Coverage & Capacity in Hybrid Wideband Ad-hoc/cellular Access System. Results & Scenarios. by Pietro Lungaro

Transcription

1 Coverage & Capacity in Hybrid Wideband Ad-hoc/cellular Access System Results & Scenarios by Pietro Lungaro

2 Agenda Problem Statement System Assumptions Results Threats

3 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.

4 Cellular traffic model: open system with Traffic Divergence at the sinks up dn

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

6 Uplink & Downlink traffic specs up is the total (from all the nodes) traffic offered to the base station. In the Uplink side It ll be assumed for i up every node i that: up In the Downlink side It ll be considered an answering traffic equal to: i dn N dn N

7 B.i.b.o. Stability as a traffic evaluator (1) General description: System Reduction for STDMA

8 B.i.b.o. Stability as a traffic evaluator (2) Expected Queue Length: L q G' Expected Delay: _ D Fl where i T f Maximal Node Throughput: i FL 1

9 System Assumptions (Propagation Model) Standard Model with 4 2 Ptra Ant Ant Sha P rec Gtra Grec Gtra rec L d 4 Shadowing variance set according to the nodes which constitutes the link: Bs-Bs=6 db Bs-Mob=8 db Mob-Mob=12 db d C 10 log d L 10 Frequency carrier 2.4 Ghz, with B=8 Mhz

10 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

11 RESULTS: Throughput Double focus: 1) Users performances (Dimensioning of the Network to improve users rate) 2) Operator Performances (Dimensioning of the Network to reduce the AP density)

12 RESULTS: Throughput Users Study: Constant Number of active terminals and variable cell radius (Variable Users/Km density) Operator s study: Constant User density and variable number of AP over the same area

13 User study:example Network for Reuse 1

14 User study:example Network for Reuse 3

15 User study:outage Comparison with Service Threshold 5%

16 Discussion on Throughput The definition given is in [Packet/Slot], or assuming a packet to be enterely transmitted in one slot ([Packet/Packet_duration]). From a B.I.B.O. Stable Queuing Network model is possible to find a bounduary for the network: With this definition of throughput [Packet/slot], assuming a packet duration coincident with the slot duration, it is possible to estimate the Delay [Slots]. Net N / Eff F L Having a figure for the maximal service delay [sec], and knowing coding and Bandwidth it is possible to compute the packet size [bytes] to fulfill the service requirements.

17 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)

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

19 Operator study: Modeling Service area: 10 km^2 Number of Basestations: Corresponding to BS/km^2 Active user density: Active_User/km^2 (or Erlang/km^2)

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

21 This means: 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

22 Proposed solution for User Density Fluctuations Wireless Router

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

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

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

26 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

27 Conclusions of the scenario Part of the Infrastructure is now, by definition, an uncontrollable variable, so: These elements could work as traffic stabilizators, correcting in a cheap way errors in the planning or needs to replan (architectural changes). They ll make the performances almost independent from that statistical uncontrollability that can t ensure QoS.

28 Reorganizing Layer The assumption is that every node in the network has an unique ID number, and related to this there s a reserved initial broadcasting slot.

29 Reorganizing It is based on a successive inclusion of Subnetworks, one for every level of the network. The Bs is level 0 or Starter. It is based on a priority activation of the links. The metric used is: Layer ( S ) Layer ( ) 2 P ( S, D) I ( S, D) D It works with a Broadcast in the downlink and unicast in the uplink

30 Reorganizing A reorganizing packet it s much smaller than a data packet (cointains only an estimation of the link qualities). For this reason it could be possible for a node to transmit its info and the relayed ones in a single larger packet (dimensioning the packet size to the largest possible one).

31 Total Number of Slot Necessary to Reorganize (Variable & Fixed Parts) Comparison

32 Effective Maximal Number of signaling packets forwarded by an Active Node

33 Threats (1) The dipendence of the performances on the user density it is Fundamental in a Multi-Hop network. In an environment with high user density fluctuation the cellular planning becames difficult.

34 Threats (2) The amount of signaling traffic necessary to build and maintain active an Ad-Hoc Network with high QoS needs can conditionate in a negative way the performances; especially when the average hop number increases.

35 Conclusions With an appropriate cell-planning a Multi-Hop Ad-Hoc solution can ensure interesting data rate to users & a reduction of the base station density to the operators. The prerequisite for all this is an enhanced intelligence in the terminals.