Base Station Failures Research Articles

Post-earthquake functional state assessment of communication base station using Bayesian network

The reliability and resilience of communication base stations are critical to the post-earthquake performance of the communication system, and consequently influence the communication, rescue, and emergence management after an earthquake. There is a lack of models that can fully evaluate the post-earthquake functional states of base stations with the consideration of the dependencies between different components. This paper proposes a Bayesian network method to evaluate the post-earthquake functionality of communication base stations. The method considers the dependence between the equipment and its hosting building structure, and the impact of power outages. This model produces seismic functional fragility curves for typical base stations that enable both qualitative and quantitative evaluations of base station functionality. The model is validated using seismic damage data from the Ludian Earthquake. It was found that the proposed model can reasonably predict the post-earthquake functional failure of base stations, in good agreement with the observed seismic damage data. The application of this model provides support for the operation and maintenance of communication base stations, and insights for managing seismic risk and resilience of the communication system.

Spatio-Temporal Analysis and Prediction of Mass Telecommunication Base Station Failure Events

Large-scale telecommunication systems are lifeline infrastructure in modern society. A telecommunication system typically consists of a huge number of base stations with diverse geographical locations across a country, which highly complicates maintenance operations. To allocate maintenance resource properly, it is important to have a good understanding on the failure pattern of these base stations. Statistical inference of recurrent failures of these base stations is challenging because of the large number of base stations and the spatial correlation of their failure processes. Based on eight-month failure data of telecommunication base stations in Harbin, China, we propose a customized nonhomogeneous Poisson process (NHPP) model for recurrent failure data from telecommunication systems. The model consists of two layers, where the temporal layer applies an NHPP with station-specific frailty for failures of each base station, and the spatial layer uses a multivariate lognormal distribution to characterize the correlation among the frailties. The Monte Carlo EM (MCEM) algorithm is applied to estimate parameters included in the proposed model. We demonstrate the proposed model using the Harbin telecommunication system example with 7725 base stations and 4615 failure records.

Reliability prediction and evaluation of communication base stations in earthquake prone areas

One of the primary tasks for effective disaster relief after a catastrophic earthquake is robust communication. In this paper, we propose a simple logistic method based on two-parameter sets of geology and building structure for the failure prediction of the base stations in post-earthquake. Using the post-earthquake base station data in Sichuan, China, the prediction results are 96.7% and 90% for the two-parameter sets and all parameter sets, respectively, and 93.3% for the neural network method sets. The results show that the two-parameter method outweighs the whole parameter set logistic method and the neural network prediction and can effectively improve the accuracy of the prediction. The weight parameters of two-parameter set by the actual field data significantly show that the failure of base stations after earthquake is mainly due to the geological differences where the base stations are located. It can be envisioned that if the geological distribution between the earthquake source and the base station is parameterized, the multi-parameter sets logistic method can not only effectively solve the failure prediction after earthquakes and the evaluation of communication base stations under complex conditions, but also provide site selection evaluation for the construction of civil buildings and power grid towers in earthquake-prone areas.

Joint service placement and user assignment model in multi‐access edge computing networks against base‐station failure

AbstractMulti‐access edge computing (MEC) enables users to exploit the resources of cloud computing at a base station (BS) in proximity to the users where an MEC server is hosted. While we have advantage of being able to communicate with low latency and small network load in MEC networks, the resources in BSs are limited. One challenge is where to provide users with services from to make efficient use of resources. Furthermore, to enhance the reliability of MEC system, the case that a BS fails needs to be considered. This paper proposes a service placement and user assignment model with preventive start‐time optimization against a single BS failure in MEC networks. The proposed model preventively determines the service placement and user assignment in each BS failure pattern to minimize the worst‐case penalty which is the largest penalty among all failure patterns. We formulate the proposed model as an integer linear programming problem. We prove that the considered problem is NP‐hard. When the problem size becomes large, it may not be solved in a practical computation time. To solve larger size problems, we introduce two algorithms: one is the greedy algorithm with allocation upgrade and the other is with allocation upgrade and preemption. The results show that the introduced algorithms obtain solutions with smaller worst‐case penalty than the benchmark in a practical time.

Cell Edge User Capacity-Coverage Reliability Tradeoff for 5G-R Systems With Overlapped Linear Coverage

Fifth-Generation mobile networks for Railway (5G-R) is a promising train-ground communication solution to deal with the design challenges on ubiquitous connections and high reliability transmission for smart railways. Considering the linear coverage scenario along the railway lines, deep overlapping coverage can enhance the coverage reliability, but the capacity of cell edge users is plagued by severe inter-cell interference. In this paper, the fundamental performance of 5G-R systems with linear redundant coverage is investigated. We quantitatively analyze the impact of inter-cell interference on the capacity of cell edge users, in which the exponential effective signal to interference plus noise (SINR) mapping method is utilized to analyze SINR distribution of 5G-R users. Then, we investigate the coverage reliability considering the base station (BS) failure. Finally, taking cell edge user capacity as the optimization objective, we analyze the cell edge user capacity-coverage reliability tradeoff for 5G-R systems, and then provide useful insights into BS deployment for 5G-R systems through performance simulations and numerical results.

User-BS Selection Strategy Optimization with RSSI-Based Reliability in 5G Wireless Networks

Although fifth-generation (5G) wireless communication can ] support well a high data rate of transmission, issues such as base station (BS) failure and poor BS signals may cause serious interruption problems. This paper studies the user-BS selection strategy with received signal strength indication (RSSI)-based reliability in 5G wireless networks. First, reliability is defined on the basis of the RSSI and failure probability of the BS. The problem is modeled as a selection strategy optimization problem with BS capacity and receiving sensitivity as constraints. Second, the original problem can be transformed into a resource allocation problem with probabilistic constraints. For the situation where user distribution is known, we used dynamic programming to obtain the optimal BS selection strategy. For the situation where user distribution is unknown, starting from user trajectory data, we used the space–time density estimation method based on the Epanechnikov kernel to estimate user density and bring it into dynamic programming to obtain the optimal selection strategy. Simulation results show that our density estimation algorithm is more accurate than the commonly used density estimation algorithm. Compared with the distance-based optimization method, our RSSI-based optimization method also improved the communication signal quality under different scenarios.

RAN energy efficiency and failure rate through ANN traffic predictions processing

In this paper, we focus on the application of ML tools to resource management in a portion of a Radio Access Network (RAN) and, in particular, to Base Station (BS) activation and deactivation, aiming at reducing energy consumption while providing enough capacity to satisfy the variable traffic demand generated by end users. In order to properly decide on BS (de)activation, traffic predictions are needed, and Artificial Neural Networks (ANN) are used for this purpose. Since critical BS (de)activation decisions are not taken in proximity of minima and maxima of the traffic patterns, high accuracy in the traffic estimation is not required at those times, but only close to the times when a decision is taken. This calls for careful processing of the ANN traffic predictions to increase the probability of correct decision. Numerical performance results in terms of energy saving and traffic lost due to incorrect BS deactivations are obtained by simulating algorithms for traffic predictions processing, using real traffic as input. Results suggest that good performance trade-offs can be achieved even in presence of non-negligible traffic prediction errors, if these forecasts are properly processed. The impact of forecast processing for dynamic resource allocation on the BS failure rate is also investigated. Results reveal that conservative approaches better prevent BSs from hardware failure. Nevertheless, the deployment of newer devices, designed for fast dynamic networks, allows the adoption of approaches which frequently activate and deactivate BSs, thus achieving higher energy saving.

Improved Throughput Coverage in Natural Disasters: Unmanned Aerial Base Stations for Public-Safety Communications

Communications play an important role during public-safety operations. Because the current communication technologies heavily rely on the backbone network, the failure of base stations (BSs) due to natural disasters or malevolent attacks causes communication difficulties for public-safety and emergency communications. Recently, the use of unmanned aerial vehicles (UAVs), such as quadcopters and gliders, has gained attention in publicsafety communications (PSCs). They can be operated as unmanned aerial BSs (UABSs), which can be deployed rapidly as a part of the heterogeneous-network (HetNet) architecture. However, due to their mobile characteristics, interference management in the network becomes challenging.

A scalable architecture for handling control plane failures in heterogeneous networks

The separation between the control plane and the user plane is a key property of the newly proposed heterogeneous networks that will be widely deployed in 5G. In contrast to the failure of a small cell base station in the user plane which can be directly handled by the associated macrocell base station, the solution to handling a macrocell base station failure in the control plane is less investigated, in particular with regard to the signaling scalability issues of having all the affected small cell base stations directly communicate with the core network. In this article, we propose a small cell controller scheme for controlling and managing affected small cell base stations in a clustered fashion during the corresponding macrocell base station fail-over period. The advantage is to achieve substantial reduction of signaling overhead caused by user device handovers across small cell base station boundaries as compared to the existing solution, while maintaining comparable system performance. The proposed scheme is evaluated through realistic simulation studies and compared against the legacy scheme. The results clearly indicate that the proposed scheme can significantly reduce the signaling latency and processing load on the core network during the macrocell base station fail-over period.

Probabilistic Availability Quantification of PON and WiMAX Based FiWi Access Networks for Future Smart Grid Applications

Availability is one of the most important quality attributes for smart grid communications, as qualitatively defined in the IEEE P2030 standard. However, the availability metric must be quantified to validate given smart grid application requirements. In recent related work, availability has been quantified for wireless and optical backhaul networks in terms of communications reachability, while in some other work availability was not formally defined in a fine-grained manner and was assumed to be known. In this paper, we develop a novel multi-class probabilistic availability model for integrated passive optical network (PON) and WiMAX networks to quantify this metric according to medium access control (MAC) protocol limits as well as fiber and base station failures. The obtained numeric results show interesting availability behaviors, including the impact on availability depending on the number of base stations. We also investigate optical traffic re-routing through WiMAX when fiber faults occur and show that there exists a maximum amount of re-routed traffic for maximizing availability. Furthermore, we investigate a scenario of real-world smart grid traffic configurations shared with regular traffic and find the maximum sensor data rate to meet the availability requirements.

An integrated restoration framework for coverage and communication within wireless sensor networks

The paper presents a novel integrated framework to restore the coverage and communication failures within a wireless sensor network (WSN) without adding new resources. We view WSN as a collection of tree topologies, where each tree comprises of base station (BS) as a root, and the sensors as rest of nodes. The sensor/BS failures produce a disjoint set of sensors, thus generating coverage and communication issues simultaneously. We have formulated the restoration within WSN as an optimisation problem, where the objective function is to maximise the lifespan of WSN, subject to energy constraints. The restoration framework employs Simulated Annealing to select the best alternate neighbouring sensor/BS to restore the coverage and communication. The simulation results of a typical WSN with 26% sensor failures and 40% BS failures demonstrate the capability of our framework to maintain 100% communications for up to 200 days of operation than without utilising restoration.

Secure Network Recovery from Base Station Failure of Surveillance WSN in Hostile Environment

Securing surveillance wireless sensor networks (WSNs) in hostile environments such as borders, perimeters and battlefields during Base Station (BS) failure is challenging. Surveillance WSNs are highly vulnerable to BS failure. The attackers can render the network useless by only destroying the BS as the needed efforts to destroy the BS is much less than that is needed to destroy the network. This attack scenario will give the attackers the best chance to compromise many legitimate nodes. Previous works have tackled BS failure by deploying a mobile BS or by using multiple BSs. Despite the best electronic countermeasures, intrusion tolerance and anti-traffic analysis strategies to protect the BSs, an adversary still can destroy them. This paper proposes a novel security architecture called Surveillance Security (SurvSec) for secure and reliable network recovery from single BS failure of surveillance WSN with single BS. SurvSec relies on a set of sensor nodes serve as Security Managers for management and storage of the security related data of all sensor nodes. SurvSec security architecture provides methodology for choosing and changing the security managers of the surveillance WSN. SurvSec has four components: (1) Sensor nodes serve as Security Managers, (2) Data Storage System, (3) Data Recovery System, (4) Security for the Data Storage System. Furthermore, both the frame format of the stored data is carefully built and the security threats are encoded to allow minimum overheads for SurvSec security architecture. In this paper, we provide detailed specifications of SurvSec security architecture along with its security system for secure and reliable network recovery from single BS failure. We evaluate our designed security architecture for reliable network recovery from BS failure. Our evaluation shows that the proposed new security architecture can meet all the desiredspecifications and our analysis shows that the provided Security Managers are capable of network recovery from BS failure.

SurvSec: A New Security Architecture for Reliable Network Recovery from Base Station Failure of Surveillance WSN

Abstract Securing surveillance wireless sensor networks (WSNs) in hostile environments such as borders, perimeters and battlefields during Base Station (BS) failure is challenging. Surveillance WSNs are highly vulnerable to BS failure. The attackers can render the network useless by only destroying the BS as the needed efforts to destroy the BS is much less than that is needed to destroy the network. This attack scenario will give the attackers the best chance to compromise many legitimate nodes. Previous works have tackled BS failure by deploying a mobile BS or by using multiple BSs. Despite the best electronic countermeasures, intrusion tolerance and anti-traffic analysis strategies to protect the BSs, an adversary still can destroy them. This paper proposes a novel security architecture called Surveillance Security (SurvSec) for reliable network recovery from single BS failure of surveillance WSN with single BS. SurvSec relies on a set of sensor nodes serve as Security Managers for management and storage of the security related data of all sensor nodes. SurvSec security architecture provides methodologies for choosing and changing the security managers of the surveillance WSN. SurvSec has three components: (1) Sensor nodes serve as Security Managers, (2) Data Storage System, (3) Data Recovery System. Furthermore, both the frame format of the stored data is carefully built and the security threats are encoded to allow minimum overheads for SurvSec security architecture. In this paper, we provide detailed specifications of SurvSec security architecture. We evaluate our designed security architecture for reliable network recovery from BS failure. Our evaluation shows that the proposed new security architecture can meet all the desired specifications and our analysis shows that the provided Security Managers are capable of network recovery from BS failure.

A Distributed Topology Adjustment Algorithm for Wireless Networks with Mobile Base Stations

Improper static network topology can reduce the capacity of wide area wireless access networks in which the distribution of subscribers' population often changes. This paper focuses on "fully wireless cellular networks" with mobile base stations, where the network topology can be dynamic due to the mobility of the base stations. In such environment, network topology can be properly controlled by the adjustment of mobile base stations' positions. A novel distributed topology adjustment algorithm is proposed in this paper. The proposed algorithm tracks subscriber's population by moving mobile base stations toward the center of their nearby groups of subscribers. At the same time, mobile base stations are also drawn outward their neighboring base stations in order to solve the "oversupply base station" problem. The balance between 2 movement forces determines the proper position of mobile base stations. The performance evaluation of the proposed algorithm shows that the proposed algorithm performs well, even in rapidly changes of subscribers' population or in the presence of failure of base stations.

An efficient distributed fault‐tolerant protocol for dynamic channel allocation

AbstractRecent demand for mobile telephone services has been growing rapidly while the electromagnetic spectrum of frequencies allocated for this purpose remains limited. Any solution to the channel assignment problem is subject to this limitation, as well as the interference constraint between adjacent channels in the spectrum. The early research focused on the fixed channel allocation and centralized schemes. Recently, distributed channel allocation schemes have received much attention because of their high reliability and scalability. In these schemes, a base station (BS) has to consult with its neighboring BSs in order to assign a channel to a call. If it cannot communicate with its neighbors, it fails in allocating a channel. However, it is a common phenomenon that a BS fails in communicating with its neighboring BSs due to some reasons, such as heavy traffic load. In this paper, we propose a distributed fault‐tolerant channel allocation schemes which can work well under the mobile host (MH) failures, BS failures, and communication link failures. This algorithm is based upon the mutual exclusion model where the channels are grouped into three equal sized groups and each group of channels cannot be shared concurrently within the same cluster. We prove its correctness. We also report our algorithm's performance with several channel systems using different types of call arrival pattern through comparing with a popular generic distributed algorithm for channel allocation DDRA. Copyright © 2008 John Wiley & Sons, Ltd.

Survivability and performance optimization of mobile wireless communication networks in the event of base station failure

In this paper, we investigate the survivability of mobile wireless communication networks in the event of base station (BS) failure. A survivable network is modeled as a mathematical optimization problem in which the objective is to minimize the total amount of blocked traffic. We apply Lagrangean relaxation as a solution approach and analyze the experiment results in terms of the blocking rate, service rate, and CPU time. The results show that the total call blocking rate (CBR) is much less sensitive to the call blocking probability (CBP) threshold of each BS when the load is light, rather than heavy; therefore, the more traffic loaded, the less the service rate will vary. BS recovery is much more important when the network load is light. However, the BS recovery ratio (BSRR), which is a key factor in reducing the blocking rate for a small number of BSs, is more important when a system is heavily loaded. The proposed model provides network survivability subject to available resources. The model also fits capacity expansion requirements by locating mobile/portable BSs in the places they are most needed.

Strategies for combatting base station failure in highway microcellular clusters

Three strategies are presented for reducing the probability of hand-over failure when a microcellular base station fails in a highway microcellular cluster having an oversailing macrocell. Simulations show that the probability of new call blocking was unchanged, while the probability of hand-over failure decreased, although the SIR also decreased.