Zejue Wang

Joint wireless and backhaul load balancing in cooperative caches enabled small-cell networks

Distributed and cooperative caches (DCCs) enabled small-cell network (SCN) has been a common approach for improving QoE perceived by mobile users (UEs) and reducing backhaul traffic load. In this paper, we propose a joint wireless and backhaul load balancing (JWBLB) framework for DCCs enabled SCNs with the objective to minimizing the system content transmission delay. The JWBLB is achieved through content-request UEs and small-cell base stations re-association, and back-haul links and cooperative caches selection, with the knowledge of the cached content distribution, jointly considering traffic load of wireless and backhaul links. Specifically, 1) a software defined networking (SDN) inspired load balancing control architecture, consisting of the coordinator and DCCs, is designed. 2) The optimal JWBLB problem is formulated with the objective to minimizing the system content transmission delay, which is proved to be a quadratic assignment problem (QAP). 3) A joint Lagrangian relaxation and decomposition, and accelerated branch and bound algorithm is proposed to efficiently find the optimal binary solutions of the considered QAP. Simulation results show that JWBLB achieves great reduction in the average transmission delay and outgoing backhaul traffic load. For instance, 65% average transmission delay can be reduced as only 50% UEs with potential re-association possibility, and 48.4% outgoing traffic load caused by content fetches from Internet is reduced as the Zipf distribution parameter equals 0.6.

Cooperative RAN Caching Based on Local Altruistic Game for Single and Joint Transmissions

This letter proposes a cooperative caching placement framework for coordinated multi-point joint transmission and single cell transmission, to minimize content transmission time for mobile users. The optimization problem is NP-hard. We thus transform it into a local altruistic game, and propose two evolved Spatial Adaptive Play (SAP) algorithms: the first one overcomes the main limitation of the traditional SAP that large action sets pose an unsurmountable computational burden; the second one further expedites escape from convergence traps caused by fake Nash Equilibria. Numerical results conducted based on a real-world LTE traffic data set have validated the performance of our proposed algorithms.

Cross-layer transmission and energy scheduling under full-duplex energy harvesting wireless OFDM joint transmission

This paper studies the design of the optimal and online cross-layer transmission and energy schedulings for a full-duplex energy harvesting wireless orthogonal frequency division multiplexing (OFDM) joint transmissions. Supported by today’s power management integrated circuit, the full-duplex energy harvesting system becomes a reality, which can overcome the transmission time loss problem caused by the half-duplex constraint of the energy storage unit (ESU) in the serial Harvest-Store-Use system. However, its corresponding modeling is still unexplored. Therefore, the full-duplex energy harvesting system is first modeled and proved to be equivalent to a composition of energy behavior models of Harvest-Store-Use in fine-time granularity. Then, the convex optimization problem of cross-layer transmission and energy scheduling is formulated with the objective to maximize the sum of transmission throughput during successively multiple time units, which takes into account the temporal variance of energy harvesting rates and channel states, and the limited capacity of ESUs. The optimal power allocation with three dimensions of time, channel and antenna is solved by utilizing the dual decomposition method with the pre-known temporal variance, and the corresponding result of the system throughput provides the theoretical upper bound. Finally, to reduce the throughput degradation caused by channel state prediction errors, a non-convex online scheduling problem is formulated as the classical energy efficiency format. It is transformed into a convex optimization problem by exploiting the properties of fractional programming, and then, an efficiently iterative solution is designed. Numerical results show that the average throughput of the online algorithm is 24% greater than that of existing time-energy adaptive water-filling algorithm. The degradation of the average throughput is less than 19% with probability 90%, even as the channel prediction error reaches 20%. These results provide guidelines for the design and optimization for full-duplex energy harvesting joint transmission systems.摘要创新点建立了全双工能量采集系统的能量流模型, 并证明了在时间尺度足够小时其可采用经典的顺序能量收集-存储-使用模型表示; 构建了最优化连续多时隙吞吐量问题模型, 并针对该问题, 基于对偶分解方法提出了功率在不同信道、天线与时隙的最优化离线控制算法; 进一步, 在考虑信道预测差的条件下, 构建了最优化连续多时隙吞吐量在线问题模型, 并针对其非凸性, 基于分数规划理论提出了功率在不同信道、天线与时隙的在线优化控制算法。

Feasibility analysis and self-organizing algorithm for RAN cooperative caching

The radio access network (RAN) cooperative caching, which explores the scale effect through cooperative content sharing and caching among multiple RAN caches, is considered as one effective way to fully benefit from the RAN cache. In this paper, we study the feasibility and self-organizing algorithm for RAN cooperative caching. Specifically, we first analyze the real-world dataset of daily content requests from 10 LTE Base Stations (BSs), and find that pursuing high hit rate does not guarantee the reduction of backhaul traffic. Besides, it is shown that content requests from different BSs feature strongly temporal and spatial correlations. To the best of our knowledge, this finding proves the feasibility of RAN cooperative caching for the first time. Then, based on our findings, we propose the self-organizing algorithm for RAN caches to individually decide on how to update their cached content objects, utilizing the defined utility with consideration of the link states among RAN caches, and the size and the request number of the missed and cached content objects. Finally, the performance of our proposed algorithm is validated based on real-world dataset. The results show that the proposed algorithm achieves significant improvement in reducing backhaul traffic. For instance, when cache capacity of each BS is 65% of the traffic generated by non-repeated content objects which are requested in one day over its coverage, the proposed algorithm with 8 defined cooperative caches (CoCas) reaches an average reduction of more than 60% of the backhaul traffic generated in one day over the BSs coverage.

Stochastic queue modeling and key design metrics analysis for solar energy powered cellular networks

There is a growing interest around the world in supplying cellular networks with renewable energy, e.g., solar, wind, and hydro, to reduce carbon footprints. One of the most challenging topics is how to design a reliable and efficient renewable energy powered cellular system, which consists of the energy harvesting part, the energy buffer part and the energy consumption part. Motivated by the open issue, we provide a theoretical basis for modeling and key design metrics definition and analysis of the solar energy powered small cells in Hetnet, which will be widely deployed in LTE(-A) networks. Firstly, the energy flow behavior of solar powered small cells is modeled by using the stochastic queue model, and then dynamics of the constructed model is analyzed mathematically. Secondly, three key design metrics, service outage probability (SOP), renewable energy utilization efficiency (REUE) and Mean depth of discharge (MDoD), are defined, and then closed-form expressions of them are derived. Through numerical analysis with measured data of the solar radiation and temperature, the design metrics under different conditions are illustrated vividly, and the optimal design limit is provided. The proposed modeling method and key design metrics provide a theoretical basis for actual designs of solar energy powered small cells, which also can be further applied to the scenario of other forms of renewable energy powered small cells.

Real-world traffic analysis and joint caching and scheduling for in-RAN caching networks

This paper analyzes the traffic of a current LTE network in China and investigates the joint optimization of content object caching and scheduling for in-radio access network (RAN) caches. Cooperative caching has been well recognized as a way of unleashing the ultimate potential of in-RAN caches, yet its feasibility is still unexplored. Moreover, content object caching and scheduling are two key issues for cache deployment, which are usually jointly considered and resolved. However, they are triggered by different events with different time granularities. Therefore, on the basis of the real-world dataset, the feasibility of in-RAN cooperative caching is proved from aspects of network topology, traffic load difference among small base stations (SBSs) and correlation analysis of content objects requested at different SBSs. Then, it is verified that different time scales should be considered in making content object caching and scheduling decisions. To exploit in-RAN cooperative caching while meeting the time scale requirement in making caching and scheduling decisions, an optimization problem is constructed considering practical transmission constraints in wireless and backhaul. It is proved to be a quadratic assignment problem, and then, a joint caching, and wireless and backhaul scheduling algorithm is proposed based on Lagrangian relaxation and decomposition, and hastening branch and bound. The performance of the proposed algorithm is evaluated based on the real-world dataset. Results depict the relationship among the cache capacity, the number of SBSs, the connection probability of SBSs and the objective performance, and show that the proposed algorithm can achieve better performance, compared with the existing algorithms.

Optimal joint transmission scheduling for green energy powered coordinated multi-point transmission system

Due to advantages in spectral efficiency and energy efficiency of its air-interface, the coordinated multi-point (CoMP) transmission has been adopted in 4G and beyond mobile communication systems, such as LTE-A, which enables the transmission cooperation among multiple remote radio units (RRUs). As the main component of a RRU, the power amplifier (PA) is always blamed for its low power efficiency, which is difficult to be further improved by todays hardware technology. To eliminate the on-grid power consumption caused by the low PA efficiency and the corresponding CO2 emission, we propose a new CoMP transmission framework, in which all RRUs and associated PAs are powered by the solar power. Then, based on the proposed framework, we derive the optimal coordinated transmission scheduling algorithm for maximizing the throughput with considerations of fast fading channel, limited pre-knowledge about channel state information (CSI), random energy arrival and finite energy storage. Theoretical analyses of the proposed algorithm are given, and numerical results show that our algorithm can achieve a close performance to the optimal transmission scheduling algorithm with a priori knowledge about CSI.

Modeling and Transmission Optimization of Full-Duplex Energy Harvesting Enabled Hybrid Relaying

Energy harvesting (EH) enabled relaying has attracted lots of interests recently, as the network energy consumption can be reduced and the coverage range can be extended simultaneously. In most existing literatures, the Harvest-Store-Use (HSU) model is utilized to describe the energy flow behavior of the EH system. However, the half-duplex (HD) constraint of HSU that harvested energy can only be used for powering load after being temporally stored in energy storage unit may reduce the effective transmission time. Thus, we first model the full-duplex (FD) energy flow behavior of the EH system where harvested energy can be tuned to power load and being stored simultaneously, and then prove the FD model is equivalent to the HSU model when time interval is small enough. With consideration of some key physical variabilities, e.g., the wireless channel and the amount of harvested energy, and the energy consumption difference between FD and HD relaying protocols, we further model the transmission optimization problem to improve the utilization of harvested energy by optimizing the short-term throughput. Finally, to numerically obtain the optimized short-term throughput, we propose the joint power adaption, relay selection and transmission protocol switching algorithm. Results show that the performance of the proposed algorithm outperforms that of fixed relaying algorithms, e.g., the short-term throughput of the proposed algorithm is improved by about 40% comparing with fixed HD relaying algorithm, with 20 user equipments, and loop interference power and EH rate equal to 23 dB and 120 J/s, respectively.

Transmission Adaptation for Battery-Free Relaying

Energy harvesting (EH)–enabled relaying has attracted considerable attention as an effective way to prolong the operation time of energy-constrained networks and extend coverage beside desired survivability and rate of transmission. In related literature, the Harvest-Store-Use (HSU) model is usually utilized to describe the energy flow behavior of the EH system. However, the half-duplex (HD) constraint of HSU that harvested energy can only be used after being temporally stored in energy buffer may reduce effective transmission time. Thus, we first construct the full-duplex (FD) energy flow behavior model of the EH system where the harvested energy can be tuned to power load and being stored simultaneously. The FD model is then proved to be equivalent with the HSU model when time interval is small enough. Considering some key physical variabilities, for example, the wireless channel and the amount of harvested energy, the transmission adaptation problem for multiple relays embedded with FD EH systems is formulated with the objective to improve the utilization of the harvested energy. We tackle the problem by using a centralized optimization algorithm by jointly tuning the factors, including power control for source and relay nodes, relay selection and dynamic switching among four relay transmission mode, namely HD amplify-and-forward (AF), HD decode-and-forward (DF), FD AF, and FD DF. The centralized optimization algorithm is proposed on the basis of dual decomposition and serves as a benchmark. To enable relays to individually make their own decisions, a distributed algorithm with relatively higher complexity is given by using consensus optimization in conjunction with the alternating direction method of multipliers, and a sub-optimal algorithm with low complexity is provided. The proposed algorithms are shown to have good performance via simulations for a range of different EH rates and prediction errors.

Adaptive relaying for full-duplex energy harvesting enabled cooperative communication in harsh environments

Energy harvesting (EH) enabled relaying has attracted considerable attentions as an effective way to prolong the operation time of energy-constrained networks and extend coverage beside desired survivability and rate of transmission. In most existing literatures, the Harvest-Store-Use (HSU) model is utilized to describe the energy flow behavior of the EH system. However, the half-duplex (HD) constraint of HSU that harvested energy can only be used after being temporally stored in energy storage unit may reduce effective transmission time. Thus, we first construct the full-duplex (FD) energy flow behavior model of the EH system where the harvested energy can be tuned to power load and being stored simultaneously, and then prove the FD model is equivalent to the HSU model when time interval is small enough. Considering some key physical variabilities, e.g., the wireless channel and the amount of harvested energy, we further study the transmission optimization problem to improve the utilization of the harvested energy by optimizing the short-term throughput. Finally, to numerically obtain the optimized short-term throughput, we propose the adaptive relaying algorithm, including power control for source and relay nodes, relay selection and dynamic switching among four relay transmission modes, namely, HD amplify-and-forward (AF), HD decode-and-forward (DF), FD AF and FD DF. Results show that short-term throughput of the system can be improved through adaptive relaying in the proposed algorithm.