Berger, Michael Stübert

Dittmann, Lars

Popovska Avramova, Andrijana

Ruepp, Sarah Renée

Zakrzewska, Anna

Online Research Database In Technology

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Downloaded from orbit.dtu.dk on: Dec 20, 2017CSMA-based SON Mechanism for Greening Heterogeneous NetworksZakrzewska, Anna; Popovska Avramova, Andrijana; Ruepp, Sarah Renée; Berger, Michael Stübert;Dittmann, LarsPublication date:2013Link back to DTU OrbitCitation (APA):Zakrzewska, A., Popovska Avramova, A., Ruepp, S. R., Berger, M. S., & Dittmann, L. (2013). CSMA-based SONMechanism for Greening Heterogeneous Networks. Paper presented at 32nd IEEE International Conference onComputer Communications (INFOCOM 2013), Turin, Italy.CSMA-based SON Mechanism for GreeningHeterogeneous NetworksAnna Zakrzewska, Andrijana Popovska Avramova, Sarah Ruepp, Michael S. Berger and Lars DittmannDepartment of Photonics EngineeringTechnical University of DenmarkØrsteds Plads 343, 2800 Kgs. Lyngby, DenmarkEmail: {azak, apop, srru, msbe, ladit}@fotonik.dtu.dkI. INTRODUCTIONEnergy consumption has become one of the major chal-lenges in the future communication networks. With the in-creased demand for capacity, the amount of energy needed byRadio Access Networks (RANs) grows significantly. Currentresearch efforts propose solutions to increase network capacityat a much lower energy cost. For example in Distributed BaseStation (DBS) or Cloud Radio Access Network (C-RAN), aset of Remote Radio Heads (RRHs) is connected to a basebandprocessing unit through an optical fiber which reduces thepower needed to transmit the signal. Furthermore, thanks tocentralized processing the number of sites decreases, thusnetwork resources, including energy, can be better utilizedthrough joint management. Another way to achieve this goalis deployment of low power nodes covering smaller areas thanmacro base stations, forming femto- or picocells. Even thoughsmall cells already reduce power consumption when comparedto macro-sites, there is still room for improvement.Base stations consume energy all the time, regardless ofthe traffic and the load. From an energy saving perspective,there is a high potential in reducing the transmission powerwhen the resource utilization becomes low, as proposed in[1], [2]. However, this may be a challenging task in case ofsmall cells, as they are deployed in an uncoordinated manner.Because of their dense deployment, centralized management iscomplex and introduces high signalling overhead. On the otherhand, distributed decision taking process may lead to potentialconflicts. In this work we present a method for independentdecision spread and coordination among small cells based onCarrier Sense Multiple Access (CSMA) principles [3], andfocus on an energy saving example.II. SELF-ORGANIZING HETEROGENEOUS NETWORKSManaging densely deployed small cells is a very challeng-ing task and therefore Self-Organizing Network (SON) [4] hasan enormous potential to make it easier, more automatic andthus reduce the cost of network maintenance and operation.Fig. 1. SON input and outputFig. 1 presents a general view on SON. It automatically col-lects different type of network information from neighbouringcells, such as current network performance (e.g. traffic loadand resource utilization for macro and pico layer, as well asenergy consumption). This data is used for further analysis,comparison with previous records, such as traffic history forinstance, preparation of future prognosis and finally execu-tion of optimization tasks. As a result, network performancecan be improved according to the required Key PerformanceIndicators (KPIs) thresholds, e.g. load, utilization and energyconsumption limits.SON can help to manage the dynamic wireless environmentmade out of small cells in either a centralized or distributedway. In the first case, there is an entity responsible for col-lecting the data, performing optimization tasks and enforcingthe decisions. On the contrary, in the latter scenario every cellruns its own optimization procedures based on the informationgathered from the surrounding environment (through sensing,reports from the neighbours etc.). Every low power nodeshould then implement changes on its own but at the sametime be aware of the configuration updates introduced at theneighbouring cells, as it may influence its own performanceand decisions. In this work we focus on the distributed scenarioand propose a mechanism based on CSMA to coordinate suchan independent parameter change.III. ENERGY EFFICIENCYAs mentioned in the introductory section, base stationsconsume the same amount of energy when being idle e.g. atnight, as they do during peak traffic hours. The same appliesto small cells but it is easier to mitigate than in the caseof macro base stations. Low power nodes have more localcharacter and their coverage is much smaller. Therefore, it iseasier to adjust their power or even switch them off without arisk of causing a coverage hole, as there is always overlayingmacrocell providing the service.There are various modes of operation of small cells, namelyopen, close and hybrid subscriber group (OSG, CSG and HSG,respectively) [5]. Depending on the user activity, the transmis-sion power of a small cell may be significantly reduced forenterprise open cells when the load is low or more private CSGcells may be even put into the sleep mode during night hours.To facilitate such changes we introduce 3 power levels: 1)regular when a node serves users at a maximum allowed powerlevel, 2) reduced power, when a node operates at a lower powerand hence the cell has smaller coverage, and 3) sleep mode,TimePowerSleepReducedAlert: neighbour high utilizationAlert: high interferenceAlert: low traffic demandFig. 2. Gradual power controlwhen a node is available for control communication purposesbut does not provide any service to the users. Different kindof alerts (internal or coming from the neighbours) can enforcereduction or increase of the transmission power of a cell, aspresented in Fig. 2. For example, constant decrease of trafficdemand in a cell may eventually put a node into the sleepmode. Any users that need to be served in the primary smallcell coverage area can be redirected by an enforced handovereither to the umbrella macrocell or to a neighbouring smallcell, if the latter increases its coverage. On the other hand, analert on high utilization of neighbouring nodes, which may leadto traffic congestion, will wake up a node and make it fullyoperational. We note that changes of the node transmissionpower can be done gradually on a step-by-step basis, and thevalue intervals as well as the frequency of such changes dependon the implemented algorithm.IV. CONTROL MECHANISMIn a dense small cell environment, where SON functional-ities are distributed, each small cell has its own optimizationobject. In Fig. 3 several small cell objects and the communi-cation among them are illustrated.In the time domain, we illustrate the optimization proce-dure as consisting of the following time periods: sensing andreporting, decision making, action execution and frozen period.During the overall operation, each cell needs to continuouslymonitor the environment, and inform the neighbouring cellsof its current state. The actual intervals for reporting andalerting depend on many parameters such as current load, thetime of the day, expected traffic demands, power consumptionetc. If the measured KPIs get closer to the actual thresholds,the alerting interval could be reduced. If the KPI thresholdsare violated then the optimization procedure needs to reacha decision that will eventually result into an action (e.g.change of transmission power, antenna tilting). For examplethe graduate power control explained in Fig. 2 of the previoussection represents the decision period.The question of who should perform an action amongthe neighbouring cell is resolved as in CSMA with collisionavoidance (CA) scheme. Before an action is conducted, anotification is sent to all neighbouring cells. If a conflictoccurs (two cells receive their notification for action), it isresolved by applying a random backoff period for the action.This means that a frozen period (similar to busy channel inCSMA) occurs for all neighbouring cells. During the frozenperiod the neighbouring cells need to monitor the environmentagain before reaching a decision and possibly notifying andperforming an action. This period is required in order to makesure that the small cells have taken into account the change inACTFROZEN TIMESENSE, REPORT, ALERTDECIDE ACTTimeDECIDE ACTDECIDE ACT FROZEN TIMEDECIDE ACT FROZEN TIMEACTDECIDEDECIDEDECIDE. . .SENSE, REPORT, ALERTACTSENSE, REPORT, ALERTSENSE, REPORT, ALERTSENSE, REPORT, ALERTreports, alertsreports, alerts reports, alertsreports, alerts. . . . . .Cell SON ObjectsDECIDEDECIDEFig. 3. Communication time framethe environment as a result of the performed action. The frozenperiod can be predetermined or agreed among neighbouringcells. The duration of the period is dynamic and depends onthe implemented optimization algorithm as well as the currentstate of the cell and neighbouring cells.The proposed way of resolving the right to perform anaction requires communication among all neighbouring smallcells. For that purpose, X2 connections among the small cellscan be used. Where X2 interface is not available, a femtocellgateway [5] can act as a proxy for the reports and actionsrequests. The actual communication among the cells is achallenging task and requires future considerations taking intoaccount such aspects as synchronization and signaling loadreduction.V. CONCLUSION AND FUTURE WORKWe propose a SON based scheme for energy controlin wireless heterogeneous networks. It allows for gradualtransmission power change by individual nodes independentlyfrom the others, as it adopts a coordination approach fromCSMA. The ongoing and future work includes designing of anefficient algorithm that can be deployed in the decision phase.Evaluation will test convergence and stability of the proposedcontrol mechanism. Mechanisms of waking the nodes up andmaking them operational after the time of limited activity alsorequire further study.REFERENCES[1] O. Blume, H. Eckhardt, S. Klein, E. Kuehn and W. M. Wajda; ”Energysavings in mobile networks based on adaptation to traffic statistics,” BellLabs Tech. J., vol. 15, no. 2, pp. 7794, Sep. 2010.[2] J. Hoydis, M. Kobayashi and M. Debbah; ”Green Small-Cell Networks,”Vehicular Technology Magazine, IEEE, vol.6, no.1, pp.37-43, Mar. 2011.[3] L. Kleinrock and F. Tobagi; ”Packet Switching in Radio Channels: PartI–Carrier Sense Multiple-Access Modes and Their Throughput-DelayCharacteristics,” Communications, IEEE Transactions on , vol.23, no.12,pp. 1400- 1416, Dec. 1975.[4] 3GPP, TS 32.500, ”Telecommunication management; Self-OrganizingNetworks (SON); Concepts and requirements”, Feb. 2009.[5] S. Hamalainen, H. Sanneck and C. Sartori (Eds.); ”LTE Self-OrganizingNetworks (SON)”, John & Wiley Sons, Ltd., 2012.

CSMA-based SON Mechanism for Greening Heterogeneous Networks

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CSMA-based SON Mechanism for Greening Heterogeneous Networks

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