A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1315&context=electricalengineeringfacpub

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

An attractive architecture called heterogeneous cloud radio access networks (H-CRAN) becomes one of the important components of 5G networks, which can provide ubiquitous high-bandwidth services with flexible network construction. However, massive access nodes increase the risk of cell outages, leading to negative impact on user-perceived QoS (Quality of Service) and QoE (Quality of Experience). Thus, cell outage management (COM) became a key function proposed in SON (Self-Organized Networks) use cases. Based on COM, cell outage detection (COD) will be resolved before cell outage compensation (COC). Currently few studies concentrate on COD for 5G H-CRAN, and we propose self-organized COD architecture and approach for it. We firstly summarize current COD solutions for LTE/LTE-A HetNets and then introduce self-organized architecture and approach suitable for H-CRAN, which includes COD architecture and procedures, and corresponding key technologies for it. Based on the architecture, we take a use case with handover data analysis using modified LOF (Local Outlier Factor) detection approach to detect outage for different kinds of cells in H-CRAN. Results show that the proposed approach can identify the outage cell effectively.

/pdf/self-organized-cell-outage-detection-architecture-and-3i1y3j4dqk.pdf

Self-Organized Cell Outage Detection Architecture and Approach for 5G H-CRAN

As one of the key technologies of 5G, Cloud Radio Access Networks (C-RAN) with cloud BBUs (Base Band Units) pool architecture and distributed RRHs (Remote Radio Heads) can provide the ubiquitous services. When failure occurs at RRH, it can’t be alleviated in time and will lead to a significant drop in network performance. Therefore, the cell outage compensation (COC) problem for RRH in 5G C-RAN is very important. Although deep reinforcement learning (DRL) has been applied to many scenarios related to the self-organizing network (SON), there are fewer applications for cell outage compensation. And most intelligent algorithms are hard to obtain globally optimized solutions. In this paper, aiming at the cell outage scenario in C-RAN with the goal of maximizing the energy efficiency, connectivity of RRH while meeting service quality demands of each compensation user, a framework based on DRL is presented to solve it. Firstly, compensation users are allocated to adjacent RRHs by using the K-means clustering algorithm. Secondly, DQN is used to find the antenna downtilt and the power allocated to compensation users. Comparing to different genetic algorithms, simulation result shows that the proposed framework converges quickly and tends to be stable, and reaches 95% of the maximum target value. It verifies the efficiency of the DRL-based framework and its effectiveness in meeting user requirements and handling cell outage compensation.

Deep Reinforcement Learning Aided Cell Outage Compensation Framework in 5G Cloud Radio Access Networks

As one of the key technologies of 5G, massive IoT environments provide the ubiquitous IoT services. Compared with 4G, its structure is more complex, and it has a large number of deployed nodes. If a failure occurs and can't be alleviated its effect in time, it will lead to a significant drop in network performance. Therefore, the cell outage compensation (COC) problem in massive IoT environments is very important. Although deep reinforcement learning (DRL) has been applied to many scenarios related to the self-organizing network (SON), there are fewer applications for cell outage compensation. In this paper, aiming at the cell outage scenario in massive IoT environments with the goal of maximizing the connectivity of base stations while meeting service quality demands of each compensation user, we present a framework based on DRL to solve it. Specifically, we first allocate compensation users to adjacent BSs by using the K-means clustering algorithm, then use DQN to find the antenna downtilt and the power allocated to compensation users. The simulation result shows that the algorithm converges quickly and tends to be stable, and reach 95% of the maximum target value. It verifies the efficiency of the DRL-based framework and its effectiveness in meeting user requirements and handling cell outage compensation.

A Deep Reinforcement Learning based Mechanism for Cell Outage Compensation in Massive IoT Environments

Emergency communications need to meet the developing demand of equipment and the complex scenarios of network in public safety networks (PSNs). Heterogeneous Cloud Radio Access Network (H-CRAN), an important technology of the 5th generation wireless systems (5G), plays an important role in PSN. H-CRAN has the features of resource sharing and centralized allocation which can make up for resource shortage in emergency communications. Therefore, an emergency communications strategy based on Device-to-device (D2D) multicast is proposed to make PSN more flexible and rapid. Nearby users can communicate directly without a base station through D2D. This strategy may guarantee high speed data transmission and stable continuous real-time communications. It is divided into three steps. Firstly, according to the distance between users, the alternative cluster head is divided. Secondly, two kinds of cluster head user selection schemes are developed. One is based on terminal power and the other is based on the number of extended users. Last but not least, the Hungarian Algorithm based on throughput-aware is used to channel multiplexing. The numerical results show that the proposed scheme can effectively extend the coverage of PSN and optimize the utilization of resources.

https://www.mdpi.com/1424-8220/20/7/1901/pdf

Emergency Communications Based on Throughput-Aware D2D Multicasting in 5G Public Safety Networks.

Cell outage compensation is a crucial way for public safety network (PSN) to recover network communication independently during disasters. As a significant technology for 5G, a cloud-radio access network (C-RAN) plays an important role in a PSN. C-RAN can better achieve multi-cell cooperative outage compensation under dense network coverage because of the characteristics of densification and centralization. Therefore, we propose an efficient multi-cell cooperative outage compensation convergence for the scene where more than one radio remote units (RRUs) are destructed in C-RAN-based PSN. This scheme compensates the network using both cooperative transmission and power adjustment. First, RRUs are selected to participate in the compensation according to the topology structure. Then, the problem model is built aiming at optimizing system outage probability. At the same time, the constraints of resources and service quality are considered. In addition, an enhanced immune-genetic algorithm is proposed innovatively to solve this NP-hard problem and to get the results of RRU transmit power parameters. Finally, simulation results demonstrate that the proposed algorithm convergences rapidly and our scheme reduces the PSN system outage probability effectively with the guarantee of users received power and the restriction of interference effects. The outage probability of the PSN system using the proposed method is 17.8% of the only cooperative transmit method and 3.9% lower than the only adjust power method.

Multi-Cell Cooperative Outage Compensation in Cloud-RANs Based 5G Public Safety Network

As a major part of wireless network optimization, load balancing can make the BS's resource utilization more reasonable This paper proposes a load-balancing strategy based on Coordinated Multiple Points (CoMP) transmission/reception among the Base Stations (BS) To use universally, different patterns of load-balancing based on CoMP are modeled and discussed We define call blocking rate as the QoS metric to be guaranteed during load balancing process The capacity of load-balancing and call blocking rate with different load-balancing patterns based on CoMP are evaluated and analyzed in an area with a moderate dense distribution of high-loaded BSs The analysis on the numerical results give the proper load balancing pattern based on CoMP with guaranteed call blocking rate

Load-balancing based on Base-Station CoMP with guaranteed call blocking rate

LTE-based Public Safety Network (PSN) is a wireless communication network which can provide efficient and reliable communication in disasters or emergencies for disaster relief and public protection. Therefore, ensuring that network congestion will not happen in PSN during an emergency is becoming increasingly important. LTE-based PSN is easy to be congested because part of spectrum resources is compressed to guarantee priority requirements of public safety users. In this paper, we develop a new method namely Selective Admission Control (SAC) mechanism to manage the radio bearers access to the commercial radio for Public Safety (PS) in LTE-based PSN. In the case of emergency, we select the traffic bearer with minimum estimated load increment accessing to the LTE-based PSN. The channel quality of new bearers should be taken into account, which means that in congestion, users who arrive earlier with poor channel quality will be rejected to reserve sufficient resources for users who arrive later with good channel quality. The simulation results show that the SAC mechanism can improve throughput by 36% and lower the rejection rate by 73% at most than reference method based on non-selective access control model, as a result effectively avoiding the network congestion and improving the utilization of spectrum resources for public safety communication.

Xuesong Qiu

Papers

Multi-Cell Cooperative Outage Compensation in Cloud-RANs Based 5G Public Safety Network

Load-balancing based on Base-Station CoMP with guaranteed call blocking rate

Preventing Congestion by Selective Admission Control in LTE-Based Public Safety Network