Wireless Networks Fall Part #4: The Cellular Principle Capacity, Interference, and Traffic Engineering

Transcription

1 Wireless Networks Fall 2018 Part #4: The Cellular Principle Capacity, Interference, and Traffic Engineering Goals: Discuss the basics of Cellular Network design tradeoffs Present various schemes for capacity improvement Introduce the basic concepts of Traffic Engineering Wireless Networks Laboratory Prof. Zygmunt J. Haas 1 The Cellular Principle Wireless Networks Laboratory Prof. Zygmunt J. Haas 2 Prof. Zygmunt J. Haas 1

2 Intro to the Cellular Principle {f4} {f6} {f2} {f5} {f3} {f7} {f4} {f6} In our example, if each set is reused 3 times, the overall capacity is increased by the factor of 3! We can now accommodate 3x350=1050 calls. {f5} {f1} {f2} {f3} {f7} {f4} {f6} {f5} {f3} {f7} j n j ( e. g., ) {f2} Wireless Networks Laboratory Prof. Zygmunt J. Haas 3 Intro to the Cellular Principle Advantages of Cellular Systems Increased capacity Lower transmission power Better coverage (more predictable propagation environment) Larger reliability (more robust system) Disadvantages of Cellular Systems Interference from co-channel cells Handoffs/Handovers Network of base-stations More hardware and larger right-of-way costs Congestion in hot spots Design Choices Cluster formation (reuse pattern, cell sizing, etc) Channel reuse and allocation schemes Handoff schemes Power control schemes Wireless Networks Laboratory Prof. Zygmunt J. Haas 4 Prof. Zygmunt J. Haas 2

3 Cellular System Modeling The actual coverage of the radiation pattern is highly irregular and is influenced by various effects, such as terrain topology, man-made structure, atmospheric conditions Cells are modeled as hexagons, to describe continuous coverage. (The cells shape should approximate the radiation pattern of an omni-directional antenna, which we assume to be a circle. We use hexagons, as the largest polygon that still tessellate a plane.) The cell size (the so called, macro-cell) can vary from 0.5 mile in metropolitan areas to 10 miles in rual areas. Note that the hexagonal pattern is created by the location of base-stations. Wireless Networks Laboratory Prof. Zygmunt J. Haas 5 Hexagonal Geometry N = 3 Wireless Networks Laboratory Prof. Zygmunt J. Haas 6 Prof. Zygmunt J. Haas 3

4 Hexagonal Geometry N = 3 Wireless Networks Laboratory Prof. Zygmunt J. Haas 7 Hexagonal Geometry N = 3 Wireless Networks Laboratory Prof. Zygmunt J. Haas 8 Prof. Zygmunt J. Haas 4

5 Hexagonal Geometry N = 3 Wireless Networks Laboratory Prof. Zygmunt J. Haas 9 Hexagonal Geometry N = 3 Wireless Networks Laboratory Prof. Zygmunt J. Haas 10 Prof. Zygmunt J. Haas 5

6 The Cellular Principle Cluster Formation N reuse factor = number of cells in a cluster. Here, N=7. {f6} {f6} {f4} {f3} {f6} {f4} {f3} {f2} {f4} {f3} {f2} {f5} {f1} {f2} {f5} {f1} {f7} {f5} {f1} {f7} {f7} Note: large N (keeping cell size constant) less capacity, but also less interference Why? Wireless Networks Laboratory Prof. Zygmunt J. Haas 11 The Cellular Principle Cluster Formation I.e., to ensure plane tessellation, clusters are modeled as hexagons too. To ensure plane tessellation: N = i 2 + ij + j 2 where i, j = 0, 1, 2, Wireless Networks Laboratory Prof. Zygmunt J. Haas 12 Prof. Zygmunt J. Haas 6

7 Interference vs. Capacity Tradeoff in Cellular Systems Wireless Networks Laboratory Prof. Zygmunt J. Haas 13 The Cellular Principle Cluster Formation In hexagonal geometry, for any N, each cell has exactly 6 co-channel cells in the first tier. Wireless Networks Laboratory Prof. Zygmunt J. Haas 14 Prof. Zygmunt J. Haas 7

8 The Cellular Principle Cluster Formation In hexagonal geometry, for any N, each cell has exactly 6 co-channel cells in the first tier. D The co-channel distance, D, depends on N: D = R Q D = R 3N or 3N R Wireless Networks Laboratory Prof. Zygmunt J. Haas 15 The Cellular Principle Cluster Formation N = i 2 + ij + j 2 Q D R = 3N i, j Cluster Size (N) Co-channel Reuse Ratio (Q) i = 1, j = i = 1, j = i = 2, j = i = 1, j = Wireless Networks Laboratory Prof. Zygmunt J. Haas 16 Prof. Zygmunt J. Haas 8

9 The Cellular Principle Co-channel Interference is the received Signal to Interference ratio at the (desired) mobile receiver (downlink). is the received Signal to Interference ratio at the(desired) base station (uplink) Note: the two are not (necessarily) the same = = = Wireless Networks Laboratory Prof. Zygmunt J. Haas 17 = Q, where we assumed that: 1. The transmit powers of the mobile and all the base stations (desired and interfering) are the same. 2. All the interfering base stations are at equal distance, D, from the mobile in question. 3. Neglecting the interference from non-first-tier interferers. 4. The mobile is at the worst case position. 5. Q, where R is the cell radius The Cellular Principle Co-channel Interference is the received Carrier to Interference ratio at the (desired) mobile receiver is the received Carrier to Interference ratio at the(desired) base station (uplink) Note: the two are not (necessarily) the same = = = = Q, where we assumed that: 1. The transmit powers of the mobile and all the base stations (desired and interfering) are the same. 2. All the interfering base stations are at equal distance, D, from the mobile in question. 3. Neglecting the interference from non-first-tier interferers. 4. The mobile is at the worst case position. 5. Q, where R is the cell radius Wireless Networks Laboratory Prof. Zygmunt J. Haas 18 Prof. Zygmunt J. Haas 9

10 The Cellular Principle Co-channel Interference = = = = Q, Note that because of (2) above, the is an approximation. Note that D is the distance between the centers of two hexagonal clusters System (S/I)min (D/R) N AMPS ~ 18 db ~ GSM ~ 11 db ~ IS-54 ~ 16 db ~ CDMA ~ -15 db ~ Wireless Networks Laboratory Prof. Zygmunt J. Haas 19 The Cellular Principle Cluster Formation N = i 2 + ij + j 2 Q D R = 3N = Q, i, j Cluster Size (N) Co-channel Reuse Ratio (Q) SIR = S I (γ = 4) i = 1, j = = = 11. 3[dB] i = 1, j = = = 18. 7[dB] i = 2, j = = 216 = 23. 3[dB] i = 1, j = = = 24[dB] Wireless Networks Laboratory Prof. Zygmunt J. Haas 20 Prof. Zygmunt J. Haas 10

11 The Cellular Principle Cluster Formation N = i 2 + ij + j 2 Q D R = 3N = Q, If i = 0, j = 1 N = 1 Q = 3 D = R 3 ; i.e., the cochannel cells are adjacent cells. Is this possible? Yes. Using CDMA, adjacent cells can use the same channel D=R 3 R D 3 2 R Wireless Networks Laboratory Prof. Zygmunt J. Haas 21 The Cellular Principle Co-channel Interference System (S/I)min (D/R) N AMPS ~ 18 db ~ GSM ~ 11 db ~ IS-54 ~ 16 db ~ CDMA ~ -15 db ~ Wireless Networks Laboratory Prof. Zygmunt J. Haas 22 Prof. Zygmunt J. Haas 11

12 Co-channel Interference More Accurate Calculation Wireless Networks Laboratory Prof. Zygmunt J. Haas 23 Co-channel Interference More Accurate Calculation SIR S I = 2 P D R P R + 2 P D + 2 P D + R SIR = R 2 D R + 2D + 2 D + R SIR = 1 2 Q 1 + 2Q + 2 Q + 1 Wireless Networks Laboratory Prof. Zygmunt J. Haas 24 Prof. Zygmunt J. Haas 12

13 Improvement of Capacity v. Interference Tradeoff in Cellular Systems Wireless Networks Laboratory Prof. Zygmunt J. Haas 25 Improving Capacity and Reducing Interference Note that there is a close correspondence between the network capacity (expressed by N) and the interference conditions (expressed by S/I). Capacity can be increased and interference can be reduced by: Cell sectoring Cell splitting Cell sizing (micro-cellular networks, pico-cellular, nano-cellular) Cell sectoring reduces the interference by reducing the number of cochannel interferers that each cell is exposed to. For example, for 60 degrees sectorization, only one interferer is present, compared to 6 in omidirectional antennas. But, cell sectorization also splits the channel sets into smaller groups, reducing the trunking efficiency. Cell splitting allows to create more smaller cells. Thus, the same number of channels is used for smaller area. For the same prob. of blocking, more users could be allocated. Wireless Networks Laboratory Prof. Zygmunt J. Haas 26 Prof. Zygmunt J. Haas 13

14 Improving Tradeoff between Capacity and Interference 3-sector cells 6-sector cells = Q = Q Wireless Networks Laboratory Prof. Zygmunt J. Haas 27 Sectoring An example No Sectoring N=3 Interferer X Y Distance A 1 A 2 A1 2R R 3 R 7 A2 2R A3 2. 5R R 3/2 R 7 A 6 A 0 A 3 A4 R 2R 3 R 13 A5 4R A 5 A 4 A6 3. 5R R 3/2 R 13 S I S I rec rec P R P R R R R R R t t db (assuming =4) Wireless Networks Laboratory Prof. Zygmunt J. Haas 28 1 Prof. Zygmunt J. Haas 14

15 Sectoring An example Sectoring N=3 Interferer X Y Distance A 1 A 2 A5 4R A6 3. 5R R 3/2 R 13 S I S I rec rec A 6 Pt R P t A 0 A 5 A 4 (assuming =4) A 3 ( 13) R 4R 3.61 (4) dB 1 There are two potential worst-case locations of the mobile; on the cell circumference and on the edge of the sector lines. Consideration of both of the locations reveals that the worst-case condition is as marked in the figure above. Wireless Networks Laboratory Prof. Zygmunt J. Haas 29 Sectoring An example 60 0 Sectoring N=3 Interferer X Y Distance A5 4R A 1 A 2 S I S I rec rec P t A 6 P R t 4 R A 0 A 5 A dB 4 (assuming =4) A 3 By properly orienting the antennas (sectors), as shown below, the number of first tier co-channel interferers can be reduced to one. Wireless Networks Laboratory Prof. Zygmunt J. Haas 30 Prof. Zygmunt J. Haas 15

16 Sectoring An example N=3 =4 Case # Sectors per Cell # of Interferers SIR No Sectoring [db] 120 o Sectoring [db] 60 o Sectoring [db] But what about capacity? As N remains the same, the number of channels per cell remains the same. However, now these channels are partitioned into groups (equal to the number of sectors. How does this affect the capacity? Wireless Networks Laboratory Prof. Zygmunt J. Haas 31 Prof. Zygmunt J. Haas 16