications

Communication Mode Selection and Pricing Mechanism for Relaying Based Device-to-Device Communications

Design of LED Display System for Robot Expression

The real reproduction of the robot expression affects not only how well the robot can mimic mankind, but also whether the robot can be accepted or not. In this case, it is necessary to find a display mode that can mimic mankind. An improved new method, namely advanced led display mode is proposed in this paper. The realization process of the led display system is as follows: A robot expression to be displayed is first chosen, then the expression data is sent to microcontroller through the serial port communication technology, and finally the display of the corresponding expression on the led screen is controlled by the microcontroller by serial port interrupt mode. The design of the led display system is proposed for robot expression, including the selection of communication mode, control mode, scanning mode, and expression display.