This page has only limited features, please log in for full access.

Unclaimed
Wenpeng Jing
School of Information and Communication Engineering, Beijing Key Laboratory of Network System Architecture and Convergence, Beijing Laboratory of Advanced Information Networks, Beijing University of Posts and Telecommunications, Beijing, 100876, China

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 18 January 2021 in IEEE Communications Letters
Reads 0
Downloads 0

Unmanned aerial vehicles (UAVs) can be utilized to provide communication services for the areas where the communication is unavailable due to the high mobility, agility and low cost. In this letter, we investigate the energy efficient UAVs deployment and the movement for emergency response in the multi-UAVs enabled wireless communication system. The positions of the UAVs, the users association and the transmit power of the ground users are jointly optimized to maximize the energy efficiency of all ground users. And when one UAV leaves because of the breakdown or the drained battery, how the other UAVs move with the minimum energy cost is also studied. An alternating algorithm based on successive convex approximation (SCA) technique is proposed to solve the formulated optimization problems. Numerical results show the proposed multi-UAVs deployment and movement outperform the benchmarks.

ACS Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Haijun Zhang. Energy-Efficient Multi-UAVs Deployment and Movement for Emergency Response. IEEE Communications Letters 2021, 25, 1625 -1629.

AMA Style

Linpei Li, Xiangming Wen, Zhaoming Lu, Wenpeng Jing, Haijun Zhang. Energy-Efficient Multi-UAVs Deployment and Movement for Emergency Response. IEEE Communications Letters. 2021; 25 (5):1625-1629.

Chicago/Turabian Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Haijun Zhang. 2021. "Energy-Efficient Multi-UAVs Deployment and Movement for Emergency Response." IEEE Communications Letters 25, no. 5: 1625-1629.

Journal article
Published: 24 July 2020 in IEEE Transactions on Vehicular Technology
Reads 0
Downloads 0

Edge-assisted mobile crowdsensing is an emerging paradigm where mobile users collect and share sensing data at the edge of networks. With the abundant on-board resources and large movement patterns of intelligent vehicles, they have become candidates to sense up-to-date and fine-grained information for large areas. The design of vehicle recruitment in edge-assisted mobile crowdsensing is challenging due to the selfishness and the uneven distribution of vehicles, as well as the spatiotemporal constraints of vehicular crowdsensing applications. To deal with these challenges, this paper proposes an incentive-aware vehicle recruitment scheme for edge-assisted mobile crowdsensing. In particular, we first design an incentive mechanism to motivate cooperation among the edge server and the intelligent vehicles, and apply the Nash bargaining theory to obtain the optimal cooperation decision. Furthermore, a practical and efficient scheme is proposed to weigh the contribution of vehicles. Then, we formulate the participant recruitment as an optimization problem, and prove that it is NP-hard. To address this problem, an effective heuristic algorithm with a guaranteed approximation ratio is proposed, by leveraging the property in submodular optimization. Finally, we conduct extensive simulations, based on a real dataset, to validate the superiority of the proposed schemes.

ACS Style

Luning Liu; Xiangming Wen; Luhan Wang; Zhaoming Lu; Wenpeng Jing; Yawen Chen. Incentive-Aware Recruitment of Intelligent Vehicles for Edge-Assisted Mobile Crowdsensing. IEEE Transactions on Vehicular Technology 2020, 69, 12085 -12097.

AMA Style

Luning Liu, Xiangming Wen, Luhan Wang, Zhaoming Lu, Wenpeng Jing, Yawen Chen. Incentive-Aware Recruitment of Intelligent Vehicles for Edge-Assisted Mobile Crowdsensing. IEEE Transactions on Vehicular Technology. 2020; 69 (10):12085-12097.

Chicago/Turabian Style

Luning Liu; Xiangming Wen; Luhan Wang; Zhaoming Lu; Wenpeng Jing; Yawen Chen. 2020. "Incentive-Aware Recruitment of Intelligent Vehicles for Edge-Assisted Mobile Crowdsensing." IEEE Transactions on Vehicular Technology 69, no. 10: 12085-12097.

Journal article
Published: 13 June 2020 in Sensors
Reads 0
Downloads 0

The data volume is exploding due to various newly-developing applications that call for stringent communication requirements towards 5th generation wireless systems. Fortunately, mobile edge computing makes it possible to relieve the heavy computation pressure of ground users and decrease the latency and energy consumption. What is more, the unmanned aerial vehicle has the advantages of agility and easy deployment, which gives the unmanned aerial vehicle enabled mobile edge computing system opportunities to fly towards areas with communication demand, such as hotspot areas. However, the limited endurance time of unmanned aerial vehicle affects the performance of mobile edge computing services, which results in the incomplete mobile edge computing services under the time limit. Consequently, this paper concerns the energy-efficient scheme design of the unmanned aerial vehicle while providing high-quality offloading services for ground users, particularly in the regions where the ground communication infrastructures are overloaded or damaged after natural disasters. Firstly, the model of energy-efficient design of the unmanned aerial vehicle is set up taking the constraints of the energy limitation of the unmanned aerial vehicle, the data causality, and the speed of the unmanned aerial vehicle into account. Subsequently, aiming at maximizing the energy efficiency of the unmanned aerial vehicle in the unmanned aerial vehicle enabled mobile edge computing system, the bits allocation in each time slot and the trajectory of the unmanned aerial vehicle are jointly optimized. Secondly, a successive convex approximation based alternating algorithm is brought forward to deal with the non-convex energy efficiency maximization problem. Finally, it is proved that the proposed energy efficient scheme design of the unmanned aerial vehicle is superior to other benchmark schemes by the simulation results. Besides, how the performance of proposed scheme design change under different parameters is discussed.

ACS Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing. An Energy Efficient Design of Computation Offloading Enabled by UAV. Sensors 2020, 20, 1 .

AMA Style

Linpei Li, Xiangming Wen, Zhaoming Lu, Wenpeng Jing. An Energy Efficient Design of Computation Offloading Enabled by UAV. Sensors. 2020; 20 (12):1.

Chicago/Turabian Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing. 2020. "An Energy Efficient Design of Computation Offloading Enabled by UAV." Sensors 20, no. 12: 1.

Journal article
Published: 19 May 2020 in IEEE Access
Reads 0
Downloads 0

Power consumption and task latency are two crucial issues in edge-cloud computing. This paper mainly aims to promote the use of clean power in geo-distributed data centers (DCs) in a deregulated electricity market where customers are allowed to buy power from multiple suppliers, combined with the guarantee of task latency. To alleviate the conflict between frequent switches of servers and the uncertainty of task arrivals in DCs, this paper proposes a two-timescale framework consisting of the long-term capacity planning of geo-distributed DCs and the real-time task dispatching from edge gateways (EGs) to DCs. First, DCs make long-term plans on the number of active servers aiming at the eco-friendly and delay-aware power cost minimization, which is formulated as problem P. Specifically, we introduce a convex pollution indicator function (PIF) to measure the pollution cost of the various types of powers sold by different suppliers, which can encourage the use of cleaner power and improve power savings. Second, in each sub-slot, each EG separately optimizes its individual mixed strategies of task dispatching to DCs with the knowledge of the planned capacities and the real-time queue backlogs of DCs, where a Lyapunov optimization framework is applied. Finally, we give the corresponding distributed algorithm design. Simulation results reveal that our method can realize the trade-off between the power cost and the delay cost of requests, and improve the clean power usage by up to 50%–60% of the total power usage in DCs. Additionally, comparisons with other schemes show that our approach can provide more stable guarantees of task latency in different situations of workload density, which benefits from the diverse-timescale optimizations of capacities of DCs and task routing from EGs to DCs.

ACS Style

Chunlei Sun; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Michele Zorzi. Eco-Friendly Powering and Delay-Aware Task Scheduling in Geo-Distributed Edge-Cloud System: A Two-Timescale Framework. IEEE Access 2020, 8, 96468 -96486.

AMA Style

Chunlei Sun, Xiangming Wen, Zhaoming Lu, Wenpeng Jing, Michele Zorzi. Eco-Friendly Powering and Delay-Aware Task Scheduling in Geo-Distributed Edge-Cloud System: A Two-Timescale Framework. IEEE Access. 2020; 8 (99):96468-96486.

Chicago/Turabian Style

Chunlei Sun; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Michele Zorzi. 2020. "Eco-Friendly Powering and Delay-Aware Task Scheduling in Geo-Distributed Edge-Cloud System: A Two-Timescale Framework." IEEE Access 8, no. 99: 96468-96486.

Journal article
Published: 29 May 2019 in Sensors
Reads 0
Downloads 0

Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs' cache tends to be small, while mobile users' content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users' data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link.

ACS Style

Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang. Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN. Sensors 2019, 19, 2449 .

AMA Style

Wenpeng Jing, Xiangming Wen, Zhaoming Lu, Haijun Zhang. Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN. Sensors. 2019; 19 (11):2449.

Chicago/Turabian Style

Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang. 2019. "Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN." Sensors 19, no. 11: 2449.

Journal article
Published: 22 May 2019 in IEEE Access
Reads 0
Downloads 0

The mobile edge caching is a promising way to reduce the user-perceived delay and improve the transmission data rates for the wireless networks. However, the cache capacities of base stations (BSs) tend to be limited and users’ interests for the contents are diverse, which makes the content placement decision critical for the network performance optimization. Besides, due to the flexible user-BS association, it is more complicated to optimize the content delivery and placement which are coupled with each other. This paper investigates the content placement and content delivery strategies in the cache-enabled wireless networks. In particular, the effective capacity, which can characterize the end-to-end user-perceived delay and data rates simultaneously, is introduced as user’s utility metric. As the content caching and content delivery operate in different time-scales, they are investigated separately. For the content caching, a content placement problem is formulated, where both users’ different active levels and diverse content preferences are considered. Due to the NP-hard nature, the problem is decomposed into two sub-problems, and an iterative association-aware content placement algorithm is proposed. For the content delivery, the user-BS association problem is formulated, and a cache-aware user-BS association algorithm is designed. The performance of the proposed algorithms is evaluated based on simulations. The numerical results show that the proposed algorithms have a better capability to cope with users’ diverse active levels, and achieve a better performance in terms of effective capacity and fairness level, compared with the existing algorithms.

ACS Style

Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang. User-Centric Delay-Aware Joint Caching and User Association Optimization in Cache-Enabled Wireless Networks. IEEE Access 2019, 7, 74961 -74972.

AMA Style

Wenpeng Jing, Xiangming Wen, Zhaoming Lu, Haijun Zhang. User-Centric Delay-Aware Joint Caching and User Association Optimization in Cache-Enabled Wireless Networks. IEEE Access. 2019; 7 (99):74961-74972.

Chicago/Turabian Style

Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang. 2019. "User-Centric Delay-Aware Joint Caching and User Association Optimization in Cache-Enabled Wireless Networks." IEEE Access 7, no. 99: 74961-74972.

Preprint
Published: 27 November 2018
Reads 0
Downloads 0

The rapid development of renewable energy in the energy Internet is expected to alleviate the increasingly severe power problem in data centers, such as the huge power costs and pollution. This paper focuses on the eco-friendly power cost minimization for geo-distributed data centers supplied by multi-source power, where the geographical scheduling of workload and temporal scheduling of batteries' charging and discharging are both considered. Especially, we innovatively propose the Pollution Index Function to model the pollution of different kinds of power, which can encourage the use of cleaner power and improve power savings. We first formulate the eco-friendly power cost minimization problem as a multi-objective and mixed-integer programming problem, and then simplify it as a single-objective problem with integer constraints. Secondly, we propose a Sequential Convex Programming (SCP) algorithm to find the globally optimal non-integer solution of the simplified problem, which is non-convex, and then propose a low-complexity searching method to seek for the quasi-optimal mixed-integer solution of it. Finally, simulation results reveal that our method can improve the clean energy usage up to 50\%--60\% and achieve power cost savings up to 10\%--30\%, as well as reduce the delay of requests.

ACS Style

Chunlei Sun; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Michele Zorzi. Eco-friendly Power Cost Minimization for Geo-distributed Data Centers Considering Workload Scheduling. 2018, 1 .

AMA Style

Chunlei Sun, Xiangming Wen, Zhaoming Lu, Wenpeng Jing, Michele Zorzi. Eco-friendly Power Cost Minimization for Geo-distributed Data Centers Considering Workload Scheduling. . 2018; ():1.

Chicago/Turabian Style

Chunlei Sun; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Michele Zorzi. 2018. "Eco-friendly Power Cost Minimization for Geo-distributed Data Centers Considering Workload Scheduling." , no. : 1.

Journal article
Published: 15 November 2018 in Sensors
Reads 0
Downloads 0

With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things (IoT). However, due to the characteristics of massive connections, access collisions in the MAC layer lead to high power consumption for both sensor devices and UAVs, and low efficiency for the data collection. In this paper, a dynamic speed control algorithm for UAVs (DSC-UAV) is proposed to maximize the data collection efficiency, while alleviating the access congestion for the UAV-based base stations. With a cellular network considered for support of the communication between sensor devices and drones, the connection establishment process was analyzed and modeled in detail. In addition, the data collection efficiency is also defined and derived. Based on the analytical models, optimal speed under different sensor device densities is obtained and verified. UAVs can dynamically adjust the speed according to the sensor device density under their coverages to keep high data collection efficiency. Finally, simulation results are also conducted to verify the accuracy of the proposed analytical models and show that the DSC-UAV outperforms others with the highest data collection efficiency, while maintaining a high successful access probability, low average access delay, low block probability, and low collision probability.

ACS Style

Qi Pan; Xiangming Wen; Zhaoming Lu; Linpei Li; Wenpeng Jing. Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things. Sensors 2018, 18, 3951 .

AMA Style

Qi Pan, Xiangming Wen, Zhaoming Lu, Linpei Li, Wenpeng Jing. Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things. Sensors. 2018; 18 (11):3951.

Chicago/Turabian Style

Qi Pan; Xiangming Wen; Zhaoming Lu; Linpei Li; Wenpeng Jing. 2018. "Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things." Sensors 18, no. 11: 3951.

Conference paper
Published: 01 May 2018 in 2018 IEEE International Conference on Energy Internet (ICEI)
Reads 0
Downloads 0

Energy Internet (EI) is regarded as a promising method to solve the energy shortage and improve the efficiency of renewable energy. It demands frequent exchanges of data flow and energy flow, which puts forward strict requests for data veracity and availability. As a result, a reliable and robust data network is critical to realize the promises of EI. This paper introduces the fog nodes with computing ability to enable erasure coding based fault-tolerant techniques so that the data availability can be guaranteed. However, the distributed and irregular deployment of EI nodes have brought many challenges to maximum distance separable code (MDS) based fault-tolerant schemes. As a result, this paper investigates the design of encoding parameters and clustering mechanism to adjust the flexible situations. And then, we propose a novel fault-tolerant mechanism based on MDS and dynamic clustering to improve the data availability. Numerical simulation results show our scheme works better than the backup and traditional MDS based schemes with determined cluster size.

ACS Style

Xin Chen; Xiangming Wen; Luhan Wang; Wenpeng Jing. A Fault-Tolerant Data Acquisition Scheme with MDS and Dynamic Clustering in Energy Internet. 2018 IEEE International Conference on Energy Internet (ICEI) 2018, 175 -180.

AMA Style

Xin Chen, Xiangming Wen, Luhan Wang, Wenpeng Jing. A Fault-Tolerant Data Acquisition Scheme with MDS and Dynamic Clustering in Energy Internet. 2018 IEEE International Conference on Energy Internet (ICEI). 2018; ():175-180.

Chicago/Turabian Style

Xin Chen; Xiangming Wen; Luhan Wang; Wenpeng Jing. 2018. "A Fault-Tolerant Data Acquisition Scheme with MDS and Dynamic Clustering in Energy Internet." 2018 IEEE International Conference on Energy Internet (ICEI) , no. : 175-180.

Conference paper
Published: 01 April 2018 in 2018 IEEE Wireless Communications and Networking Conference (WCNC)
Reads 0
Downloads 0

To meet the dramatically increasing traffic demand, licensed-assisted access (LAA) has been proposed for long-term evolution (LTE) systems to operate on the unlicensed spectrum. However, it is a huge challenge to achieve fair and efficient coexistence between LAA and Wi-Fi on the same band. In this paper, we devise a novel channel access approach for LAA eNBs to improve system throughput and achieve fair coexistence with Wi-Fi nodes. Specifically, Carrier Sense Multiple Access with Enhanced Collision Avoidance (CSMA/ECA), which is able to reach and maintain collision-free operation by deterministic backoff (DB) after successful transmissions, is introduced to the listen-before-talk (LBT) procedure of LAA eNBs to improve the coexistence system throughput. However, note that the fixed DB value in traditional CSMA/ECA cannot ensure fair coexistence all the time corresponding to different network sizes. Therefore, an adjustable DB value scheme is devised to replace the fixed one, in order to achieve fair coexistence whatever the number of Wi-Fi nodes and LAA eNBs is. Aiming to obtain the maximum system throughput improvement, the behavior of a LAA eNB is modeled as a Markov chain, and the throughput of the coexistence network is derived. Then, we formulate a throughput optimization problem and develop an algorithm of DB value adjustment, which can not only achieve the maximum throughput improvement but also maintain the fair coexistence whatever the number of nodes in the coexistence network is. At last, numerical results are presented which validate the accuracy of our analysis model and demonstrate the effectiveness of the proposed algorithm.

ACS Style

Xin Zhang; Zhaoming Lu; Xiangming Wen; Wenpeng Jing; Hang Qi. A fair and efficient channel access approach based on CSMA with enhanced collision avoidance for LAA. 2018 IEEE Wireless Communications and Networking Conference (WCNC) 2018, 1 -6.

AMA Style

Xin Zhang, Zhaoming Lu, Xiangming Wen, Wenpeng Jing, Hang Qi. A fair and efficient channel access approach based on CSMA with enhanced collision avoidance for LAA. 2018 IEEE Wireless Communications and Networking Conference (WCNC). 2018; ():1-6.

Chicago/Turabian Style

Xin Zhang; Zhaoming Lu; Xiangming Wen; Wenpeng Jing; Hang Qi. 2018. "A fair and efficient channel access approach based on CSMA with enhanced collision avoidance for LAA." 2018 IEEE Wireless Communications and Networking Conference (WCNC) , no. : 1-6.

Proceedings article
Published: 01 December 2017 in 2017 IEEE Globecom Workshops (GC Wkshps)
Reads 0
Downloads 0

Machine-type communication (MTC) is a promising technology to constitute a significant part of the fifth-generation (5G) systems. Massive MTC is considered to be one of the usage scenarios of 5G. However, large accesses of massive devices would lead to serious overload and deteriorate the service performance of Human-to-Human communication (H2H). Group paging is one of the solutions to alleviate the Radio Access Network (RAN) congestion. When the group scale is large, group paging with pre-backoff can effectively alleviate the RAN overload problem. But the existing group paging schemes have an apparent defect that they can not ensure the QoS requirements for devices in different applications. In contrast with the existing group paging schemes, we introduce a differentiated QoS provisioning strategy named pre- backoff based random access with priority (PBRAP). Specifically, We classify the MTC devices into three priority categorizations according to their QoS requirements. The random access slots would be allocated to different MTC classes according to their priorities. The proposed scheme can alleviate the RAN overload as well as guarantee the the QoS requirements. The efficiency of the proposed scheme is verified through computer simulation.

ACS Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Qi Pan; Wenpeng Jing. Pre-Backoff Based Random Access with Priority for 5G Machine-Type Communication. 2017 IEEE Globecom Workshops (GC Wkshps) 2017, 1 -6.

AMA Style

Linpei Li, Xiangming Wen, Zhaoming Lu, Qi Pan, Wenpeng Jing. Pre-Backoff Based Random Access with Priority for 5G Machine-Type Communication. 2017 IEEE Globecom Workshops (GC Wkshps). 2017; ():1-6.

Chicago/Turabian Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Qi Pan; Wenpeng Jing. 2017. "Pre-Backoff Based Random Access with Priority for 5G Machine-Type Communication." 2017 IEEE Globecom Workshops (GC Wkshps) , no. : 1-6.

Article
Published: 02 September 2016 in Wireless Networks
Reads 0
Downloads 0

This paper investigates the energy-efficient radio resource allocation problem of the uplink smallcell networks. Different from the existing literatures which focus on improving the energy efficiency (EE) or providing fairness measured by data rates, this paper aims to provide fairness guarantee in terms of EE and achieve EE-based proportional fairness among all users in smallcell networks. Specifically, EE-based global proportional fairness utility optimization problem is formulated, taking into account each user’s quality of service, and the cross-tier interference limitation to ensure the macrocell transmission. Instead of dealing with the problem in forms of sum of logarithms directly, the problem is transformed into a form of sum of ratios firstly. Then, a two-step scheme which solves the subchannel and power allocation separately is adopted, and the corresponding subchannel allocation algorithm and power allocation algorithm are devised, respectively. The subchannel allocation algorithm is heuristic, but can achieve close-to-optimal performance with much lower complexity. The power allocation scheme is optimal, and is derived based on a novel method which can solve the sum of ratios problems efficiently. Numerical results verify the effectiveness of the proposed algorithms, especially the capability of EE fairness provisioning. Specifically, it is suggested that the proposed algorithms can improve the fairness level among smallcell users by 150–400 % compared to the existing algorithms.

ACS Style

Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Zhiqun Hu; Tao Lei. Proportional-fair energy-efficient radio resource allocation for OFDMA smallcell networks. Wireless Networks 2016, 24, 695 -707.

AMA Style

Wenpeng Jing, Xiangming Wen, Zhaoming Lu, Zhiqun Hu, Tao Lei. Proportional-fair energy-efficient radio resource allocation for OFDMA smallcell networks. Wireless Networks. 2016; 24 (3):695-707.

Chicago/Turabian Style

Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Zhiqun Hu; Tao Lei. 2016. "Proportional-fair energy-efficient radio resource allocation for OFDMA smallcell networks." Wireless Networks 24, no. 3: 695-707.

Journal article
Published: 26 February 2016 in International Journal of Communication Systems
Reads 0
Downloads 0

Wireless multimedia services are increasingly becoming popular, which boosts the need for better quality-of-experience (QoE). However, there are many aspects leading to the degradation of real-time video QoE, especially, a large number of always-on-line (AOL) applications existing in future wireless networks transmit heartbeat message periodically to keep always-on, and hence induce heavy signaling costs and overload wireless networks. In this paper, we propose QoE-based pseudo heartbeat message compression mechanism to reduce the number of signaling loads in the radio access network by intercepting the heartbeat message at a certain frequency in the proxy client. To maintain the protocol feature of the AOL applications, the heartbeat messages are reconstructed by the proxy server and sent to the application server. Furthermore, to analyze the influence of this mechanism on the video user, a new QoE perception model is proposed. Finally, combined the QoE perception model for video services with AOL services, the utility function for joint optimization multi-services is developed to determine the optimum compression frequency. The simulation results show that the proposed mechanism greatly alleviates the signaling load and leads to a significant performance improvement on the QoE of video users, while a slight decrease in the QoE of AOL users. Copyright © 2016 John Wiley & Sons, Ltd.

ACS Style

Zhiqun Hu; Zhaoming Lu; Xiangming Wen; Wenpeng Jing. QoE-based pseudo heartbeat message compression mechanism for future wireless network. International Journal of Communication Systems 2016, 29, 1513 -1528.

AMA Style

Zhiqun Hu, Zhaoming Lu, Xiangming Wen, Wenpeng Jing. QoE-based pseudo heartbeat message compression mechanism for future wireless network. International Journal of Communication Systems. 2016; 29 (9):1513-1528.

Chicago/Turabian Style

Zhiqun Hu; Zhaoming Lu; Xiangming Wen; Wenpeng Jing. 2016. "QoE-based pseudo heartbeat message compression mechanism for future wireless network." International Journal of Communication Systems 29, no. 9: 1513-1528.

Journal article
Published: 17 December 2015 in IEEE Communications Letters
Reads 0
Downloads 0

Quality of experience (QoE) and power consumption are two important considerations of OFDMA multicell networks. In this letter, we propose a fair QoE-based radio resource allocation (FQRA) for OFDMA multicell networks. Different from the previous work, the multiuser QoE per power consumption is introduced as the performance metric. A novel utility function, which can characterize the fairness of users' QoE and power consumption jointly, is proposed. Then a multiuser FQRA problem is formulated. Due to the nonconvex form of optimization, a two-step solution is devised in which the subchannel allocation and power allocation are performed iteratively. Simulation results show that our method can significantly improve the QoE per power consumption of cells and outperform the state-of-art schemes.

ACS Style

Hua Shao; Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang; Yawen Chen; Dabing Ling. Joint Optimization of Quality of Experience and Power Consumption in OFDMA Multicell Networks. IEEE Communications Letters 2015, 20, 380 -383.

AMA Style

Hua Shao, Wenpeng Jing, Xiangming Wen, Zhaoming Lu, Haijun Zhang, Yawen Chen, Dabing Ling. Joint Optimization of Quality of Experience and Power Consumption in OFDMA Multicell Networks. IEEE Communications Letters. 2015; 20 (2):380-383.

Chicago/Turabian Style

Hua Shao; Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang; Yawen Chen; Dabing Ling. 2015. "Joint Optimization of Quality of Experience and Power Consumption in OFDMA Multicell Networks." IEEE Communications Letters 20, no. 2: 380-383.

Journal article
Published: 07 July 2015 in IEEE Communications Letters
Reads 0
Downloads 0

IEEE 802.11ac standard, adopting a downlink multi-user multiple-input and multiple-output (DL-MU-MIMO) scheme, can significantly improve the performance of wireless local area networks (WLANs). To support the DL-MU-MIMO technology, a transmission opportunity (TXOP) sharing mechanism has been proposed to allow an access point (AP) to communicate with multiple users simultaneously. In this letter, we present an analytical model based on Markov chains for a non-saturated IEEE 802.11ac enhanced distributed channel access (EDCA) network, which supports the TXOP sharing mechanism. The analytical model computes the 802.11ac EDCA throughput, in the assumption of ideal channel conditions. Extensive simulation and analysis results show that the analytical model can accurately predict the throughput of the 802.11ac networks under non-saturated operation.

ACS Style

Zhiqun Hu; Xiangming Wen; Zhaoxing Li; Zhaoming Lu; Wenpeng Jing. Modeling the TXOP Sharing Mechanism of IEEE 802.11ac Enhanced Distributed Channel Access in Non-Saturated Conditions. IEEE Communications Letters 2015, 19, 1576 -1579.

AMA Style

Zhiqun Hu, Xiangming Wen, Zhaoxing Li, Zhaoming Lu, Wenpeng Jing. Modeling the TXOP Sharing Mechanism of IEEE 802.11ac Enhanced Distributed Channel Access in Non-Saturated Conditions. IEEE Communications Letters. 2015; 19 (9):1576-1579.

Chicago/Turabian Style

Zhiqun Hu; Xiangming Wen; Zhaoxing Li; Zhaoming Lu; Wenpeng Jing. 2015. "Modeling the TXOP Sharing Mechanism of IEEE 802.11ac Enhanced Distributed Channel Access in Non-Saturated Conditions." IEEE Communications Letters 19, no. 9: 1576-1579.

Journal article
Published: 01 July 2015 in International Journal of Distributed Sensor Networks
Reads 0
Downloads 0

Information security has been received more and more attention for next-generation wireless sensor networks. In this paper, we consider the problem of resource management based on security satisfaction ratio with fairness-aware in two-way relay networks. Multiple source nodes exchange information with the help of relay node in the presence of an eavesdropper, and diverse security requirements are taken into account with coexistence of security users and normal users. The joint problem of power allocation, and subchannel pairing and allocation aims to maximize the security satisfaction ratio for legitimate users subject to limited power and subchannel constraints. We model the security resource management problem as a mixed integer programming problem, which is decomposed into three subproblems, distributed power allocation, distributed subchannel allocation, and distributed subchannel pairing, and then solved it in constraint particle swarm optimization (CPSO), binary CPSO (B_CPSO), and classic Hungarian algorithm (CHA) method, respectively. Moreover, a suboptimal subchannel pairing algorithm is proposed to reduce the computational complexity compared with the CHA. Simulations are conducted to evaluate the effectiveness of the proposed algorithms.

ACS Style

Jun Zhao; Zhaoming Lu; Xiangming Wen; Haijun Zhang; Shenghua He; Wenpeng Jing. Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks. International Journal of Distributed Sensor Networks 2015, 11, 1 .

AMA Style

Jun Zhao, Zhaoming Lu, Xiangming Wen, Haijun Zhang, Shenghua He, Wenpeng Jing. Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks. International Journal of Distributed Sensor Networks. 2015; 11 (7):1.

Chicago/Turabian Style

Jun Zhao; Zhaoming Lu; Xiangming Wen; Haijun Zhang; Shenghua He; Wenpeng Jing. 2015. "Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks." International Journal of Distributed Sensor Networks 11, no. 7: 1.

Article
Published: 26 June 2015 in Mobile Networks and Applications
Reads 0
Downloads 0

Femtocell is a promising technique to enhance indoor coverage and improve network capacity. Nevertheless, because of the random and co-channel deployment of femtocells, the macrocell will suffer serious cross-tier interference from femtocells in two-tier femtocell networks. Thus, interference mitigation in femtocell networks has been an indispensable task. Meanwhile, with the explosive popularity of smart terminals, especially smart phones and tablets, the wireless networks have loaded a mount of data services with diverse delay quality of service (QoS) requirements. However, due to the stochastically varying nature of wireless physical channel, it is extremely difficult to offer a deterministic delay guarantee in wireless networks. Therefore, the effective capacity of femtocell users (FU) has been introduced to provide a statistical delay QoS provisioning. For that reason, in this paper, we will study the interference mitigation with statistical delay QoS guarantee in uplink two-tier orthogonal frequency division multiple access (OFDMA) femtocell networks. In order to mitigate the cross-tier interference at macrocell base station (MBS), we adopt a price-based power control strategy, in which the MBS protects itself by pricing the interference from FU. Additionally, to guarantee the statistical delay QoS for each FU, effective capacity is introduced into their utility functions. Then, a Stackelberg game is formulated to study the joint utility maximization of the MBS and the FUs subject to a maximum tolerable interference power constraint at the MBS. Subsequently, based on the mathematical analysis of the equilibrium of the formulated Stalkeberg game, a particle swarm optimization (PSO) aided power allocation (PSOPA) algorithm is proposed to solve this optimization problem. At last, simulation results show that our proposed PSOPA algorithm can not only improve significantly the average effective capacity of each FU and guarantee their statistical delay QoS, but also converge successfully.

ACS Style

Shenghua He; Zhaoming Lu; Xiangming Wen; Zhicai Zhang; Jun Zhao; Wenpeng Jing. A Pricing Power Control Scheme with Statistical Delay QoS Provisioning in Uplink of Two-tier OFDMA Femtocell Networks. Mobile Networks and Applications 2015, 20, 413 -423.

AMA Style

Shenghua He, Zhaoming Lu, Xiangming Wen, Zhicai Zhang, Jun Zhao, Wenpeng Jing. A Pricing Power Control Scheme with Statistical Delay QoS Provisioning in Uplink of Two-tier OFDMA Femtocell Networks. Mobile Networks and Applications. 2015; 20 (4):413-423.

Chicago/Turabian Style

Shenghua He; Zhaoming Lu; Xiangming Wen; Zhicai Zhang; Jun Zhao; Wenpeng Jing. 2015. "A Pricing Power Control Scheme with Statistical Delay QoS Provisioning in Uplink of Two-tier OFDMA Femtocell Networks." Mobile Networks and Applications 20, no. 4: 413-423.

Journal article
Published: 22 June 2015 in International Journal of Communication Systems
Reads 0
Downloads 0

In this paper, we study the resource allocation problem of the uplink transmission with delay quality‐of‐service constraints in two‐tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra‐cluster subchannel allocation subproblem and inter‐cluster power control subproblem. Firstly, we develop a low‐complexity heuristic semi‐dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter‐cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter‐cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes. Copyright © 2015 John Wiley & Sons, Ltd.

ACS Style

Fengchao Fu; Zhaoming Lu; Yuanbao Xie; Wenpeng Jing; Xiangming Wen. Clustering-based low-complexity resource allocation in two-tier femtocell networks with QoS provisioning. International Journal of Communication Systems 2015, 30, e3005 .

AMA Style

Fengchao Fu, Zhaoming Lu, Yuanbao Xie, Wenpeng Jing, Xiangming Wen. Clustering-based low-complexity resource allocation in two-tier femtocell networks with QoS provisioning. International Journal of Communication Systems. 2015; 30 (4):e3005.

Chicago/Turabian Style

Fengchao Fu; Zhaoming Lu; Yuanbao Xie; Wenpeng Jing; Xiangming Wen. 2015. "Clustering-based low-complexity resource allocation in two-tier femtocell networks with QoS provisioning." International Journal of Communication Systems 30, no. 4: e3005.

Journal article
Published: 14 January 2015 in IEEE Communications Letters
Reads 0
Downloads 0

The radio resource allocation problem is studied, aiming to jointly optimize the energy efficiency (EE) and spectral efficiency (SE) of downlink OFDMA multi-cell networks. Different from existing works on either EE or SE optimization, a novel EE-SE tradeoff (EST) metric, which can capture both the EST relation and the individual cells' preferences for EE or SE performance, is introduced as the utility function for each base station (BS). Then the joint EE-SE optimization problem is formulated, and an iterative subchannel allocation and power allocation algorithm is proposed. Numerical results show that the proposed algorithm can exploit the EST relation flexibly and optimize the EE and SE simultaneously to meet diverse EE and SE preferences of individual cells.

ACS Style

Wenpeng Jing; Zhaoming Lu; Xiangming Wen; Zhiqun Hu; Shaoshi Yang. Flexible Resource Allocation for Joint Optimization of Energy and Spectral Efficiency in OFDMA Multi-Cell Networks. IEEE Communications Letters 2015, 19, 451 -454.

AMA Style

Wenpeng Jing, Zhaoming Lu, Xiangming Wen, Zhiqun Hu, Shaoshi Yang. Flexible Resource Allocation for Joint Optimization of Energy and Spectral Efficiency in OFDMA Multi-Cell Networks. IEEE Communications Letters. 2015; 19 (3):451-454.

Chicago/Turabian Style

Wenpeng Jing; Zhaoming Lu; Xiangming Wen; Zhiqun Hu; Shaoshi Yang. 2015. "Flexible Resource Allocation for Joint Optimization of Energy and Spectral Efficiency in OFDMA Multi-Cell Networks." IEEE Communications Letters 19, no. 3: 451-454.

Conference paper
Published: 01 June 2014 in 2014 IEEE International Conference on Communications Workshops (ICC)
Reads 0
Downloads 0

In this paper, the resource allocation problem is studied in downlink femtocell networks to minimize the energy consumption of femtocell base stations (FBSs), provide delay-aware quality-of-service (QoS) guarantees for femtocell users and limit the cross-tier interference. Specifically, by integrating the concept of effective capacity, users' delay-aware QoS requirements are characterized by the QoS exponent and minimum effective capacity constraints. The problem of minimizing transmit power of FBSs is formulated as a mixed integer programming problem and is decomposed into two subproblems in order to reduce the complexity. Accordingly, a suboptimal subchannel allocation algorithm and a QoS-driven optimal power allocation algorithm are proposed respectively. Simulation results demonstrate that the proposed algorithms can use the lowest transmit power to satisfy diverse delay-aware QoS requirements of femtocell users, which show great advantages in energy saving and QoS provisioning.

ACS Style

Wenpeng Jing; Zhaoming Lu; Haijun Zhang; Zhicai Zhang; Jun Zhao; Xiangming Wen. Energy-saving resource allocation scheme with QoS provisioning in OFDMA femtocell networks. 2014 IEEE International Conference on Communications Workshops (ICC) 2014, 912 -917.

AMA Style

Wenpeng Jing, Zhaoming Lu, Haijun Zhang, Zhicai Zhang, Jun Zhao, Xiangming Wen. Energy-saving resource allocation scheme with QoS provisioning in OFDMA femtocell networks. 2014 IEEE International Conference on Communications Workshops (ICC). 2014; ():912-917.

Chicago/Turabian Style

Wenpeng Jing; Zhaoming Lu; Haijun Zhang; Zhicai Zhang; Jun Zhao; Xiangming Wen. 2014. "Energy-saving resource allocation scheme with QoS provisioning in OFDMA femtocell networks." 2014 IEEE International Conference on Communications Workshops (ICC) , no. : 912-917.