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With the substantial increase in spatio-temporal mobile traffic, reducing the network-level energy consumption while satisfying various quality-of-service (QoS) requirements has become one of the most important challenges facing six-generation (6G) wireless networks. We herein propose a novel multi-agent distributed Q-learning based outage-aware cell breathing (MAQ-OCB) framework to optimize energy efficiency (EE) and user outage jointly. Through extensive simulations, we demonstrate that the proposed MAQ-OCB can achieve the EE-optimal solution obtained by the exhaustive search algorithm. In addition, MAQ-OCB significantly outperforms conventional algorithms such as no transmission-power-control (No TPC), On-Off, centralized Q-learning based outage-aware cell breathing (C-OCB), and random-action algorithms.

At present, 5G mobile traffic base stations in energy consumption accounted for 60% ~ 80%, compared with 4G energy consumption increased three times. In the future, high-density overlapping heterogeneous cellular network architecture means more base station deployment. When the transmission rate increases by 10-100 times, low cost and low energy consumption become the key. This paper proposes a power control algorithm based on energy efficiency, which combines cell breathing technology and base station sleep technology to reduce base station energy consumption on the premise of ensuring the quality of communication. To improve the efficiency of the network.

A primary technological challenge after a disaster is rapid deployment of temporary infrastructure to provide communications for disaster management workers. 3GPP Release 12 defines proximity service (ProSe) to allow direct communications within users for Long Term Evolution-Advanced (LTE-A) public safety. To support group communications, each group members have to receive data sent from the group application server (GAS) maintained in ProSe. This paper discusses the use of vehicle-mounted mobile base station to provide group communications over a two-tier heterogeneous architecture with the aid of GAS and ProSe links. In this method, each vehicle-mounted mobile base station (BS) works in a cell breathing manner to expand or shrink the cell coverage periodically. This way can ensure GAS having the up-to-date proximity knowledge of all users while the part of high-cost group data traffic due to the users located far from the BS can be offloaded to low-cost ProSe links instead. We formulate the minimum cost problem of the ProSe-based File Distribution (PFD) in such architecture. We prove the minimum PFD problem is NP-complete and then proposes three sources selection algorithms for PFD, namely Greedy algorithm, Defer algorithm, and Recursive algorithm. Extensive simulation study is conducted to evaluate performance of the proposed algorithms.

This paper proposes a novel load-balancing scheme for an operator-deployed cellular-wireless local area network (WLAN) heterogeneous network (HetNet), where the user association is controlled by employing a cell-breathing technique for the WLAN network. This scheme eliminates the complex coordination and additional signaling overheads between the users and the network by allowing the users to simply associate with the available WLAN networks similar to the traditional WLAN-first association, without making complex association decisions. Thus, this scheme can be easily implemented in an existing operator-deployed cellular-WLAN HetNet. The performance of the proposed scheme is evaluated in terms of load distribution between cellular and WLAN networks, user fairness, and system throughput, which demonstrates the superiority of the proposed scheme in load distribution and user fairness, while optimizing the system throughput. In addition, a cellular-WLAN interworking architecture and signaling procedures are proposed for implementing the proposed load-balancing schemes in an operator-deployed cellular-WLAN HetNet.

According to Cooper's law, the number of conversations per location doubles every two and a half years. Therefore, congestion control has become a promising research area. Nowadays small cell deployment has become a solution to deal with congestion. If large numbers of small cells are allocated for congestion control, then two critical issues will arise: densification and interference management. In such a scenario sector breathing can offer low power congestion control by avoiding densification problem. This paper proposes a power consumption model for sector breathing based congestion control in a mobile network. With sector breathing, a congested cell is sectored at an angle of 60° or 120°. The congested sectors are then identified. The lightly loaded neighbour cells of the congested sector are sectored at 60°. The sectors of the lightly loaded cell capture the border region customers of the adjacent congested sector by increasing the coverage area. When the transmitter antenna of the adjacent lightly loaded sector expands coverage to provide service to the subscribers residing at the border region of the congested sector, the transmitter antenna of the congested sector reduces its coverage area. The simulation results indicate that sector breathing reduces the power transmission of the BS antennas by approximately 6–75% and 62–75% compared cell breathing and dense femtocell allocation based congestion controls respectively. Simulation results also show that sector breathing reduces the power consumption of the BS antennas by approximately 6–64% and 82–90% compared with the cell breathing and dense femtocell allocation based congestion controls, respectively. Hence sector breathing is a green congestion control approach. Keywords: Cell breathing, Sectoring, Power, Interference

As the data traffic demand increases exponentially, efficient and fair use of Wi-Fi networks together with the emerging cellular networks becomes a crucial topic. In this article, we first present novel cell breathing based load balancing algorithms for Wi-Fi networks which provide full service availability. Then we enhance these algorithms to provide efficient offloading from cellular to Wi-Fi network in hot-spot areas. We also provide an efficient adaptive strategy for dynamic environments, where user distribution temporally changes. An extensive set of simulation results show that the proposed algorithms are very promising in satisfying min-max fairness and better user experience in Wi-Fi/Cellular heterogeneous networks. (C) 2018 Elsevier B.V. All rights reserved.

Traffic load in any 802.11 infrastructure mode network is typically distributed unevenly between access points (APs), creating hotspots. This is due to the inherent nature of wireless area networks (WLANs), where stations are free to associate to any known AP they desire, and the lack of control by the APs themselves. This imbalance creates a condition where affected APs in the network suffer traffic congestion while others are underutilized, leading to stations experiencing lower throughput, longer latency, and operating below the network potential capacity. To alleviate this problem, some form of load balancing is required to redistribute the work load among other available APs in the wireless network. This article presents a survey of the various works done in performing load balancing in an infrastructure mode wireless network and will cover the common methods including admission control, association management, cell breathing, and association control. Updates to the IEEE standards are also presented that support load-balancing efforts. Finally, software-defined networks are investigated to determine the extent of control integration to support managing and load-balancing WLANs. Trends in load-balancing research are also uncovered that indicate how the introduction of new wireless standards influences the amount of research.

In this paper the method for determining cell assignment probabilities, used for cellular network planning, is extended to take cell breathing into account. The model will be changed from a model based on the pilot power to a model based on the quality of the pilot signal. To reach a usable expressions some simplifications are made that hold in the network scenario, given by a network where the load is randomly spread and the investigated pixel is located randomly within the cell. In that case the ratio between the single cell state and the soft handover state is constant for load, which gives a simple cell assignment probability formulation that meets the requirements.

In this paper, the authors demonstrate the existence of a new type of losses later called ’signal breathing losses’. They have adopted this name because when the optical signal propagates in the propagation channel it changes its size and its position each half period. These dimensions changes will force the signal to get out from the transmission channel with signal losses and part of its proper power making it less confined. They have been able, theoretically and experimentally, to measure small variations in the signal which propagates in the optical propagation channel to 3D or in the plans XY, XZ and YZ. Furthermore, the authors measured and quantified the signal breathing losses based on the depth of corrugation, the size and of the number of periods. Then they affirmed that this type of loss increases with a significant number of periods, with periods of large dimensions, or disturbances to index modulation characterized by important depths. These measures were performed on a set of Bragg filters done on an optical propagation channel of type broadcasted waveguide. The authors believe the ’signal breathing’ phenomenon is similar to that of 2G and 3G wireless systems including code-division multiple access (CDMA) which is the cell breathing phenomenon due to alteration of the data traffic.

This paper proposes a new concept for making 5G networks flexible and adaptable. It introduces an approach and the method to execute it which can help attain maximum coverage, both in terms of efficiency and area, by allowing the eNodeBs/small cells to adjust their range according to the load and requirements of the network. The concept proposed in this paper also introduces a new potential dimension to the spider graph used by most companies and organizations involved in the development of 5G technologies and networks for comparing the performances of wireless technologies used for communication, which directly or indirectly affects the existing dimensions. The concept incorporates DLT, the abbreviation for Distributed Ledger Technology, and it’s approach towards data, i.e. decentralization to achieve streamlined processing and security. The ideas and technologies are carefully put together to attain the objective of enhancing the overall QoS.

Cell breathing is a method to reduce number of connected clients to a base station or an access point within mobile or wireless network. However, this cell breathing may disconnect progressing communication. Other work improved it by disconnecting the beacon signal only, so that current connection is not lost. However, this method does not avoid a mobile node or more, disconnected from any station. By proposing clustered beacon signal cell breathing, signal reduction is applied only to the cluster area where other base station or access point signal is detected. So that the disconnected mobile node will still be able to reconnect to other base station or access point. Simulation shows the method is able to reduce lost connection about 27.66%.

CDMA merupakan teknologi komunikasi seluler yang diklaim mampu memberikan kestabilan proses komunikasi yang lebih baik dari teknologi lainnya. Namun, teknologi CDMA yang dijalankan oleh TelkomFlexi di kabupaten Banggai, tidak begitu. Sering terjadinya gagal komunikasi (drop call) menjadi masalah terbesar. Upaya yang dilakukan untuk menyelesaikan masalah ini adalah melakukan proses analisis trafik dengan metode asosiasi dan komparatif, untuk melihat hubungan antara parameter yang ada, terhadap drop call yang terjadi. Dari hasil penelitian yang dilakukan, diketahui bahwa penyebab dari drop call adalah peristiwa cell breathing, tidak adanya mekanisme power kontrol, dan tidak adanya sel tetangga pada BTS yang diteliti. CDMA is one of the communication technology that claimed to provide stability in communication process, better than other technologies. But in fact, this technology that run by TelkomFlexi in Banggai district, is not like that. Frequently drop call events that occurs is the biggest problem. One of the important efforts that made to resolve, is to perform a traffic analysis process by using the association and the comparative method, to see the relationship between the existing parameters and the drop call. The result of this research is, it is known that the causes of the drop call is a cell breathing events, no power control mechanism, and no neighboring cells.

International Journal of Grid Computing & Applications (IJGCA) ISSN : 0976-9404 [Online]; 2229-3949 [Print] Parminder Kaur Article Title: ON THE CELL BREATHING TECHNIQUE TO REDUCE CONGESTION APPLYING BANDWIDTH LIMITATION ABSTRACT In order to effectively analyze or evaluate the performance of Wireless Local Area Networks (WLANs), it is important to identify what types of network settings can cause bad performance in the network when analyzing poor network performance, there is an important factor which is responsible for poor performance is when a number of users may obtain a much larger share of the available bandwidth in access point in a limited boundary as provided in the concept of cell breathing technique. In this paper, we proposed a new concept in which we can set bandwidth limitation so that no user can access data more than the specified limit for a particular access point. In this way the different users will get an efficient access over the network. KEYWORDS Access Point, Bandwidth, Bandwidth Limitation, boundary, Cell Breathing, Wireless Local area network. For More details please visit : http://www.airccse.org/journal/ijgca/ijgca.html Original Source URL: http://airccse.org/journal/ijgca/papers/3112ijgca02.pdf&nbsp

The 5G network has become one of the hottest research focuses. In this network, it is a consensus reached that the user terminals are high density and the cover of the base stations are multi-tier. The unbalance and variability of the spatial distribution and time of user services make the low utilization ratio of the network resources. A cell breathing algorithm based on energy efficiency is proposed in this paper which combines energy control, base station sleeping and cell zooming. The simulation shows that this algorithm makes the network performance better in energy efficiency and can balance the load of the base stations.

An overlay macrocell-femtocell system aims to increase the system capacity with a low-cost infrastructure. To construct such an infrastructure, we need to solve some existing problems. First, there is a tradeoff between femtocell coverage and overall system throughput, which we defined as the cell-breathing phenomenon. In light of this, we propose a femtocell downlink cell-breathing control framework to strike a balance between the coverage and data rate. Second, due to the selfish nature of mobile stations, the system information collected from them does not necessarily reflect the true status of the system. Thus, we design FEmtocell Virtual Election Rule (FEVER), a voting-based direct mechanism that only requires users to report their channel quality information to the femtocell base station. Not only is it proved to be truthful and has low implementation complexity, but it also strikes a balance between efficiency and fairness to meet the different needs. The simulation results verify the enhanced system performance under the FEVER mechanism.

International audience; In the context of ever-increasing wireless data rates, energy consumption could increase fast, with severe consequences on the operator's energy bill, in addition to environmental considerations. Energy-efficient cell breathing and BS switching-off algorithms are an important tool for energy reduction in cellular networks. In this paper, an energy-effcient cell breathing and offoading mechanism in both macrocellular and heterogeneous networks is studied. First, the need for limiting the number of Macro-BSs switched off and the control of cell sizes are analyzed. An approach based on the use of a traffic threshold from a technique previously proposed by our team is applied in order to control the BS switching-off aggressiveness. One reason for limiting this aggressiveness is the trade-off we point out between the existing RAN power consumption and the transmission power in uplink for mobile devices. Then, in the context of macro/femto deployments, the BS switching-off possibilities are extended by means of the extra capacity from an added femtolayer under regulated control access. We explore the impact of access policies from 3GPP CSGs (Closed Subscriber Groups) on the network performance and how CSG features may be used by operators to set aspects such as pricing policies and QoS provision levels. In this article, our goal is to provide a combined approach of both techniques in a single framework for macro/femto environments. The obtained results are analyzed showing the importance of proper tuning of energy-efficient algorithms in order to guarantee convenient energy savings and maintaining good QoS levels.

Wi-Fi wireless communication has become a basic service in public areas. However, the quality of service (QoS) might be inadequate in some areas because of the following influential factors: 1) the limited number of non-overlapping channels, 2) the interference caused by unplanned deployment and mobility, 3) the rapidly changing distribution of customers, and 4) access point (AP) failures. These factors result in non-uniform network traffic distribution and unavailability of service in some areas. Hence, this study focused on addressing the problems of AP failure and interference. We propose a self-healing algorithm to provide seamless and reliable service despite AP failures. The proposed water ripple algorithm maximizes the minimum delay difference, which is defined as the difference between transmission delay and tolerable delay, to satisfy requirements of multiple users simultaneously. Variable transmission power ranges (which involve cell breathing method types) and association management are adjusted to minimize the number of out-of-service mobile devices (MDs). Thus, fair allocation of resources to users and adequate QoS are satisfied.

Display Omitted The characteristics among the metrics, MD quantity, served traffic, bandwidth, and delay for load balancing were compared.A TALB algorithm is proposed to obtain high performance through cell-sizes and connections controlling.The balancing metrics are evaluated for heterogeneous wireless networks.The simulation results show that the delay metric enhances the balance and outperforms other metrics. The transmission ranges and bandwidths differ in heterogeneous wireless networks deployed from one- or two-dimensional to three-dimensional infrastructure-based architectures. Each mobile device (MD) selects a served access point (AP) or base-station (BS) according to their requirements and, subsequently, an MD selects the served AP, or the AP sends re-association messages to related MDs. This causes load-balancing problems because the balancing metrics of the MD quantity, AP-served traffic, and bandwidth usages are unsuitable to satisfy the fairness and quality of service (QoS) requirements. The packet delay was used as a measure of the criteria required to satisfy these requirements. To compare these metrics, a three-dimensional architecture load balance (TALB) algorithm is proposed that is based on the concepts of cell breathing and association control. Varying traffic requirements, the number of MDs, and AP bandwidths are considered. The simulation results show that the delay metric enhances the balance and outperforms other metrics.

In last decade, number of internet users are increasing so as Wi-Fi network usage is also increasing. Users are using Wi-Fi network for the internet facility. Wi-Fi network is a collection of Mobile Users [MUs] and Access Points [APs]. Because of unavailability of smart association techniques, sometimes mobile users are associated to single access point beyond the capacity of the access point, at that time load on access point is increased. While other access points have less mobile users. So it is necessary to balance the load. To balance the load in Wi-Fi network, various techniques like: received signal strength indicator, least load first, fair bandwidth allocation, smart association control, cell breathing, fuzzy, load balancing with fast handoff scheme and distributed association. These techniques working differently and use various criteria for load balancing in Wi-Fi network. Study all the technique and comparative analysis is done in this paper.

This letter proposes Intelligent Cell brEathing (ICE) to optimize the utilization of green energy in cellular networks by minimizing the maximal energy depleting rate of the low-power base stations powered by green energy. Minimizing the maximal depleting rate is an NP-hard problem. ICE is thus proposed to achieve low computational complexity. ICE, in each iteration, finds the energy dependent set and the vector of beacon power level decrements for low-power base stations in the set, and then shrinks the coverage area of these base stations by reducing their beacon power levels. The algorithm iterates until the optimal solution is found. ICE balances the energy consumptions among LBSs, enables more users to be served with green energy, and therefore reduces the on-grid energy consumption.

Cell size in cellular networks is in general fixed based on the estimated traffic load. However, the traffic load can have significant spatial and temporal fluctuations, which bring both challenges and opportunities to the planning and operating of cellular networks. This article introduces a concept of cell zooming, which adaptively adjusts the cell size according to traffic load, user requirements and channel conditions. The implementation issues of cell zooming are then presented. Finally a usage case of cell zooming for energy saving is investigated. Centralized and distributed cell zooming algorithms are developed, and simulation results show that the proposed algorithms can greatly reduce the energy consumption, which leads to green cellular networks.

The 802.11 networks have been commonly used for public internet access. Most 802.11 hotspots have more than one access point in an area. When these access points belong to the same network, users may choose anyone it connects to. In order to enhance the access services, some methods have been proposed. The methods allocate users to certain access point to avoid crowded and collided access. The method is referred to as load balancing. The existing work in load balancing are usually based on traffic balancing as well as cell breathing. The first one is the most common method as the cell breathing applies power reduction while electromagnetic wave travels anywhere and access point are usually in distance of low power transmitter. This paper proposes load and resource balancing where the client allocation is not only based on its load but also the access point resource. The simulation evaluation shows that the proposed method outperforms the existing one by reducing delay by 0.9%, increasing throughput up to 715 kbps and the collision probability reduces by 0.068% in average.

There are many issues when we implement a cellular system like bandwidth, channel assignment, cell structure etc. but call admission control in a cellular network become a most important issue. Call admission control not only utilize bandwidth efficiently but also decreases the new call blocking and handoff call dropping probability to an acceptable level. Call admission control (CAC) is a fundamental mechanism used for QOS(Quality of Service) provisioning in a network. It restricts the access to the network based on resource availability in order to prevent network congestion and service degradation for already supported users. In this paper, we consider a call admission control scheme for wideband code division multiple access (WCDMA) system. This call admission control uses cell breathing concept. In this scheme we also consider the condition of neighboring cell while making the decision on call request. The objective is to reduce the new call blocking and handoff call dropping probability and efficient utilization of available bandwidth while maintaining the desired level quality of service requirement.

Wireless LAN administrators often have to deal with the problem of sporadic client congestion in popular locations within the network. Existing approaches that relieve congestion by balancing the traffic load are encumbered by the modifications that are required to both access points and clients. We propose cell breathing, a well-known concept in cellular telephony, as a load balancing mechanism to handle client congestion in a wireless LAN. We develop power management algorithms for controlling the coverage of access points to handle dynamic changes in client workloads. We further incorporate hand-off costs and manufacturer specified power level constraints into our algorithms. Our approach does not require modification to clients or to the standard. It only changes the transmission power of beacon packets and does not change the transmission power of data packets to avoid the interactions with auto-rating. We analyze the worst-case bounds of the algorithms and show that they are either optimal or close to optimal. In addition, we evaluate our algorithms empirically using synthetic and real wireless LAN traces. Our results show that cell breathing significantly outperforms the commonly used fixed power scheme and performs at par with sophisticated load balancing schemes that require changes to both the client and access points

Dense deployment of wireless local area networks (WLANs) is part of the next generation Wi-Fi and standardization (802.11ax) efforts are underway. However, dense deployment of WLAN access points (APs) faces increased interference and uncoordinated association of user stations (STAs) with APs, which degrade network throughput. To assess the potential of improving uplink throughput in the presence of interference using AP association coordination, we propose an association optimization algorithm that matches STAs to APs in dense WLAN (DWLAN). While existing cell breathing approaches suggest tuning of APs' beacon powers for association control, the proposed approach utilizes uplink signal- interference-noise ratio (SINR) of stations (STAs) to coordinate STA-AP association. In order to further coordinate interference and increase spatial reuse, an algorithm is proposed to adjust the clear channel assessment (CCA) threshold of the 802.11 MAC protocol in each AP cell to address the problem of overlapped basic service set (OBSS) that degrades overall network throughput. Performance evaluation reveals that our SINR-based AP association coordination and CCA threshold adjustment schemes achieve significant increase in per-user throughput in a DWLAN.

International audience; Cell breathing is a mechanism used in cellular networks since many years, which is now proposed for energy efficient purposes. By using this technique, it is possible to save energy during low traffic periods by switching unnecessary BSs off whereas the cell topology is re-adapted supported on some few BSs active. In this article, we analyze a multi-size approach which provide means for an enhanced cell topology adaptation. We divide our approach in two redistribution phases. Each of these two phases is conceived for being efficient at specific traffic levels. A first phase configuration only allows short range cell expansion to cover just direct adjacent sectors, which works well for medium traffic load. Then if low load conditions afford it, a second phase may be executed which allows an extended multi-size expansion making it possible to cover additional sectors at a far distance, which results in some new larger cells and some extra BSs switched-off. The decision mechanism makes it possible to choose the best strategy between running "phase 1 only" or "phase 1 & 2 combined". Our approach is supported on a clustered architecture which distributes the computational load in the network. Each cluster consists of groups of BSs with a BS cluster head in charge of making decisions based on collected power saving indicators. Simulation and results are provided to analyze each of the potential approaches supported on phase 1 and 2 redistribution. It is shown that some interesting energy savings are obtained when each of our proposed phases is conveniently applied.

The paper introduces a self optimized close loop antenna array amplitude control system to counter the effect of non-uniform cell size breathing in UMTS and CDMA networks by avoiding the overshooting cells in the entire network automatically. In the proposed antenna array amplitude control system the active sector’s channel utilization as well as the relative channel utilizations of the entire candidate sectors is considered. We introduce a feedback system to detect physical parameters of the entire cell site sector antennas, like antenna heights above the ground level, antenna azimuths, antenna mechanical tilts, antenna latitudes and longitudes to avoid the chances of overshooting cells when the antenna array amplitudes are controlled remotely from the OMC-R. Remote mechanical antenna tilts are used to eliminate overshooting cells. The contribution of the proposed work is to develop an overshooting resistant antenna array amplitude control system to counter the non-uniform cell size breathing.

This paper studies the problem of energy cost optimization in green heterogenous cellular networks, in which base stations can be powered by hybrid energy supplies. We propose two intelligent cell breathing algorithms to solve this problem. The key idea of our first algorithm is to adapt cell sizes to assign more users to green pico BSs for energy cost saving, so as to maximizing the utilization of green energy. Considering its higher operational complexity, our second algorithm adds a biasing factor to the received pilot signal power from green pico BSs. Simulation results demonstrate that our two algorithms can significantly reduce energy cost, compared with the conventional maximum received signal power algorithm.

The gap between the stable system resource supply and the traffic load (i.e, the demand) with temporal fluctuations and spatial disparities results in deficiency in the system resource (e.g, power and spectrum resources) utility in cellular networks. To bridge the variant gap, cell breathing schemes are adopted in prior arts, which mainly focus on the temporal variance. Therefore, there is every reason to further explore the improvement room in terms of efficiency in the system resource utilization of cell breathing, jointly considering temporal fluctuations and spatial disparities of the traffic load, especially under Ultra-Dense HetNets (UDHNs), the promising delivery of 5G networks. We propose the High-Resolution Cell Breathing (HiRCB) strategy for improving energy efficiency for UDHNs: 1) inspired by pixels in digital imaging, the UDHN coverage area is logically divided into Traffic Lattices (TLs), capturing spatial disparities of the traffic load; 2) the TL association problem with the objective of maximizing the accumulative energy efficiency utility is formulated; 3) to solve the formulated problem, the Parallel and Integer TL Association Algorithm (PITLAA) is proposed, featuring parallel computations and algorithmic conversions from multiple to single TL association. Numerical results show that HiRCB improves at least 50% energy efficiency.

We investigate a wireless system of multiple cells, each having a downlink shared channel in support of high-speed packet data services. In practice, such a system consists of hierarchically organized entities including a central server, Base Stations (BSs), and Mobile Stations (MSs). Our goal is to improve global resource utilization and reduce regional congestion given asymmetric arrivals and departures of mobile users, a goal requiring load balancing among multiple cells. For this purpose, we propose a scalable cross-layer framework to coordinate packet-level scheduling, call-level cell-site selection and handoff, and system-level cell coverage based on load, throughput, and channel measurements. In this framework, an opportunistic scheduling algorithm--the weighted Alpha-Rule--exploits the gain of multiuser diversity in each cell independently, trading aggregate (mean) down-link throughput for fairness and minimum rate guarantees among MSs. Each MS adapts to its channel dynamics and the load fluctuations in neighboring cells, in accordance with MSs' mobility or their arrival and departure, by initiating load-aware handoff and cell-site selection. The central server adjusts schedulers of all cells to coordinate their coverage by prompting cell breathing or distributed MS handoffs. Across the whole system, BSs and MSs constantly monitor their load, throughput, or channel quality in order to facilitate the overall system coordination. Our specific contributions in such a framework are highlighted by the minimum-rate guaranteed weighted Alpha-Rule scheduling, the load-aware MS handoff/cell-site selection, and the Media Access Control (MAC)-layer cell breathing. Our evaluations show that the proposed framework can improve global resource utilization and load balancing, resulting in a smaller blocking rate of MS arrivals without extra resources while the aggregate throughput remains roughly the same or improved at the hot-spots. Our simulation tests also show that the coordinated system is robust to dynamic load fluctuations and is scalable to both the system dimension and the size of MS population.

Summary Wireless hotspots, ie, infrastructures composed of several IEEE 802.11 access points (APs), are today the most common solution in providing Internet access to a wide and rapidly changing population of users. According to common device implementation, stations establish associations with APs based on the measured strongest Received Signal Strength Indicator level. This usually leads to an uneven distribution of users to APs, increasing the chances of local network congestion. Load balancing (LB) solutions aim at mitigating this problem controlling the distribution of users. The LB algorithms enforce stations to associate with APs that manage a low number of users and/or that have a low traffic load. Usually, LB solutions do not consider traffic priorities or they assume some a priori quality of service (QoS) configuration for users. In this study, we propose a QoS-LB solution based on the cell breathing technique with the goal of balancing the load in IEEE 802.11e Enhanced Distributed Channel Access (EDCA) Hotspots. The proposed algorithm explores the space of possible power/EDCA configurations by using a branch and bound approach that reduces the number of analyzed configurations and, hence, the time required to find the global optimal solution. The algorithm has been analytically defined and its performance evaluated through simulations and tests in a real test bed. The results prove that the proposed solution is effective in solving the optimal QoS-LB configuration problem in WiFi hotspots of average size.

A balanced network generally has a fair user distribution among the access points (APs) and enables a maximized overall network throughput. However, there are some hot-spot areas resulting in uneven load distribution among APs. Existing load balancing techniques mostly require hardware or software contribution at user side to control the association of users with APs. Power adjustment techniques at AP side require no modification at user devices, but, coverage reduction can create unserviced areas. We provide a dynamic min-max load balancing algorithm based on power adjustment technique which provides service availability guarantee by dynamically checking the coverage holes. We enhanced the algorithm by increasing awareness to heterogeneous nature of user distribution. We show the effectiveness of the provided algorithms via extensive set of simulations. Simulation results show that the algorithms improved the load balancing among the hot-spot areas up to 10%.