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Wireless Communication Cellular Systems

Wireless Communication Cellular Systems. Sharif University of Technology. Fall 1395 Afshin Hemmatyar. The total Bandwidth is divided into a number of narrowband (200KHz) channels. 8 Users are given time slots in each narrowband channel.

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Wireless Communication Cellular Systems

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  1. Wireless CommunicationCellular Systems Sharif University of Technology Fall 1395 AfshinHemmatyar

  2. The total Bandwidth is divided into a number of • narrowband (200KHz) channels. • 8 Users are given time slots in each narrowband • channel. • So GSM is a combination of FDMA and TDMA. • Multiple access is orthogonal that means users • within the cell never interfere with each other. Most Widespread Example: GSM

  3. Access Method FDMA/TDMA • Frequency Band 900MHz and 1800MHz • No. of Channels 125 radio carriers • Max No. of user channels 125*8 = 1000 channels • Channel Bandwidth 200KHz • Uplink (MS  BS) Freq. BW. 890 to 915MHz • Downlink (BS -> MS) Freq. BW 935 to 960MHz • Modulation Digital GMSK • (Gaussian Minimum Shift Keying) • Speech Coding RPE-LTP • (Regular Pulse Excited- Long Term Prediction) • Speech Bit Rate 13Kbps • Data Bit Rate 12Kbps The GSM Specifications

  4. Assume we have S frequency channels available for our • mobile system. • For GSM, we have 125 frequency channels and 8 time slots • per channel thus S is equal to 1000. • How many people can speak at the same time in a city with • that many channels? • If we use 1000 channels for the whole city with one Base • station then obviously 1000 people can talk at the same time. • Then, how many people are actually speaking simultaneously • with their phones in Tehran? Why We Use Cellular Systems?

  5. Divide the area into “Cells” with different “Base Stations”. • Frequencies/Timeslots/Codes reused at spatially-separated • locations. • Cells should be far enough so that signals do not interfere. Cells and Base Stations

  6. Base Stations/”Mobile Switching Centers” (MSC) coordinate • handoff and control functions. • Shrinking cell size increases capacity, as well as networking • cost and burden. Mobile Switching Center

  7. Why hexagonal cells? • They give the maximum distance to center for minimum • number of cells to cover an area. • Are cells so uniform in reality? • They are designed based on uniform design. • In reality base stations are closed to designed locations. • Real footprints should be simulated or measured in real deployments. Cell Shape

  8. S: Total number of channels • K: Number of channels in each cell • N: Number of cells that in total use all S • channels • N cells form a “cluster” • N is usually 1, 3, 4, 7, or 12 Reuse Concept

  9. Note that choice of cluster size (N) is independent from actual size of cells, so for fair comparison, assume identical cell sizes and decide on best value of N. Cluster Size (1)

  10. If we use M clusters in an area, the total capacity (number • of users that can talk at the same time) will be: • C = M.S = M.K.N • Assume, number of cells in the area is fixed (cell size is • fixed) thus M.N is fixed. • Therefore , to maximize C, should maximize K (number of • channels per cell) • S = K.N thus minimize N for highest capacity • Decreasing N causes • Higher capacity but higher interference as well • Therefore, for a given mobile system we should first specify • how much interference we can tolerate. • Then, choose the smallest value of N that ensures that • amount of interference. Cluster Size (2)

  11. Distance between Cells Same Cells Adjacent Cells R j.d d = 2Rcos30o = R√3 i.d D = d√(i2 - 2ijcos120o + j2) = d√(i2 + ij + j2) = R√3 √(i2 + ij + j2)

  12. No. of Channels per Cell • For hexagonal cells we have: • N = i2 + i.j + j2 Reuse distance is D = R√(3N) • Example: AMPS • Total BW = 25MHz • Each channel = 30KHz simplex • For N = 4, 7, 12 we will have • 104, 59 and 34 channels per cell

  13. The terminology of capacity for cellular system is not • related to Shannon capacity! • Here capacity means the number of users a cellular • system can support. • Co-channel interference inherent in cellular systems • due to frequency reuse . • Mobile systems are designed to be • interference limited and not noise limited. • Co-channel interference can not be reduced by • increasing Tx power, only can be reduced by having • enough separation between co-channel sites. • Therefore, interference computation is the main way of • estimating capacity. Interference and System Capacity (1)

  14. How should we find the best possible N? • The starting point in mobile system design is the • minimum acceptable Signal to Interference Ratio • (SIRmin ) level at receiver. • Then, we need to find out the relation between SIRmin • and Nmin. • Pr=P0(d/d0)-n •  S=P0(R/d0)-n(R is radius of the cell) • and Ii=P0(Di/d0)-n(Di is distance between co-channel cells) • Ii is ith co-channel interference thus Di is the same for • all co-channel cells (Di=D). • SIR=S/∑Ii=R-n/∑Di-n • =(D/R)n/NC(NC is the number of co-channel cells) • For hexagonal cells NC=6 thus SIR=(D/R)n/6 Interference and System Capacity (2)

  15. Q=D/R is Co-channel Reuse Ratio • For Hexagonal cells Q=D/R=R√(3N)/R=√(3N) • SIR=(√(3N))n/6 N=10(2log(6SIR)/n)/3 • Example1: AMPS  SIRmin=18dB=63.1 • Assuming n=4 Nmin=7 • Example2: GSM  SIRmin=12dB=15.8 • Assuming n=4 Nmin=4 • Example3: SIRmin=15dB=31.6 • Assuming n=4 Nmin=7 • Assumingn=3 Nmin=12 • So better propagation will lead to larger values of N, • which will decrease capacity. Interference and System Capacity (3)

  16. Fixed Assignment • Can also use borrowing in advances system • Dynamic assignment • Measure RSSI (Radio Signal Strength Indicator), • Traffic distribution, and channel occupancy • Mostly fixed assignment used in practice. Channel Assignment (1)

  17. In reality, channel planning is a complex optimization • problem, that need to use special program. • Part of mobile channels are devoted to signaling. Thus • we should to use better reuse ratio (for example 12 • instead of 7) • In CDMA systems in theory, reuse ratio “1” can be • used. • In practice, we don’t assign co-channel frequencies to • neighboring cells to control interference levels. • Also an “equivalent reuse ratio” can be defined for • CDMA systems. Channel Assignment (2)

  18. If Rx filters were ideal then “Adjacent Channel • Interference” was not important. • But in reality filters are not ideal and so adjacent • channel signals may also enter the receiver. • Highest Adjacent Channel Interference when desired • user at cell boundaries. • In practice Adjacent channels are not used in the • same cell or even in neighboring cells. Adjacent Channel Interference (1)

  19. Example: • In same cell scenario, if another user is much closer • to the base than the desired user, its adjacent • channel signal can cause significant interference. • Assume the ratio of distance from the two sources • to the base (D1/D2), is equal to 20, then SIR =20-n • which for n=4 is equal to -52dB. • If Rx filter slope is 20dB/oct, at least 6 channel • separation (each 200KHz) between users is • required. • In practice some sort of “power control” is used (more • important in CDMA). Adjacent Channel Interference (2)

  20. Need to change base stations as we cross cell • boundaries. • Sounds easy, but is not! • Handoff (or Handover) mechanism should be such • that: • Least number of handoffs • More successful handoffs • Threshold Setting: • Lower threshold -> More call cutoff probability • Higher threshold  More Handoffs. Handoff (1)

  21. Signals should also be averaged over time, otherwise • signals get disconnected due to fading. • Should also consider velocity in Handoff process. • Should monitor other Base Station signals as well. • Channel Reservation for Handoff • Soft Handoff in CDMA systems. Handoff (2)

  22. Lets assume we have to cover a city with our mobile • system. • Simple question: • For a given number of subscribers, • how many channels should we assign to that area? • In practice, for a telephony system when you want to • cover N subscribers, you do not assign N channel to • them. This is due to the fact that subscribers connect • to network only occasionally. • For example, in an office with N employees, the • number of lines that talk at the same time is only a • fraction of N. • Obviously we need to define an acceptable quality • level that based on that we can find required number • of channels for a given N. Trunking Theory (1)

  23. Trunking concept: • Allowing large number of users to share • relatively small number of channels based on the fact users use the channel statistically over time • Based on a quantitative measure of acceptable • service, N can be found. • Acceptable service quality in trunking theory is defined • based on the measureable “Grade of Service” (GoS)_ • parameter. • GoS is usually defined based on the following two • parameters: • “Blocking Rate” which is the probability of getting • a busy tone when trying to dial a number. • “Waiting Period” to get the number through (for • queued systems). Trunking Theory (2)

  24. Basic definition: • Blocked Call: A call that can not get through • Holding Time: Average duration of a call (H in sec) • Request Rate: Average number of requested calls • in unit of time for each user (λ in 1/sec) • Erlang: One Erlang is the amount of traffic that will • completely occupy the channel for the given period • of time. • Example: If a channel in one hour is only occupied for • 30 minutes then the traffic of that channel is 0.5 Erlangs. • Traffic Intensity: Average occupancy of one or more • channel (A in Erlangs) • GoS: • Possibility of blockage of a call (Erlang B formula) • Possibility of a connection with a delay more than a • specific value (Erlang C formula) Trunking Theory (3)

  25. Traffic parameters: • Au: Average traffic offered by each user • A: Offered traffic by U users • AC: Average traffic of each channel • C: Number of available channels • Au=λ.H  A=U.Au AC=A/C • Note that if too much traffic is offered to a system, • than the actual traffic supported will at most be C • Erlangs if C channels are available. • The Gos defined for wireless system is different from • wired values: • For wired system GoS is about 0.5% • For wireless systems GoS of 2-5% is usually specified. • For example for 2% GoS at peak hours, 2 out of 100 • calls attempted by subscribers will be blocked. • You can guess what is the current GoS we have in Tehran! Trunking Theory (4)

  26. GoS Equations (Case 1: No queue) • Users try to call; if get busy signal, try at a later time. • Call requests are independent and have a Poisson • distribution: • λ=mean call arrival rate for all users=average of t1, t2, . . . • Call duration (holding times) have exponential • distribution: 1/μ= average of τ1, τ2, . . . Trunking Theory (5)

  27. GoS Equations (Case 1: No queue) • Then, for C channels in the system, it can be shown that the probability of blocking is given by: • A=λ.H=λ./μ is the total traffic offered to the system • The above equation is called the Erlang B formula. • (Bad) 1 ≥ GoS ≥ 0 (Good) Trunking Theory (6)

  28. Capacity of an Erlang B System Trunking Theory (7)

  29. Example 1 • How many users, assuming 0.1 Erlang traffic for • each user, can be supported for 0.5% blocking • probability for the following number of trunked • channels: 5, 10, 100 channels • C=5  1.13 Erlang traffic  11 users • C=10  3.96 Erlang traffic  39 users • C=100  80.9 Erlang traffic  809 users • Quick observation: for smaller number of channels, • the ratio of users to channels is around 2 but for • higher C, the ratio is around 8 • having larger pool of channels creates more • efficient trunking. Trunking Theory (8)

  30. Example 2 • Assume one million residents in a city. • Assume 49 cells with 100 channels per cell assigned • For 1% GoS and average calls of two 3 minute calls • per hour, find percentage of market penetration. • Au=λ.H=2(3/60)=0.1 Erlang • C=100  A=84.1 Erlang (total traffic) •  U=A/Au=84.1/0.1=841 user/cell • Total subscribers = 49x841= 41209 • Penetration =41209/1000000 x 100% = 4.12% Trunking Theory (9)

  31. Example 3 • City Area = 1300Km2 • Hexagonal cells radius = 4Km , and N = 7 • Total BW = 49MHz, and full duplex BW = 100KHz • GoS = 1%, and Offered traffic/user = 30 mErlang • Find: • Number of cells • Number of channels/cell • Traffic of each cell • Maximum carried traffic • Total number of users that can be served • Maximum number of serves users that can talk at the same time Truncing Theory (10)

  32. Example 3 • Cell area = 3√3/2 R2 ≈ 2.6R2 = 41.6Km2 •  number of cells = 1300/41.6 ≈ 31 cells • Total number of channels/cell = 49MHz/100KHz/7 = 70 channels • C = 70, GoS = 1%  A = 56.1 Erlang/cell • Maximum carried traffic = 56.1x31 = 1739.1 Erlang • Total number of users = 1739.1/0.03 = 57970 user • Maximum number of simultaneous calls = number of all channels = 70x31 = 2170 calls • So, about 2170/57970 x100% = 3.7% of users in the same area can talk at the same time. Truncing Theory (11)

  33. GoS Equations (Case 2: Blocked users queued) • In this scenario, blocked users will enter a queue. • The new model for such scenario is called Elrang C • formula. Trunking Theory (12)

  34. Channel Distribution • For example, if we have 10 channels, what happens if • we divide the set to two 5 channel sets? • Using bigger channel pools is better in statistical access • scenarios. • For the above example: • for 10 channels  4.46 Erlang • for 5 channels  1.36 Erlang • 1.36x2 = 2.72 < 4.46 Erlang • A set of 10 channels supports about 60% more traffic than two 5 channel sets. Trunking Theory (13)

  35. Trunking Efficiency • A measure of efficiency of trunking systems is: • η= Traffic (Erlang)/Number of channels x 100% • For smaller number of channels, the efficiency is • smaller. Trunking Theory (14)

  36. If we want to have more subscribers in an area, what • can we do? • Some common approaches: • Cell Splitting • Interference Reduction • Sectoring • Antenna Adjustment • Voice Activity Monitoring • Frequency Hopping • Smart Antennas • Interference Cancellation Capacity Increase (1)

  37. Cell Splitting • Diving cells into smaller cells. • More BTSs required with smaller height and smaller • power. • Use smaller cells (micro-cells and pico-cells) in more • crowded areas. • Frequency assignment is more complex in various-size • cells, but no other choice. Capacity Increase (2)

  38. Sectoring • Using directional antenna vs. omni-directional antennas • Why using directional antenna reduces interference? • Use of 120° antenna: • for N=3  number of co-channels down from 6 to 3 •  SIR: 17dB  20dB • for N=7  number of co-channels down from 6 to 2 •  SIR: 17dB  21.7dB Capacity Increase (3)

  39. Sectoring • SIR=(√(3N))n/NC • Omni Antenna  NC= 6 • 120° Antenna  NC= 2 • 60° Antenna  NC= 1 • So, by sectoring can get higher SIR and so can use • smaller N. • Disadvantages: • More equipment at BTS sites • More handoffs • Smaller trunking efficiency due to dividing channels • in each cell into three groups (Erlang B formula) • In general, sectoring is widely used in practical mobile • deployments. Capacity Increase (4)

  40. Sectoring Example • Assume GoS=1%, Avg. call duration=2 minutes, • Avg. 1 call per hour, total number of channels =395, • and N=7 • For omni antenna: • 395/7 channel  44.2 Erlang traffic  1326 call/hour • For 120° antenna: • SIR increases by a factor of 3 for 7-reuse • 395/7/3 channels/sector  11.2 Erlang/sector  33.6 Erlang •  1008 call/hour • So, if we don’t change N, we improve SIR, but lose capacity. • For 60° antenna: • SIR increases by a factor of 6  can reduce N from 7 to 4 • 395/4/6 channels/sector  9 Erlang/sector  54 Erlang •  1620 call/hour • So, if we can reduce N, by using sectored antenna, we may • regain the lost trunking efficiency. Capacity Increase (5)

  41. Other Means • Antenna height and tilt adjustment • Voice Activity • Every user is only talking at about 40% of time • V.A. is efficiency used in CDMA • Also incorporated in GSM as DTX (discontinuous transmission) • Frequency Hopping • Use a set of frequencies that can be swapped randomly • over time, instead of one fixed channel. • Widely used in GSM  also improves resistance to fading. • Two modes in GSM: Baseband and Synthesized • Hop rate is around 200Hz (slow rate hopping). • Since all channels are not used all the time statistically • reduces the interference (~2dB lower SIR requirement). • In theory, can marginally achieve N=1 (full reuse). • In practice, N=3 and N=4 are common. Capacity Increase (6)

  42. In a cellular design always pay attention to the • roles of two main factors: • Interference • Cluster size, Trunking Efficiency and Capacity • A change in system may improve one but degrade • another one. • In general, mobile planning and optimization is • a quite complicated and time consuming task • relying mainly on lots of experience. Summary

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