Master Of Science Thesis Work. (some Results & Scenarios)

Transcription

1 Coverage & Capacity in Hybrid Wideband Ad-hoc/cellular Access System Master Of Science Thesis Work (some Results & Scenarios) by Pietro Lungaro

2 Problem Statement Design a possible networking scenario, and carry out a realistic study about the eventual feasibility, in terms of Coverage & Capacity, of a cellular Ad-hoc multihop network.

3 Cellular traffic model: open system with Traffic Divergence at the sinks λup λdn

4 System Assumptions (Traffic) Even Traffic Distribution among the nodes Poisson Distributed Arrivals of Packets in the transmission buffers ( /N) λup Answering Poisson Distributed Traffic from the Basestation towards the terminal nodes ( α) Single service assumption (Implemented also a possible extension to multiservice) Intracell traffic assumed to be negligible B.I.B.O. Stability criterion for the determination of the Maximal Network throughput [Packet/Slot]

5 System Assumptions (Propagation Model) Standard Model with α = 3.6 P rec = P L tra ( d ) λ 4 π 2 G Ant tra G Ant rec G Sha tra rec Shadowing set according to the nodes which constitutes the link: Bs-Bs=6 db Bs-Mob=8 db Mob-Mob=12 db ( d ) = C + 10 α log ( d ) L 10 Frequency carrier 2.4 Ghz, with B=8 Mhz

6 System Assumptions (Radio Layers) Design & implementation of the Radio Access Layer Solution: Scheduling Routing Reorganizing STDMA (**) MHA Reor-Alg(*) (*) MILLCOMM 85 & Robertazzi (Converted to STDMA) (**) Grönkvist & Somarriba

7 RESULTS Users Study Parameters: Number of active terminals in a cell & variable cell radii Operator s study Parameters: User density & Access Point Densities over a fixed service area Both are based on the same cost model assumptions

8 User study:example Network for Reuse 1

9 5% User study:outage Comparison with Service Threshold

10 Extended Service Area (Area not to be covered)

11 Extended Service Area (Area not to be covered) 1 Hop System

12 Discussion on Throughput The definition is given in [Packet/Slot]; Assuming a packet duration coincident with the slot duration, it is possible to estimate the Delay [Slots]. From a B.I.B.O. Stable Queuing Network model is possible to find a bounduary for the network: λ Net < N / Eff F L

13 User study:complete Throughput (Packet/Tslot) Comparison (K=1 and K=3) (Each Reuse 3 Packet is assumed to carry a third of Reuse 1 Packet information)

14 User study:complete Throughput [Kbit/Sec] Comparison (K=1 and K=3)

15 Operator study: Modeling Service area: 10 km^2 Number of Basestations: Corresponding to BS/km^2 Active user density: Active_User/km^2

16 Operator study: Throughput per site (Bit/Sec/Hz/Site) analysys in function of both Bs-Density & Users-Density

17 Operator study: Throughput per user (Packet/Slot) analysys in function of both Bs- Density & Users-Density

18 Operator study: Throughput per user (Kbit/Sec) analysys in function of both Bs- Density & Users-Density

19 Discussion: Given that: - The benefits of this architecture are statistically related to the user density. - There can be important Fluctuations in the user density. How can we do a definitive cell planning?

20 Proposed solution for User Density Fluctuations Wireless Router

21 Routers Scenario: Reuse 1 & variable number of routers per cell 9 Routers 6 Routers 3 Routers

22 Outage Comparison with Threshold Operator Medium cost Operator Lower cost Operator High cost 5% Network Planning Hysteresis

23 Outage Comparison with Threshold Medium cost=0.6km Lower cost=0.8km High cost=0.4km Threshold fixed at 5% Need for zoom!!

24 Routers benefits for Users and Operators: Specific Zoom in the 2-8 Active users Area * = No Routers + = 3 Routers x = 6 Routers o = 9 Routers

25 Throughput with routers

26 Conclusions Multi-Hopping Increases Coverage (This lowers the BS deployment costs!) High Capacity needs High User Density (Bad because not controllable!) Elements like Routers could work as Traffic Stabilizators, correcting in a Cheap way errors in planning and density fluctuations They ll also make the performances almost independent from that statistical uncontrollability that can t ensure QoS