Throughput Enhancement Through Femto-Cell Deployment

Bharucha, Zubin; Haas, Harald; Cosovic, I.; Auer, Gunther

doi:10.1007/978-90-481-2530-2_30

Cited by 19 publications

(18 citation statements)

References 5 publications

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“…In each active femto-cell, both the MSs and FBS are uniformly distributed in the apartment. Due to the private deployment of femto-cells a closed-access system is assumed [20], so each MS is assigned to TABLE II PROBABILITY TABLES FOR THE NUMBER OF USERS ALLOCATED IN A SINGLE FEMTO-CELL. THE LEFT TABLE INDUCES EQUAL PROBABILITIES FOR EACH POSSIBLE NUMBER OF USERS, IN THE RIGHT TABLE THE PROBABILITY IS HALVED WITH EACH ADDITIONAL USER. µ(u) 1 2 3 4 p n(u)=1 1 1 /2 1 /3 1 /4 p n(u)=2 0 1 /2 1 /3 1 /4 p n(u)=3 0 0 1 /3 1 /4 p n(u)=4 0 0 0 1 /4 orμ (u) 1 2 3 4 p n(u)=1 1 2 /3 4 /7 8 /15 p n(u)=2 0 1 /3 2 /7 4 /15 p n(u)=3 0 0 1 /7 2 /15 p n(u)=4 0 0 0 1 /15 the FBS in its apartment, even if a foreign cell exhibits superior link conditions.…”

Section: A Scenario Constructionmentioning

confidence: 99%

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Distributed and Autonomous Resource and Power Allocation for Wireless Networks

Burchardt

Sinanović

Bharucha

et al. 2013

IEEE Trans. Commun.

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In this paper, a distributed and autonomous technique for resource and power allocation in orthogonal frequency division multiple access (OFDMA) femto-cellular networks is presented. Here, resource blocks (RBs) and their corresponding transmit powers are assigned to the user(s) in each cell individually without explicit coordination between femto-base stations (FBSs). The "allocatability" of each resource is determined utilising only locally available information of the following quantities:• the required rate of the user;• the quality (i.e., strength) of the desired signal;• the level of interference incident on each RB; and• the frequency-selective fading on each RB.Using a fuzzy logic system, the time-averaged values of each of these inputs are combined to determine which RBs are most suitable to be allocated in a particular cell, i.e., which resources can be assigned such that the user requested rate(s) in that cell are satisfied. Furthermore, link adaptation (LA) is included, enabling users to adjust to varying channel conditions. A comprehensive study in a femto-cell environment is performed, yielding system performance improvements in terms of throughput, energy efficiency and coverage over state-of-the-art inter-cell interference coordination (ICIC) techniques. Index Termsautonomous resource allocation, distributed ICIC, fuzzy logic, OFDMA, femto-cellular networks. I. INTRODUCTIONFuture wireless networks are moving towards heterogeneous architectures, where in each cell a user may have over four different types of access points (APs) (e.g., macro-, pico-, femtocells, relays and/or remote radio heads) [1]. Intuitively, this has many positive effects for a September 14, 2018 DRAFT 2 mobile station (MS), which can now choose from several base stations (BSs) to find the most suitable. However, pico-and femto-cellular overlays also imbue many difficulties, e.g., cellorganisation/optimisation, resource assignment to users, and especially interference coordination between APs within the same and neighbouring cells. Standard inter-cell interference coordination (ICIC) techniques based on network architectures [2, 3] only go so far in dealing with these challenges, and hence a new approach is necessary. A. Challenges in Heterogeneous Networks (HetNets)Through the various types, locations and dense deployment of APs, and the different transmissions powers/ranges associated with them, numerous technical challenges are posed by femto/picocell overlays [1,4,5]. These mainly fall into the following areas:• Network self-organisation -Self-configuration and -optimisation are required of all cells.In cellular networks, such organisation can be performed via optimisation techniques [6], however these tasks become increasingly difficult given the additional APs and network parameters to be considered, motivating a distributed configuration approach [7].• Backhauling -Connecting the different BSs to the core-network necessitates extra infrastructure [1]. In the femto-cell case, the long delay of connection via wired backhaul...

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Section: A Scenario Constructionmentioning

confidence: 99%

“…Further, we assume each user is uniformly distributed a MCS 4 , hence by replacing (20) with (26) and performing the same CDF transformation, the transmit power PDFs (i.e., f Pt (p) and f Pt,dB (θ))…”

Section: Signal Statisticsmentioning

confidence: 99%

Distributed and Autonomous Resource and Power Allocation for Wireless Networks

Burchardt

Sinanović

Bharucha

et al. 2013

IEEE Trans. Commun.

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“…Any UE which is not a member of this so-called closed subscriber group (CSG) must attempt to maintain communication with its serving macro Evolved NodeB (eNB) despite being in close proximity to the HeNB. While femto-cells promise substantial coverage and capacity gains [3,[9][10][11], their random deployment introduces additional interference, particularly to macro UEs who are not part of the CSG of the HeNB/s in their vicinity. This paper focuses on the performance of such macro UEs.…”

Section: Introductionmentioning

confidence: 99%

Femto-to-Macro Control Channel Interference Mitigation via Cell ID Manipulation in LTE

Bharucha

Auer

Abe

et al. 2011

2011 IEEE Vehicular Technology Conference (VTC Fall)

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With considerable interest being garnered in recent years, femto-cells are seen as a major contender to significantly increase capacity and fill coverage holes in 3 rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) cellular networks. User-deployed femto-cells, each exclusively serving a set of registered users and sharing the same frequency spectrum as the overlay macro-cells are already defined in 3GPP specifications. Such a co-channel and random deployment of femto-cells can cause heavy downlink (DL) interference to a user equipment (UE) in the vicinity of one or more femto-cells and not belonging to their closed subscriber groups (CSGs). In this paper, we focus on protection of the most important LTE DL control channel, known as the physical control format indicator channel (PCFICH). Failure to decode this channel correctly results in the loss of the subsequent subframe. A technique which mitigates femto-to-macro PCFICH interference by carefully manipulating the physical cell identity (PCI) of the aggressor femto-cell ispresented. It is shown that employing this technique results in a significant improvement of PCFICH effective signal-tointerference-plus-noise ratio (SINR) without the need for any additional network signaling.

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“…The Femto Access Points (FAPs) are small and low cost base stations located typically within buildings with the purpose to improve Quality of Service (QoS) for indoor users [1]. The FAP is connected to the operator network via wired link exploiting xDSL, cable, or optic fiber connection.…”

Section: Introductionmentioning

confidence: 99%

Efficient routing of data for femtocells

Mach

Bečvář

2011

2011 IFIP Wireless Days (WD)

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The paper proposes novel routing method for two users connected to the same femtocell communicating with each other. In conventional case, data are sent in two sequential steps. In the first step, data are transmitted from the user to the femtocell. In the second step, data have to be retransmitted to other user. We suggest transmitting user's data directly instead of two hop communications if both users are sufficiently close to each other. In addition, we propose exchange of management messages in order to implement our routing scheme in LTE-A standard. The simulation results indicate that the throughput offered by femtocells can be significantly increased.

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Throughput Enhancement Through Femto-Cell Deployment

Cited by 19 publications

References 5 publications

Distributed and Autonomous Resource and Power Allocation for Wireless Networks

Distributed and Autonomous Resource and Power Allocation for Wireless Networks

Femto-to-Macro Control Channel Interference Mitigation via Cell ID Manipulation in LTE

Efficient routing of data for femtocells

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