Deployment Of Relay Stations Research Articles

Throughput and coverage based Base Station–Relay Station deployment for 5G cellular network

SummaryFifth generation cellular networks have high data rates and connectivity demands. The relaying approaches are widely used in cellular networks to improve coverage, user throughput, and capacity at low cost. The increasing data requirements of the mobile network increase energy consumption. Energy efficiency‐based approaches also impact network coverage and throughput. Therefore, developing an energy‐efficient network with optimal coverage and throughput is considered a challenging issue. It can be resolved with optimal deployment of Base Station (BS), Relay Station (RS), and minimizing power consumption. In this research, a joint clustering‐based deployment technique is proposed for BS–RS deployment by considering the network throughput and coverage ratio. After enabling optimal BS–RS deployment, the network traffic is estimated with an On‐demand real‐time traffic estimation framework (ODTE). It estimates user association values using Beacon frames. In addition, the Relay Assisted Base station Power Scheduling (RABPS) approach to minimize power consumption is included. Based on Erlang's probability, the RABPS algorithm is enhanced with sleep mode activation during off‐peak hours. The proposed 5G network ensures uninterrupted connectivity and energy efficiency with varying time slots of power scheduling. The throughput performance of the clustering‐based approach is increased with a coverage ratio of 88%. The simulation results show the superiority of the proposed 5G BS–RS deployment and power scheduling in terms of throughput, coverage ratio, and power consumption.

Traffic based power consumption and node deployment in green LTE-A cellular networks

The energy utilization of green cellular networking or cellular network infrastructure has become a popular research domain due to the economic concern of network operators and global climate change. Also, due to the growth of wireless networks, the authors are attracted to finding novel relay station (RS) deployment techniques to support high user density and high data rate services by reducing energy consumption and operating costs of different network elements. The location of RSs greatly influences how far a cell can be covered. Therefore, the deployment RS plays a major role in widening the cell's coverage radius. To solve these challenges and to realize greener network designs by maximizing power consumption with QoS assurance, a novel traffic-based power consumption minimization and node deployment for the LTE green cellular networks is proposed. Also, key performance indicators (KPIs) are required to monitor and improve network performance. KPIs control the accomplished resource utilization and the quality of services. The research work comprises RS deployment, traffic estimation, and power allocation. Power losses, communication delays, increased implementation costs, and decreased throughput are the effects of an inappropriate RS deployment. Therefore, this research introduces the transmission area-based relay stations deployment scheme (TARSD) with multiobjective functions maximization of coverage area, minimization of the overlapping area and the minimization of power consumption cost. Traffic estimation helps to identify future capacity requirements and enables improved planning and decision-making. The deployment scheme of a cellular network relies on network traffic estimation. Nash traffic entropy learning algorithm (NTEL) is used to estimate traffic, and based on the estimated eNB switching ON/OFF is performed to minimize power consumption. Inter cell interference (ICI) can impact the performance of the LTE network. Several power allocation schemes can be used to improve system performance to achieve the optimal trade-off between interference and signal-to-noise ratio (SINR). Because of its good performance and efficacy in improving the mutual information between a channel's input and output, the enhanced low complexity water-filling (ELCWF) has been widely employed in power allocation with its increment and decrement properties. This research studies the statistical behaviour of a Received Signal Strength Indicator (RSSI), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ) and Signal to Interference noise Ratio (SINR). Also, statistical analysis of cost versus coverage performance is examined. Under the 7th simulation run, the proposed method yields the best coverage of 88.81 and 98.74%, respectively. In the experimental scenario, for the proposed model, the deployment cost for BS and RS are 27 and 13 units, the average throughput per user is 9.74 Mbps, and the coverage ratio is 97% under the BS candidate location of 20, respectively. In the power allocation stage, if the number of users is 50, the proposed model yields a power consumption of 0.2 W, throughput of 23.4 Mbps, delay of 15 ms and SINR of 20.12 dB, respectively.

Survey on UAV Deployment and Trajectory in Wireless Communication Networks: Applications and Challenges

A new era of the fifth-generation (5G) networks is realized to satisfy user demands on higher data rate and massive connectivity for information sharing and utilization. The vertical applications such as vehicle-to-everything (V2X) communications, industrial automation, smart factory, smart farm and smart cities require ultra-fast communications and wide service range. Coverage extension is a key issue to support the required demands on higher performance, but requires an additional deployment of base or relay stations. Therefore, an efficient solution needs to be cost-effective and easy, in order to deploy more stations. An unmanned aerial vehicle (UAV) has been considered as a candidate to overcome these issues because it is much more cost-effective than the ground stations and does not require network or cell replanning, thereby enhancing the network coverage without additional excessive deployment procedures of the existing networks. UAVs will play important roles in 5G and beyond networks assisting as macro base stations, relay stations, small cells, or a moving aggregator. The performance of UAV wireless networks highly depends on the position or the trajectory of UAVs and the resource managements of entire networks. Recently, there have been extensive studies on performance analysis, UAV deployment, UAV trajectory and resource management of UAV wireless networks to achieve the required demands on performance. This paper surveys research conducted for the UAV deployment and trajectory to construct UAV wireless networks for the coverage extension, the throughput improvement and the resource management for different use cases and scenarios, so as to encourage further studies in this area.

Relay Positioning for Load-Balancing and Throughput Enhancement in Dual-Hop Relay Networks.

In a cellular communication system, deploying a relay station (RS) is an effective alternative to installing a new base station (BS). A dual-hop network enhances the throughput of mobile stations (MSs) located in shadow areas or at cell edges by installing RSs between BSs and MSs. Because additional radio resources should be allocated to the wireless link between BS and RS, a frame to be transmitted from BS is divided into an access zone (AZ) and a relay zone (RZ). BS and RS communicate with each other through the RZ, and they communicate with their registered MSs through an AZ. However, if too many MSs are registered with a certain BS or RS, MS overloading may cause performance degradation. To prevent such performance degradation, it is very important to find the proper positions for RSs to be deployed. In this paper, we propose a method for finding the sub-optimal RS deployment location for the purpose of load-balancing and throughput enhancement. The advantage of the proposed method is the efficiency in find the sub-optimal location of RSs and its reliable tradeoff between load-balancing throughput enhancement. Since the proposed scheme finds the proper position by adjusting the distance and angle of RSs, its computational complexity lower than other global optimization approach or learning-based approach. In addition, the proposed scheme is constituted with the two stages of load-balancing and throughput enhancement. These procedures result in the appropriate tradeoff between load-balancing and throughput enhancement. The simulation results support these advancements of the proposed scheme.

Energy efficiency based on relay station deployment and sleep mode activation of eNBs for 4G LTE-A network

ABSTRACT The energy efficiency is considered as a major issue due to large power consumption of eNBs in heterogeneous cellular networks. In this paper, a novel relay station (RS) deployment scheme and base station (BS) sleep mode algorithm is proposed to minimize the power consumption of eNBs. Initially, the RSs are deployed to cover the entire area of a cell. It is due to the purpose of providing service when the BS is in sleep mode. Then the network traffic of each cell is measured with Erlang B and C probability measure. If the network traffic is low, then the BS is decided to put into sleep mode which reduces the power consumption. For that, the corresponding RS are selected to handover the active mobile users (MUs). Then, the network traffic is estimated for each RS and the RS without MU becomes sleep mode in order to reduce power consumption further. The proposed model of cellular network reduces the power consumption by applying sleep mode algorithm for both BS and RS based on the measured network traffic. The power consumed by the entire network is measured and compared with the network without sleep mode. The evaluation results show the efficiency of our proposed work.

Placement of Relay Stations in WiMAX Network Using Glowworm Swarm Optimization

The Relay Station (RS) deployment problem for WiMAX networks is studied. Unlike Base Station (BS), RS does not need a wire-line backhaul and has much lower hardware complexity. Hence, usage of RSs can significantly minimize the deployment cost and maximize the network coverage of the system. To solve the RS deployment problem, the authors have used a nature inspired technique known as Glowworm Swarm Optimization (GSO). Different cases have been considered for a single fixed BS, to find the feasible number of RSs and its optimal placement in WiMAX networks. Computational experiments are conducted to show the effect of RS deployments in different distribution scenarios. This article also shows the impact of placing RSs at optimal locations to serve given Mobile Stations (MSs) that are distributed arbitrarily in a given geographic region such that the cost is minimized, and the network coverage is maximized. The results obtained from the GSO algorithm are compared with k-means algorithm and it is observed that GSO performs better than k-means algorithm.

Dynamic Base Station or Relay Station deployment and small cell On/Off strategy for green ultra dense networks

Due to tremendous advancements in technologies to make the human tasks easier,users are highly dependent on these applications and it has reached a scenario that they are not ready to compromise delay or issues in connectivity. So it becomes the very need of the mobile operators that they should develop a model to satisfy customer needs. In next generation networks,ultra dense small cellular networks are emerging to deal with this increasing traffic. However increasing the number of Base Stations may increase the Energy Consumption and reduce the Efficiency. Therefore,In this paper we develop model which considers both Energy Consumption and Efficiency. This can be stated as 2 sub problems:Dynamic Deployment of Base Station or Relay Station at the centroid depending on the user distribution and Dynamic small cells On/Off approach to reduce the unwanted energy consumption of under utilized cells. This paper also examines a comparison between the existing system and some of the modified systems in terms of Energy Consumption,Efficiency,Complexity and Cost. Simulation results shows that the Energy Consumption can be reduced up to 14% and Efficiency can be increased up to 87.5%.

Range Extension in IEEE 802.11ah Systems Through Relaying

A great number of Internet of Things (IoT) and machine-to-machine (M2M) based applications require energy efficient, long range and low data rate wireless communication links. In order to offer a competitive solution in these areas, IEEE 802.11 standardization group has defined the "ah" amendment, the first sub-1GHz WLAN standard, with flexible channel bandwidths, starting from 1MHz, up to 16MHz, and many other physical and link layer improvements, enabling long-range and energy efficient communications. However, for some regions, like Europe, the maximum transmitted power in dedicated frequency band is limited to only 10mW, thus disabling the achievement of ranges which would be close to targeted of up to 1km. In this paper we examine possibilities for range extension through implementation of half-duplex decode-and forward (DF) relay station (RS) in communication between an access point (AP) and an end-station (ST). Assuming a Rician fading channel between AP and RS, and a Rayleigh fading channel on the RS-ST link, we analytically derive results on achievable ranges for the most robust modulation and coding schemes (MCSs). Analyses are performed for two different standard adopted deployment scenarios on the RS-ST link. Moreover, we have analyzed whether the considered most robust MCSs, known for supporting the longest range, but the lowest data rates, can meet the defined requirement of at least 100kb/s for the greatest attainable AP-RS-ST distances. We examine data rate enhancements, brought by coding and using of short packets, for both downlink (DL) and uplink (UL). Finally, we present bit error rate (BER) results, obtained through simulations of a dual-hop DF IEEE 802.11ah relay system for the considered MCs. All presented results confirm that IEEE 802.11ah systems, through deployment of relay stations, become an interesting solution for M2M and IoT based applications.

Power-aware fuzzy based joint base station and relay station deployment scheme for green radio communication

In recent years, green wireless communication has received much attention of industrial and academic communities due to its ability to create eco-friendly power efficient networks. To support anytime-anywhere seamless broadband services to all mobile subscribers, more number of macro base stations (BSs) have to be deployed. The macro BSs are power inefficient and also responsible for large carbon dioxide (CO2) emissions. The increase in the number of macro BSs will also increase the system cost and interference. The concept of multi-hop relay network has been widely discussed in long term evolution-advanced (LTE-A) standard, where the low power relay stations (RSs) are also deployed along with the macro BS to address the coverage and capacity issues. However, improper BS and RS deployment introduces power inefficiency, transmission delay, huge deployment cost and reduced throughput. Many of the conventional deployment schemes require iterative and complex computation. These deployment schemes are not eco-friendly and do not sustain for all channel conditions. In this work, we have proposed an eco-friendly, power-aware, fuzzy based BS and RS deployment algorithm to maximize the coverage and capacity of the system. Unlike the conventional methods, a new parameter called power consumption effectiveness ratio, which accounts for the greenness of the network is proposed and included in the fuzzy based decision making process along with the coverage ratio and traffic ratio. The simulation results prove that the proposed scheme is superior over the conventional uniform clustering and fuzzy based schemes. Further the proposed scheme is more suitable candidate for power-aware green radio communication.

Energy-efficient joint BS and RS sleep scheduling in relay-assisted cellular networks

The deployment of relay stations (RSs) offers a promising and viable approach to satisfy the increasing need of high data rate in cellular networks. With the expected increase of the number of RSs, the energy efficiency (EE) becomes a crucial system design parameter. One of the most effective energy saving methods is to switch off some stations. In this paper, joint base station (BS) and RS sleep scheduling algorithms are investigated in relay-assisted cellular networks. We aim to maximize the EE of the relay-assisted cellular networks under the spectral efficiency (SE) constraint. First, we establish a mathematical model which is a mixed integer nonlinear fractional programming problem. To solve it with globally optimal solution, a branch and bound (BnB) algorithm based on the denominator interval values of the objective function is designed and its convergence is proved theoretically. Then, two kinds of sub-optimal algorithms are proposed to compare with the optimal algorithm: one is a greedy algorithm and the other is based on the Cellular Automata (CA) theory. Simulation results are presented to demonstrate the effectiveness of our algorithms.

A Novel Relay Station Deployment Scheme for beyond 4G Multi-hop Network

In Long Term Evolution-Advanced (LTE-A) and Worldwide interoperability for microwave access (WiMAX) systems, the coverage area, signal strength and transmission quality are affected by white Gaussian noise, shadowing, wireless interference etc. This effect can be decreased by using more number of evolved NodeBs (eNB), but problem is that eNBs are expensive and it will increase network cost. Relay Stations (RS) are less expensive than eNBs, hence we go for RS deployment instead of eNBs. Thus this paper proposes a cost effective deployment of RSs using dynamic cost based deployment of RS (DCDR) approach. This approach first analyse the impact parameters and then finds the dynamic weighting and network cost for different deployment combination. Simulation result shows that DCDR approach gives a cost effective solution for the deployment of RSs.

A Quality-Aware Relay Station Deployment Scheme for Green Radio Communication

A Quality-Aware Relay Station Deployment Scheme for Green Radio Communication

Optimal location planning of relay-based next generation wireless access networks

Use of relays is considered one of the most effective ways for capacity enhancement and coverage extension in next-generation broadband wireless access networks (BWAN). The paper investigates the location planning problem in BWANs, aiming at an optimal deployment of relay stations and base stations to enhance capacity. We develop formulations in mixed integer linear programming to effectively capture various planning policies that govern relay and base station placement. Case studies are conducted to verify the effectiveness of the proposed formulations. We show that the same traffic demand can be satisfied with up to 73 % fewer relay stations with a slight (6 %) decrease in the overall network capacity, compared with our benchmark. Based on the developed formulations, we introduce a maximin objective function to properly distribute excess bandwidth to all subscriber stations rather than assigning it to a single one, which surprisingly leads to a significant gain in the rate allocated to each subscriber station.

Energy-Efficient Base Station Sleep Scheduling in Relay-Assisted Cellular Networks

We Relay-assisted cellular network architecture has been developed to cover cell-edge users and to improve capacity. However, the deployment of relay stations (RSs) in cellular networks may increase the total energy consumption. Though energy efficiency has become a major concern in cellular networks, little work has studied the energy efficiency of relay-assisted cellular networks by sleep scheduling. In this paper, a distributed base stations (BSs) sleep scheduling scheme in relay-assisted cellular networks is proposed. The goal is to maximize the energy efficiency under the spectral efficiency constraint. Firstly, whether the BSs should be sleeping or active is determined by the traffic profile. Then, the transmission powers of the active BSs are optimized within the game-theoretic framework, by using an interior-point method, so as to maximize the energy efficiency. Simulation results demonstrate that the effectiveness of the proposed scheme is superior to that turning on all the BSs without sleep scheduling.

Analyses of Relay Nodes Deployment in 4G Wireless Mobile Multihop Relay Networks

In 4G cellular networks: LTE/LTE-Advanced and the mobile WiMAX network, some key impact factors: white Gaussian noise, wireless interference, shadow fading, etc., degrade signal transmission quality and reduce wireless service coverage significantly. The degradations can be improved by deploying more eNBs or BSs, but the expensive eNB/BS extremely increases network cost. The specifications of LTE-Advanced and IEEE 802.16j thus propose a relay-based scheme, namely mobile multihop relay (MMR) networks, to cooperate with the existing cellular network while not obviously increasing the relay station (RS) deployment cost. Various types of RSs: Fixed RS, Nomadic RS and Mobile RS, can be adopted in MMR networks. To efficiently deploy different types of RSs becomes a critical issue. Thus, this paper first analyzes the impact factors: transmission quality, deployment price, service coverage and RS overlap index, and then models the cost-effective issue of the RS deployment as an optimization problem. The paper proposes an adaptive cost-based RS deployment (ACRD) approach to form a cost function in terms of all impact factors, and then solves the optimization problem by determining the RS deployment with the least network cost as the solution. Numerical results demonstrate that ACRD outperforms the compared approaches in network cost, transmission quality, RS deployment price, service coverage, and RS overlap index. Additionally, ACRD deploys more RSs on the areas with high-density populations and thus increases transmission quality and guarantees the quality of service (QoS). Finally, the worst case running time of ACRD is analyzed, which requires $$ T(n) = O(I \cdot P) $$T(n)=O(I·P).

A cluster-based relay station deployment scheme for multi-hop relay networks

Multi-hop relay networks have been widely considered as a promising solution to extend the coverage area and to reduce the deployment cost by deploying the relay stations (RSs) in mobile communication systems. Suitable deployment for the RSs is one of the most important features of the demand nodes (DNs) to obtain a high data transmission rate in such systems. Considering a tradeoff among the network throughput, the deployment budget, and the overall coverage of the systems, efficient RS deployment schemes and corresponding algorithms must be developed and designed. A novel cluster-based RS deployment scheme is proposed in this paper to select the appropriate deployment locations for the relay stations from the candidate positions. To make an ideal cluster distribution, the distances between the DNs are calculated when deploying the RSs. We take into account the traffic demands and adopt a uniform cluster concept to reduce the data transmission distances of the DNs. On the basis of the different candidate positions, the proposed scheme makes an adaptive decision for selecting the deployment sites of the RSs. A better network throughput and coverage ratio can be obtained by balancing the network load among the clusters. Simulation results show that the proposed scheme outperforms the previously known schemes in terms of the network throughput and the coverage ratio. Additionally, a suitable deployment budget can be implemented in multi-hop relay networks.

Techniques to Enhance the Quality of Service of Multi Hop Relay Networks

Broadband internet access through the user equipment has become the hot research topic. The shadowing and multipath issues restrict the high performance nature of 4G cells. In Multi hop Relay (MHR) networks, Relay Stations (RS) are introduced to improve coverage and capacity of the system. There exist some issues like path selection and RSs deployment, which severely affects the Quality of Service (QoS) of the system. In this paper, to improve the QoS of MHR networks, Load Aware Routing Metric (LARM) based path selection and a low complex Burst Profile (BP) based RS deployment schemes are discussed.

Multihop relaying for broadband wireless access systems at 800 and 3500 MHz in rural areas

AbstractThis paper addresses the coverage enhancement for broadband wireless access (BWA) at 800 and 3500 MHz in a rural scenario in north Germany using multi‐hop relay concepts. The investigation is divided into two phases: In phase I, the coverage of a single BWA system in a rural area is predicted and verified with measurement data. In phase II, the coverage from the BWA system is analyzed and enhanced through the deployment of relay stations. The number of relay stations required for each carrier frequency is determined, and the positions of the relay stations are identified via three different relay placement algorithms, namely path‐loss‐based, distance‐based, and hybrid algorithms. At 800 MHz, the path‐loss‐based algorithm requires seven relay stations to achieve an overall coverage of 95%. The hybrid and distance‐based algorithms require 11 and 14 relay stations, respectively, to achieve the same coverage. At 3500 MHz, path‐loss based and hybrid algorithms require 19 and 16 relay stations, respectively, to achieve the same coverage. The distance‐based requires 20 relay stations to achieve an overall coverage of 82%. Further increase of relay stations has led to higher interference. Lastly, the transmit power of the relay station is optimized via an intelligent power allocation scheme. The results show that 20% of the total transmit powers from 14 relay stations can be saved at 800 MHz whereas 18% of the total transmit powers from the 20 relay stations can be saved at 3500 MHz.

A Nonstationary Wideband MIMO Channel Model for High-Mobility Intelligent Transportation Systems

The recent development of high-speed trains (HSTs), as a high-mobility intelligent transportation system, and the growing demands of broad-band services for HST users, introduce new challenges to wireless communication systems for HSTs. The deployment of mobile relay stations on top of the train carriages is one of the promising solutions for HST wireless systems. For a proper design and evaluation of HST wireless communication systems, we need accurate channel models that can mimic the underlying channel characteristics for different HST scenarios. In this paper, a novel nonstationary geometry-based stochastic model (GBSM) is proposed for wideband multiple-input multiple-output HST channels in rural macrocell scenarios. The corresponding simulation model is then developed with angle parameters calculated by the modified method of equal areas. Both channel models can also be used to model nonstationary vehicle-to-infrastructure channels in vehicular communication networks. The system functions and statistical properties of the proposed channel models are investigated based on a theoretical framework that describes nonstationary channels. Numerical and simulation results demonstrate that the proposed channel models have the capability to characterize the nonstationarity of HST channels. The statistical properties of the simulation model, verified by the simulation results, can match those of the proposed theoretical GBSM. An excellent agreement is achieved between the stationary intervals of the proposed simulation model and those of relevant measurement data, demonstrating the utility of the proposed channel models.

On the Optimization of Deployed Positions for Fixed Relay Stations in a LTE Cooperative Network

Abstract The Fixed Relaying technique is presented as the most mature cooperative technique. This technique aims at increasing the network coverage and/or capacity. In addition, this technique brings economic benefits to the Mobile Network Operators (MNOs). The aim of this paper is to develop a Fixed Relay Station (FRS) deployment algorithm, taking into account the number of used FRSs and considering a multi-cell environment. The goal of the algorithm is to find a FRS deployment pattern for each cell, taking into account the FRSs positions in each cell of the cluster, minimizing the FRS-FRS inter- and intra-cell interference. Using the algorithm implementation, this paper investigates the number of FRSs which should be used in each cell. The achieved results suggest that the ideal number of used FRS per cell is 12. In this case, the algorithm increased 32% and 82% the User Equipment (UE) throughput and its Signal-to-Interference plus Noise (SINR) at the cell edge, respectively.