Cellular Systems and Infrastructure- Based Wireless Networks

Transcription

1 Cellular Systems and Infrastructure- Based Wireless Networks

2 ABSTRACT Infrastructure-based wireless networks have base stations (access points). Advantages over Ad-hoc networks : - efficiently utilize network resources. - single-hop routes, results in : - lower delay and loss - higher data rates Examples : Wireless LANs, paging systems, and cellular phone systems.

3 References [1] Andrea Goldsmith, "Wireless Communications", Cambridge University Press, [2] David Tse; Pramod Viswanath, "Fundamentals of Wireless Communication", Cambridge University Press, [3] Simon Haykin, "Communication Systems", John Willy & sons, [4] William Stallings, "Data and Computer Communications", Pearson Education, [5] Lucent Technologies; Bell Labs Innovations, "GSM Introduction WL9001", 1998.

4 OUTLINE Cellular System Fundamentals Interference Reduction Techniques Reuse Distance D Dynamic Resource Allocation diamond-shaped Cells Scheduling Hexagonally-shaped cells DCA Power Control SINR & User Capacity Fundamental Rate limits Shannon s Capacity Area Spectral Efficiency Case Study

5 Cellular System Fundamentals: Channel Reuse Different channel sets Ci are assigned to different cells. Adjacent cells are assigned different channel sets to avoid interference. Cells sufficiently spaced from each other can use the same channel set to in crease system capacity ( cochannels).

6 Cellular System Fundamentals: Handover is the process of automatically switching a call in progress from one traffic channel to another to neutralize the adverse effects of user movements [5]

7 Cellular System Fundamentals: Access Techniques Time Division Multiple Access (TDMA), the time axis is divided into nonoverlapping time slots, and each user is assigned a different cyclically-repeating timeslot to transmit during it.

8 Cellular System Fundamentals: Access Techniques Frequency Division Multiple Access (FDMA), the frequency axis is divided into nonovelapping channels, and each user is assigned a different frequency channel to transmit over it. The channels usually have guard bands to overcome imperfect filters effects and adjacent channel interference

9 Cellular System Fundamentals: Access Techniques Code Division Multiple Access (CDMA), information of different users are modulated by orthogonal or nonorthogonal spreading codes. The resulting spread signals simultaneously occupy the same time and bandwidth.

10 Cellular System Fundamentals: Access Techniques Space Division Multiple Access (SDMA), user can access the channel at the same time and the same frequency by exploiting the spatial separation of the individual user. multibeam (directional) antennas are used to separate radio signals by pointing them along different directions

11 Cellular System Fundamentals: Cell Size Shrinking the size of a cell increases the number of users as long as all aspects of the system scale so that SINR remains the same.

12 Cellular System Fundamentals: Cell Shape

13 Cellular System Fundamentals: Reuse Distance D the distance between the centers of cells that use the same channels. is a function of cell shape, cell size, and the number of intermediate cells between the two cells sharing the same channel.

14 Cellular System Fundamentals: Reuse Distance D For Diamond-shaped cells; D = R + 2RNI + R = 2R (NI + 1) NI, no, of intermediate cells any two between co-channel cells.

15 Cellular System Fundamentals: Reuse Distance D For hexagonally-shaped cells; E. g. cell G is located at (0, 1), cell S is located at (1, 1), cell P is located at ( 2, 2), and cell M is located at ( 1, 1).

16 Cellular System Fundamentals: Cell Clustering For diamond-shaped cells a tesselating cell cluster forms another diamond, with K cells on each side (K = 4 in fig.) The number of cells per cluster is N = K², which is also called the reuse factor: since D = 2KR, we have N =.25(D/R),

17 Cellular System Fundamentals: Cell Clustering For hexagonally-shaped cells: total BW is broken into N channel sets C1,..., CN,,N =cluster size Strating from origin, assign channels as shown (move i cells and then move j cells Then start from another arbitrary cell, and so on until cells assigned channels.

18 Cellular System Fundamentals: Cell Clustering

19 SINR & User Capacity SINR Orthogonal Channelization (TDMA & FDMA): Intercell Interfernce (Co-channel interference) Non-Orthogonal Channelization (CDMA): Intercell Interference + intracell Interfernce

20 SINR & User Capacity SINR Pr is the received signal power, PI is the received power associated with both intracell and intercell interference, and N0B is noise power.

21 SINR & User Capacity SIR Good cellular system designs are interference-limited [1] i. e. PI >> N0B N0B zero SIR = Pr / PI

22 SINR & User Capacity example: SIR (Uplink TDMA) the simplified path loss model d=propagation distance; K is a unitless constant depends on antenna characteristics and average channel attenuation, do is a reference distance for the antenna far-field, and γ is the path loss exponent, the value of γ depends on the propagation environment: for free-space model 2 γ 4

23 SINR & User Capacity example: SIR ( uplink TDMA) Setting do = 1 m for our calculations yields γi = pathloss exponent (in-cell propagation) γo= pathloss exponent intercell interference) M = no. of interferers

24 SINR & User Capacity example: SIR ( uplink TDMA) For simplicity, If d = R, and all interferes are located at reuse distance D, then and if γi = γo = γ this yields

25 SINR & User Capacity User Capacity (Cu) The user capacity Cu is defined as the total number of active users per cell that the system can support while meeting a common BER constraint for all users [1]. the user capacity Cu = Nc,N c = No. of channels assigned to any given cell.

26 SINR & User Capacity User Capacity (Cu) For orthogonal multiple access, B=BW Bs= channel BW NT= total No. Of orthogonal Channels N=reuse factor G=Ratio of total BW to individual user BW

27 Interference Reduction Techniques Multipath can cause fading due to phase cancellation between different propagation paths which reduce signal power against noise. Delay Spread results from differences in propagation delays among multiple propagation delay, this delay spread can lead to a significant intersymbol interference in the received signal. Co-channel interference.

28 Interference Reduction Techniques Antenna Sectorization directional antennas to divide up a base station's 360 omnidirectional antenna to N sectors interference to a given mobile comes primarily from its sector reducing interference power by roughly a factor of N

29 Interference Reduction Techniques Smart Antennas consists of an antenna array combined with signal processing in both time and space. form narrow beams to provide high gain to the desired user's signal and can provide spatial nulls in the direction of interference

30 Interference Reduction Techniques other techniques Interference Averaging. Multiuser Detection. Interference Precancellation.

31 Dynamic Resource Allocation Cellular systems are dynamic in the number of users in any given cell and in their time-varying channel gains. As voice applications are migrated with Multimedia data, user no longer have uniform data rate requirements.

32 Dynamic Resource Allocation a flexible resource allocation is required to dynamically assign channels, data rates, and power levels relative to the current system conditions and user needs.

33 Dynamic Resource Allocation Scheduling dynamically allocate resources to mobile users according to their required data rates and delay constraints. exploits multiuser diversity to allocate resources to the user with the best channel. unfair to users with inferior channels.

34 Dynamic Resource Allocation Dynamic Channel Allocation Falls into two categories, Dynamic assignment of multiple channels within a cell (intracell DCA). Assignment of channels between cells (intercell DCA) for orthogonal channelization.

35 Dynamic Resource Allocation Dynamic Channel Allocation Intracell DCA allows dynamic assignment of multiple channels within a cell to a given user. In TDMA systems this is done by assigning a user multiple timeslots, and in CDMA by assigning a user multiple codes and/or spreading factors.

36 Dynamic Resource Allocation Dynamic Channel Allocation In intercell DCA, every channel is available in every cell, i.e. no fixed channel reuse pattern exists. Each channel can be used in every cell as long as SIR requirements of each user are met. Thus, channels are assigned to users as needed.

37 Dynamic Resource Allocation Power Control The goal of power control is to adjust the transmit powers of all users such that the SINR of each user meets a given threshold required for acceptable performance.

38 Dynamic Resource Allocation Power Control power control on the uplink results in more reduction of intercell interference since the transmission can come from cell boundaries which cause intercell interference to neighbors cells.

39 Dynamic Resource Allocation Power Control In an uplink with K interfering users we denote the SIR for the kth user as

40 Dynamic Resource Allocation Power Control Assume SIR requirement of the Kth user is By substituting in the previous equation and representing it in matrix form we get Where, is the transmitted powers vector,

41 Dynamic Resource Allocation Power Control u is the column vector of noise powers scaled by the SIR constraints and channel gain, and F is an irreducible matrix with non-negative elements given by

42 Dynamic Resource Allocation Power Control The SIR requirements of all users are satisfied with which meets the SIR requirements with the minimum transmitted power of the users.

43 Dynamic Resource Allocation Power Control Iterative Algorithm: requires only SIR information at each transmitter.

44 Fundamental Rate Limits Shannon's Capacity of Cellular Systems C = B LOG2 ( 1 + SNR ) bps a bound on the rate of data transmission and a measure for the efficiency of the communication system η = R / C trade-off between channel bandwidth and received SNR. a framework for comparing noise performance between the different modulation schemes.

45 Fundamental Rate Limits Shannon's Capacity of Cellular Systems Under full base stations cooperation assumption :base stations can be viewed as a single base station with multiple geographically-dispersed antennas and treated. The system then can be treated as MIMO ( in uplink an in down link)

46 Fundamental Rate Limits Shannon's Capacity of Cellular Systems and by characterizing the propagation between mobiles and the multiple-antenna base station (uplink) using AWGN model with unity channel gain within a cell and a channel gain of α, 0 α 1, between cells

47 Fundamental Rate Limits Shannon's Capacity of Cellular Systems Then, The per-user capacity which defined as the maximum possible rate that all user can maintain simultaneously is [1] where B is the total system bandwidth, NoB is the noise PSD, K is the number of mobiles per cell, and P is the average transmit power of each mobile.

48 Fundamental Rate Limits Shannon's Capacity of Cellular Systems Under no base station cooperation Assumption, So, receivers in each cell treat signal from other cell as interference reflects the practical design of cellular systems Unfortunately, Shannon s theory in channels with interference is mostly unsolved [1].

49 Fundamental Rate Limits Area Spectral Efficiency (ASE) ASE is a capacity measure that allows the the reuse distance, to be optimized relative to fundamental capacity limits. Since the reuse distance D, is the distance between any two cells use the same channel, then the area cover by each channel is approximately the area of a circle with radius 0.5D, i. e. A = π (.5D)².

50 Fundamental Rate Limits Area Spectral Efficiency (ASE) The system throughput ( Sum-Rate) is given by

51 Fundamental Rate Limits Area Spectral Efficiency (ASE) The ASE of a cell is defined as the throughput/hz/unit area that is supported by a cell s resources

52 Case Study: AWGN TDMA System Uplink K users Cell Radius R All user assigned equal time slots Tk = 1/ K All user transmit the same power P 6 interferers (blue dots) to B.S. of the center cell

53 Case Study: AWGN TDMA System Uplink Using Simplified Path Loss Model Setting do = 1 m for our calculations yields

54 Case Study: AWGN TDMA System Uplink The received signal power of the kth user (red dot) by his base station is Interfernce caused by 6 interferers is where 2 γ 4.

55 Case Study: AWGN TDMA System Uplink The maximum rate for the kth user in the cell Rk is and the ASC1 is where Ck = Rk.

56 Plots [1] of Ae versus D for γ=4 and γ=2 with the cell radius normalized to R=1

57 Case Study: AWGN TDMA System Uplink If all interferers are at a distance D R/2 from the base station of the center cell, then the ASE2 is

58 Plots of ASE2 along with ASE1 for γ = 4

59 CONCLUSION Well designed cellular systems are interferencelimited. The dynamic nature of cellular system in load and channel conditions requires a dynamic resource allocation to efficiently utilize these resources. Shannon s Capacity of channels with interference (Cellular Systems) is a longstanding open problem. The optimization of reuse distance D relative capacity limits is based on ASE.

60 References [1] Andrea Goldsmith, "Wireless Communications", Cambridge University Press, [2] David Tse; Pramod Viswanath, "Fundamentals of Wireless Communication", Cambridge University Press, [3] Simon Haykin, "Communication Systems", John Willy & sons, [4] William Stallings, "Data and Computer Communications", Pearson Education, [5] Lucent Technologies; Bell Labs Innovations, "GSM Introduction WL9001", 1998.