Macro Stations Research Articles

Conflict-Free Parallel Data Access Technology for Matrix Calculation in Memory System of ASIP of 5G/6G Macro Base Stations

Among the physical layer baseband algorithms in macro base stations, the matrix processing has the dom-inant computing cost, large data access overhead and com-plicated addressing mode. The existing data access methods are not the best solution for memory system of ASIP (Ap-plication Specific Instruction Set Processor) in 5G/6G macro stations. We hence proposed a parallel conflict-free data access method for matrix. Moreover, we proposed a non-redundant access method for positive definite matrix that stores only trigonometric part, and the corresponding parallel addressing method with low storage overhead. Our method solves the problem of data conflict and minimizes the memory space of ASIP, and supports ASIP to approach the performance limit of architecture to the maximum ex-tent under the constraint of architecture and data parallel-ism. We implemented the proposed method as a static memory optimizer, which provides a tool for the design and optimization of memory system of ASIP in 5G/6G macro base stations with low overhead. Experimental results show that for 64W64 positive definite matrix inversion algorithm based on Cholesky decomposition, our addressing method can save 32% of the execution time, and the cost of memory space is reduced by half.

Base Station Planning Based on Region Division and Mean Shift Clustering

The problem of insufficient signal coverage of 5G base stations can be solved by building new base stations in areas with weak signal coverage. However, due to construction costs and other factors, it is not possible to cover all areas. In general, areas with high traffic and weak coverage should be given priority. Although many scientists have carried out research, it is not possible to make the large-scale calculation accurately due to the lack of data support. It is necessary to search for the central point through continuous hypothesis testing, so there is a large systematic error. In addition, it is difficult to give a unique solution. In this paper, the weak signal coverage points were divided into three categories according to the number of users and traffic demand. With the lowest cost as the target, and constraints such as the distance requirement of base station construction, the proportion of the total signal coverage business, and so on, a single objective nonlinear programming model was established to solve the base station layout problem. Through traversal search, the optimal threshold of the traffic and the number of base stations was obtained, and then, a kernel function was added to the mean shift clustering algorithm. The center point of the new macro station was determined in the dense area, the location of the micro base station was determined from the scattered and abnormal areas, and finally the unique optimal planning scheme was obtained. Based on the assumptions made in this paper, the minimum total cost is 3752 when the number of macro and micro base stations were determined to be 31 and 3442 respectively, and the signal coverage rate can reach 91.43%. Compared with the existing methods, such as K-means clustering, K-medoids clustering, and simulated annealing algorithms, etc., the method proposed in this paper can achieve good economic benefits; when the traffic threshold and the number of base stations threshold are determined, the unique solution can be obtained.

Research on Base Station Site Planning Based on Cluster Analysis and Azimuth Analysis Model

With the rapid development of the information age, the construction of 5G mobile network has improved the speed of network transmission and the utilization rate of spectrum. However, at the same time, the coverage of base stations is correspondingly less and less. In order to improve the quality of mobile communication, this paper uses the normal distribution 3-standard deviation method, Euclidean distance and 0-1 planning site selection model to analyze and divide the macro and micro base stations and make the optimal solution of site planning. Furthermore, the azimuth analysis model and K-means clustering algorithm were used to optimize the site planning and coverage area. Finally, 331 macro stations and 6459 micro base stations needed to be built, with an optimized Angle of 47 degrees and a coverage area of 93.3%. This paper provides some reference ideas for solving the problem of selecting and planning the base station site in the communication network.

Research on Penetration Loss of D-Band Millimeter Wave for Typical Materials.

The millimeter-wave frequency band provides abundant frequency resources for the development of beyond 5th generation mobile network (B5G) mobile communication, and its relative bandwidth of 1% can provide a gigabit-level communication bandwidth. In particular, the D-band (110–170 GHz) has received much attention, due to its large available bandwidth. However, certain bands in the D-band are easily blocked by obstacles and lack penetration. In this paper, D-band millimeter-wave penetration losses of typical materials, such as vegetation, planks, glass, and slate, are investigated theoretically and experimentally. The comparative analysis between our experimental results and theoretical predictions shows that D-band waves find it difficult to penetrate thick materials, making it difficult for 5G millimeter waves to cover indoors from outdoor macro stations. The future B5G mobile communication also requires significant measurement work on different frequencies and different scenarios.

Aviation Data Lake: Using Side Information to Enhance Future Air-Ground Vehicle Networks

Future denser air-ground vehicle networks (AGVNs) face challenges such as resource allocation, mobility management, secure transmission, and so on. At the same time, surveillance is a must for modern air traffic management. This motivates us to find opportunities in the aerial vertical by forming a conceptual surveillance plane for aerial vehicles. In this article, we propose an enhanced software-defined network architecture where the surveillance plane can provide local and global surveillance information to macro stations, acting as a side system for the communication links. We review air- ground communications and, by summarizing challenges and opportunities, propose the enhanced architecture of side-information-assisted networks in detail. We then present how we obtain, organize, manage, and utilize the local and global side information by a so-called aviation data lake (ADL). The data lake can be easily connected with advanced machine learning schemes and, thus, provide timely, context-aware metrics and predictions.

Congestion Control of Multi-layer Cellular Networks based on Modeling of Transmit Power

The explosive growth of network traffic and the limited storage node resources make the existing network architecture bear great pressure, and network congestion appears in work and life from time to time. In order to ensure the timeliness and effectiveness of the network, we propose a congestion control method based on transmission power. Different from previous work, we built a multi-layer cellular network consisting of multiple macro stations, small base stations and mobile terminals. On this basis, we establish a congestion control model based on the mixed queuing model of service window and calculate the input/output rate and congestion. Finally, we use simulation to verify the effectiveness of the congestion model. The network builder can use our model to set the appropriate power of macro stations and small base stations to ensure network stability.

A New Coalition Formation Approach for Power Losses Reduction in Electrical Power Micro-Grids

In recent years, the technology of micro-grids (µGs) has gained a lot of interest. µGs utilize distributed generators (DGs) to locally meet the needs of consumers. This decentralized nature increases the efficiency of the system in addition to improving the electrical service reliability. In this paper, coalitional game theory is used to study the process of local power exchange among a set of µGs. A coalition forming (CF) algorithm which depends on the topology of the network is proposed. The presented algorithm is scalable i.e. can capture a substantial number of µGs which makes it applicable in real systems. Besides the macro-station (MS), each formed coalition comprises a set of µGs with a lack of power to purchase and a set of µGs that have an excess of power to sell. Within each coalition, quadratic programming (QP) is used to organize the transition of power among µGs and MS so as to reduce the power losses. To illustrate the significant impact of the presented procedure, a full numerical example is introduced. The analysis and simulation show that the proposed algorithm results in a decrease in the average power losses per bus, reaching up to 37.6% enhancement compared with the non-cooperative situation.

RETRACTED ARTICLE: Adaption of 5G networks in industrial sector with improved bandwidth utilization

The newly arrived Software Defined Network (SDN) has been adapted to industry standards. By defining Software Defined Air Interface (SDA) would support achieving higher data rate and utilization of bandwidth. The growing use of internet in industrial sector has claimed higher bandwidth conditions. To provide sufficient bandwidth support for the industrial networks, the fifth generation network has been emerged. The industrial sector utilizes the internet communication for variety of purpose where the bandwidth of the connections needs higher values. They involve in accessing different resources located in different geographic location where the latency of communication should be less and they need to transfer huge amount of data which requires higher bandwidth conditions. However, the increased growth of internet usage has introduced huge challenge for the service providers in handling higher data rate solutions. However different opinions are generated toward 5G network design, still there is no blue print has been arrived. Towards the growth of 5G networks and for the improved performance of data rate maintenance, a novel software defined air interface has been proposed in this paper. The presence of macro cells and small cells supports the higher data rate. Each small cell has been fabricated with number of MIMO which is located in different locations of the network in dense. The software defined interface is capable of selecting optimal macro station or small cell for betterment of data transmission. The interface designed monitor the network conditions and estimates bandwidth utilization support (BUS) and data rate maintenance support (DMS) for different small cells located in different geographic location. The SDA designed is responsible for the selection of small cell, MIMO to maintain the data rate. The proposed method improves the performance of bandwidth utilization and data rate maintenance.

Cooperative energy management system for networked microgrids

Abstract This paper proposes a hybrid Energy Management Systems (EMS) architecture based on canonical coalition games for cooperative power exchange management of networked microgrids, interconnected with the main grid through a macro station. A central EMS and local EMSs perform three main processes: scheduling process, monitoring and rescheduling process, and benefits distribution process. A value function verifying the superadditivity property, which guarantees the grand coalition is the best coalition structure, and a computationally efficient non-linear scheduling model, which allows obtaining the power exchange strategy that minimizes transmission and transformation power losses, are defined. The scheduling process uses the scheduling model to generate a cooperative schedule for a rolling horizon. In order to enhance the performance of networked microgrids, the monitoring process uses efficiency thresholds for monitoring the schedule execution to identify schedule disruptions. For preserving the private information of microgrids, each local EMS only informs the central EMS of their state profiles, which specifies its power surplus or deficit for each time period of the scheduling horizon. The benefit-distribution process uses a Core-based model for distributing saved power loss obtained as a result of the power exchanged during the schedule execution. By comparing the proposed approach with a coalition formation game-based algorithm recently reported in the literature, it is concluded that the problem of power exchange management of networked microgrids should be modeled as a canonical coalition game and not as a coalition formation game. Results obtained from a prototype testing of the proposed EMS are presented.

GT-CFS: A Game Theoretic Coalition Formulation Strategy for Reducing Power Loss in Micro Grids

In recent years, research attention on smart grid comprising distributed power generators has increased. To produce electricity in the smart grid, many micro grids (MGs) may exploit various renewable energy resources. Because the production capacity of renewable resources cannot be controlled, the MGs often require the power plants to provide power for them. However, the power loss between each MG and the power plant is larger than that among the MGs. To alleviate this power loss, we propose a game theoretic coalition formulation strategy for the MGs dubbed GT-CFS. Our proposed GT-CFS allows the MGs (belonging to the same macro station (MS)) to autonomously cooperate and self-organize into a partition composed of disjoint MG coalitions. Also, GT-CFS enables the MGs, in a distributed manner, to decide whether they will remain in the coalitions or not upon environmental changes, e.g., the variation of the power demand of the MGs. Within every coalition, MGs coordinate the power transfer among themselves as well as with the MS, in a fashion to optimize a utility function, which captures the total losses over the power distribution lines. MGs in the same coalition will distribute the extra profits (i.e., payoff) produced from forming coalitions by their “Shapley value.” Through computer simulations, we demonstrate that the proposed GT-CFS reduces the average power loss per MG significantly in contrast with the conventional noncooperative approach.

On Optimally Reducing Power Loss in Micro-grids With Power Storage Devices

Chapter 5 described a strategy to allow the micro grids to make coalitions and exchange power with other micro grids and/or the macro station. In this chapter, we are going to carry on from that strategy and enhance the model further by considering micro grids to use power storage devices. Recently, the micro grid developers and operators are exhibiting a great deal of interest in using lithium-ion batteries and flow batteries. The battery technologies have become quite mature and they are currently capable enough to provide exceptional renewable power integration in the micro grids based energy systems [1, 2]. In [3], it was demonstrated how the storage devices can supplement energy generation to consumption to achieve a balance between energy demand and supply within the micro grid. Necessity of optimal control of the power storage devices of the micro grid was also indicated in [3]. A new photovoltaic power generation and load power consumption prediction algorithm was designed in [4] which was specifically designed for a residential storage controller. However, these existing works usually focused on a single micro grid and did not consider the power losses impacting the entire system including the macro station and multiple micro grids. Instead, they had a localized approach such as how to reduce the power loss within a given micro grid, how to charge and discharge the storage device periodically, and so forth. In this chapter, we adopt a different approach by focusing on a scalable total power loss minimization approach across the entire smart grid.

Waves of intermediate length through an array of vertical cylinders

We report a semi-analytical theory of wave propagation through a vegetated water. Our aim is to construct a mathematical model for waves propagating through a lattice-like array of vertical cylinders, where the macro-scale variation of waves is derived from the dynamics in the micro-scale cells. Assuming infinitesimal waves, periodic lattice configuration, and strong contrast between the lattice spacing and the typical wavelength, the perturbation theory of homogenization (multiple scales) is used to derive the effective equations governing the macro-scale wave dynamics. The constitutive coefficients are computed from the solution of micro-scale boundary-value problem for a finite number of unit cells. Eddy viscosity in a unit cell is determined by balancing the time-averaged rate of dissipation and the rate of work done by wave force on the forest at a finite number of macro stations. While the spirit is similar to RANS scheme, less computational effort is needed. Using one fitting parameter, the theory is used to simulate three existing experiments with encouraging results. Limitations of the present theory are also pointed out.