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Ghost Femtocells: a Novel Radio Resource Management Scheme for OFDMA Based Networks

Ghost Femtocells: a Novel Radio Resource Management Scheme for OFDMA Based Networks. WCNC 2011. Outline. Introduction System Model Ghost Femtocells: The Proposed Resource Allocation Algorithm Simulation Conclusions. Introduction.

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Ghost Femtocells: a Novel Radio Resource Management Scheme for OFDMA Based Networks

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  1. Ghost Femtocells: a Novel Radio ResourceManagement Scheme for OFDMA Based Networks WCNC 2011

  2. Outline • Introduction • System Model • Ghost Femtocells: The Proposed Resource Allocation Algorithm • Simulation • Conclusions

  3. Introduction • The femtocell deployment in 3GPP/LTE sets new challenges to interference mitigation techniques and Radio Resource Management (RRM). • The goal of this paper is to achieve effective spectral reuse between macrocells and femtocells while guaranteeing the QoS of users served by both macro and femto base stations.

  4. System Model • OFDM symbols are organized into a number of physical RBs consisting of • 12 contiguous sub-carriers • 7 consecutive OFDM symbols • bandwidth of 10 MHz • 50 RBs are available for data transmission

  5. System Model

  6. System Model: Deployment

  7. System Model: Path loss

  8. System Model: Fading channels • The information theoretical limit is established by defining an outage probability • Pout that the instantaneous mutual information for a given fading instance is smaller than the spectral efficiency R associated with the transmitted packet

  9. Proposed Resource Allocation Algorithm • In this paper vision, femtocells should be invisible in terms of interference generated to neighbour cellular users. • Femtocells deployment presents a very challenging issue: while H-BSs power consumption and interference range should be small, the coverage range at which UEs can meet their QoS constraints should be large.

  10. Proposed Resource Allocation Algorithm • Step 1: [Classification of Interferers] • H-UEs overhear the broadcast channel (BCH) and estimate which neighbour HBSs are strong interferers. • Step 2: [Feedback to H-BS] • H-UE feedbacks to the H-BS its QoS constraints • the momentary Channel State Indicator (CSI) • and the cell-IDs of the H-BSs perceived as strong interferers • Step 3: [Feedback to Control Unit] • Each H-BS reports this information to the Control Unit (CU). • CU stores the set of its neighbours Vi.

  11. Proposed Resource Allocation Algorithm • Step 4: [Computing Scheduling Matrices] • CU computes scheduling metricλij for every user i on every RB j. • RRMghostimplements a Proportional Fair based scheduler, that is • RRMghostuses this metric to build the scheduling matrices MTxand Mrep • MTx : scheduler allocates to each user the minimum number of RBs that meets QoS and power constraints. • Mrep: to allocate to the served users additional available RBs. RB1 U1 RB2 RB6 U2 RB9 U2 U3 U1 U3 RB1 RB2 RB16 RB16

  12. Proposed Resource Allocation Algorithm • Step 5: [Scheduling] • The CU selects for each user to serve, the minimum number of RBs that meets QoS and power constraints. • Step 5-a: • selects the best user-available RB pair (i,j) with the best metric in MTx • Step 5-b: • Each user-available RB pair (i,j), the algorithm checks the set of RBs allotted to user i (RBi) and selects the highest possible Modulation and Coding Scheme (MCSi), accordingly. RB1 U1 RB2 RB6 U2 RB9 U3 RB16

  13. Proposed Resource Allocation Algorithm • Step 5-c: • The controller estimates the sum of the Mutual Information I given by set RBi and MCSi. RB1 U1 RB2 RB6 U2 RB9 U3 RB16

  14. Proposed Resource Allocation Algorithm • Step 6: [MCS Scaling] • Given the set of RBs (RBi) allocated each served user i, the algorithm finds the MCS* of the minimum order that meets the QoS target. If MCS* is different from MCSi, the MCS of user i (MCSi) is set equal to MCS*. • Step 7: [Repetition] • The CU allocates unused RBs to repeat the original message and improve the transmission robustness. • Step 7-a: • The scheduler selects the user-available RB pair (i,j) that has the best metric in MRep. • Step 7-b: • If I < Rtg, repetitions would cause outage, hence the values of the row corresponding to user I in MRep are set to zero. • When I ¸ Rtg, the original message is repeated in the additional RB and MRep(i; j) as well as MRep(k; j), where k ∈ Vi, are set to zero.

  15. Proposed Resource Allocation Algorithm • Step 8: [Power Scaling] • The algorithm estimates the SINR perceived at each served user and reduces the allocated transmission • power to meet the SINR threshold given by the target PER and the selected MCS. • Step 9: [Message Reception] • Finally, each user collects the information received in each of its allotted RBs and combines these RBs using the chase combining scheme

  16. Simulation

  17. Conclusions • RRMghost, a novel radio resource management scheme that efficiently uses the available wireless spectrum in a two-tier network. • It limits the undesired effects of interference by reducing the power budget PTrequired at femtocells to meet target QoS constraints.

  18. 每周一句 • On the contrary, in Scenarios Traf:3 and Traf:4 under RRMghost, H-UEs achieve performance beyond 90% of Ttg. • on the contrary: 恰恰相反 • in contrast:  一定是相反，非常不一樣即可 • on the other hand: 換句話說

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