- Количество слайдов: 48
EE 359 – Lecture 20 Outline l Announcements l l l Project due Friday at 5 pm (extension request due today). HW 8 due Friday at 5 (no late HWs: solns posted at 5). tbp evals at end of class (10 bonus poits) l l 2 nd Must be turned in no later than Monday, Dec. 6, at exam. Exam next Monday, 12/6, 9: 30 -1: 30, Gates B 01 Review of Last Lecture+RAKE Receivers l Course Summary l EE 359 Megathemes l Wireless Networks l Hot Research Topics l
2 nd Exam Announcements l 2 nd Exam next Monday, 12/6, 9: 30 -11: 30, Gates B 01 l Local SCPD student take in class, others contact Joice. l Open book/notes l Covers Chapters 9 -13 (and related prior material) l Similar format to first exam l Practice finals posted (10 bonus points) l Exam review session Thursday 5 -6 pm TCSEQ 102 l Extra OHs l l My OHs: Th 7 -8, F 4 -5 and by appt (none today). Rajiv: T 6 -7, W 5 -7, F 11 -12, Sa 3 -4, Email: TWTh 10 -11 pm.
Review of Last Lecture l l Introduction to Spread Spectrum Direct Sequence Spread Spectrum S(f) Info. Signal l l I(f) S(f)*Sc(f) I(f)*Sc(f) Receiver Input Despread Signal a. S(f)*Sc(f)[ad(t)+b(t-t)] Receiver Input Good properties Long versus short codes ISI Rejection br. S’(f) Despread Signal ISI rejection by code autocorrelation Maximal linear codes l l Interference Rejection S(f) -1 N -Tc 1 1 Tc NTc
RAKE Receiver l Multibranch receiver l l l Assume h(t) a 1 d(t)+a 2 d(t-Tc)+…+a. Nd(t-MTc) Branches synchronized to different MP components ISI with delay j. Tc on ith branch reduced by rsc((j-i)Tc) x y(t) Demod a 1 dk+ISI 1+n 1 sc(t) x Demod aidk+ISIi+ni sc(t-i. Tc) x Demod Diversity Combiner a. Mdk+ISIN+n. M sc(t-MTc) l Diversity combiner can use SC, MRC, or EGC ^ dk
Course Summary l Signal Propagation and Channel Models l Modulation and Performance Metrics l Impact of Channel on Performance l Fundamental Capacity Limits l Flat Fading Mitigation l Diversity l Adaptive Modulation ISI Mitigation l Equalization l Multicarrier Modulation l Spread Spectrum l
Future Wireless Networks Ubiquitous Communication Among People and Devices Wireless Internet access Nth generation Cellular Wireless Ad Hoc Networks Sensor Networks Wireless Entertainment Smart Homes/Spaces Automated Highways All this and more… • Hard Delay/Energy Constraints • Hard Rate Requirements
Design Challenges l Wireless channels are a difficult and capacitylimited broadcast communications medium l Traffic patterns, user locations, and network conditions are constantly changing l Applications are heterogeneous with hard constraints that must be met by the network l Energy, delay, and rate constraints change design principles across all layers of the protocol stack
Signal Propagation l Path Loss l Shadowing l Multipath d Pr/Pt d=vt
Statistical Multipath Model l Random # of multipath components, each with varying amplitude, phase, doppler, and delay l Narrowband channel l Signal amplitude varies randomly (complex Gaussian). l 2 nd order statistics (Bessel function), Fade duration, etc. l Wideband channel l Characterized by channel scattering function (Bc, Bd)
Modulation Considerations l Want high rates, high spectral efficiency, high power efficiency, robust to channel, cheap. l Linear Modulation (MPAM, MPSK, MQAM) Information encoded in amplitude/phase l More spectrally efficient than nonlinear l Easier to adapt. l Issues: differential encoding, pulse shaping, bit mapping. l l Nonlinear modulation (FSK) Information encoded in frequency l More robust to channel and amplifier nonlinearities l
Linear Modulation in AWGN l ML detection induces decision regions l Example: 8 PSK dmin l Ps depends on l # of nearest neighbors l Minimum distance dmin(depends on gs) l Approximate expression
Linear Modulation in Fading In fading gs and therefore Ps random l Metrics: outage, average Ps , combined outage and average. l Ts Outage Ps Ps(target) Ps Ts
Moment Generating Function Approach l Simplifies average Ps calculation l Uses alternate Q function representation l Ps reduces to MGF of gs distribution Closed form or simple numerical calculation for general fading distributions l Fading greatly increases average Ps. l
Doppler Effects l High doppler causes channel phase to decorrelate between symbols l Leads to an irreducible error floor for differential modulation l Increasing l power does not reduce error Error floor depends on Bd. Ts
ISI Effects l Delay spread exceeding a symbol time causes ISI (self interference). 0 l ISI leads to irreducible error floor l l Tm Increasing signal power increases ISI power ISI requires that Ts>>Tm (Rs<
Capacity of Flat Fading Channels l Three cases l Fading statistics known l Fade value known at receiver l and transmitter Optimal Adaptation l Vary rate and power relative to channel l Optimal power adaptation is water-filling l Exceeds AWGN channel capacity at low SNRs l Suboptimal techniques come close to capacity
Variable-Rate Variable-Power MQAM One of the M(g) Points log 2 M(g) Bits Uncoded Data Bits M(g)-QAM Modulator Power: S(g) Point Selector Delay To Channel g(t) BSPK 4 -QAM 16 -QAM Goal: Optimize S(g) and M(g) to maximize EM(g)
Optimal Adaptive Scheme l Power Water-Filling gk l g Spectral Efficiency g Equals Shannon capacity with an effective power loss of K.
Practical Constraints l Constellation restriction l Constant power restriction l Constellation updates. l Estimation error. l Estimation delay.
Diversity l Send bits over independent fading paths l Combine l Independent fading paths l Space, l paths to mitigate fading effects. time, frequency, polarization diversity. Combining techniques l Selection combining (SC) l Equal gain combining (EGC) l Maximal ratio combining (MRC)
Diversity Performance l Maximal Ratio Combining (MRC) l l l Optimal technique (maximizes output SNR) Combiner SNR is the sum of the branch SNRs. Distribution of SNR hard to obtain. Can use MGF approach for simplified analysis. Exhibits 10 -40 d. B gains in Rayleigh fading. Selection Combining (SC) Combiner SNR is the maximum of the branch SNRs. l Diminishing returns with # of antennas. l CDF easy to obtain, pdf found by differentiating. l Can get up to about 20 d. B of gain. l
Multiple Input Multiple Output (MIMO)Systems l MIMO systems have multiple (M) transmit and receiver antennas l With perfect channel estimates at TX and RX, decomposes to M indep. channels l l l M-fold capacity increase over SISO system Demodulation complexity reduction Beamforming alternative: Send same symbol on each antenna (diversity gain) l Diversity versus capacity tradeoff l
Digital Equalizers n(t) d(t)=Sdnp(t-n. T) l g*(-t) Heq(z) Typically implemented as FIR filter. Criterion for coefficient choice l l + ^ dn Equalizer mitigates ISI l l c(t) yn Minimize Pb (Hard to solve for) Eliminate ISI (Zero forcing, enhances noise) Minimize MSE (balances noise increase with ISI removal) Channel must be learned through training and tracked during data transmission.
Multicarrier Modulation l Divides bit stream into N substreams l Modulates substream with bandwidth B/N l l Separate subcarriers B/N
Fading Across Subcarriers l Compensation techniques l Frequency equalization (noise enhancement) l Precoding (channel inversion) l Coding across subcarriers l Adaptive loading (power and rate) l Practical Issues for OFDM l Peak-to-average power l System imperfections ration
Direct Sequence Spread Spectrum l Bit sequence modulated by chip sequence s(t) sc(t) Sc(f) S(f)*Sc(f) 1/Tb Tc Tb=KTc 1/Tc l Spreads bandwidth by large factor (K) l Despread by multiplying by sc(t) again (sc(t)=1) l Mitigates ISI and narrowband interference 2 l l ISI mitigation a function of code autocorrelation Must synchronize to incoming signal
RAKE Receiver l Multibranch receiver l y(t) Branches synchronized to different MP components x Demod sc(t) x Demod sc(t-i. Tc) x Diversity Combiner ^ dk Demod sc(t-NTc) l These components can be coherently combined l Use SC, MRC, or EGC
Megathemes of EE 359 l The wireless vision poses great technical challenges l The wireless channel greatly impedes performance l l Low fundamental capacity. Channel is randomly time-varying. ISI must be compensated for. Hard to provide performance guarantees (needed for multimedia). l We can compensate for flat fading using diversity or adapting. l MIMO channels promise a great capacity increase. l A plethora of ISI compensation techniques exist l Various tradeoffs in performance, complexity, and implementation.
Wireless Network Design l Broadcast and Multiple Access Channels l Spectral Reuse l Cellular System Design l Ad-Hoc Network Design l Networking Issues
Broadcast and Multiple Access Channels Broadcast (BC): One Transmitter to Many Receivers. Multiple Access (MAC): Many Transmitters to One Receiver. x x x h 1(t) x h 22(t) h 21(t) R 2 R 1 h 3(t) R 3
Bandwidth Sharing l Dedicated channel assignment Code Space l Time Frequency Division Frequency Code Space l Time Division Time Frequency Code Space l Code Division l Hybrid Schemes 7 C 29822. 033 -Cimini-9/97 Time Frequency
Multiple Access SS l Interference between users mitigated by code cross correlation a l l In downlink, signal and interference have same received power In uplink, “close” users drown out “far” users (near-far problem) a
Multiuser Detection l In all CDMA systems and in TD/FD/CD cellular systems, users interfere with each other. l In most of these systems the interference is treated as noise. Systems become interference-limited l Often uses complex mechanisms to minimize impact of interference (power control, smart antennas, etc. ) l l Multiuser detection exploits the fact that the structure of the interference is known Interference can be detected and subtracted out l Better have a darn good estimate of the interference l
RANDOM ACCESS TECHNIQUES Random Access l Dedicated channels wasteful for data l l use statistical multiplexing Techniques l l Aloha Carrier sensing l l l Reservation protocols PRMA Retransmissions used for corrupted data Poor throughput and delay characteristics under heavy loading l 7 C 29822. 038 -Cimini-9/97 Collision detection or avoidance Hybrid methods
Cellular System Design BASE STATION l l l Frequencies, timeslots, or codes reused at spatiallyseparate locations Efficient system design is interference-limited Base stations perform centralized control functions l Call setup, handoff, routing, adaptive schemes, etc.
Design Issues l Reuse distance l Cell size l Channel assignment strategy l Interference management l Power adaptation l Smart antennas l Multiuser detection l Dynamic resource allocation 8 C 32810. 44 -Cimini-7/98
Dynamic Resource Allocation Allocate resources as user and network conditions change l Resources: l l l l Channels Bandwidth Power Rate Base stations Access BASE STATION Optimization criteria l l l Minimize blocking (voice only systems) Maximize number of users (multiple classes) Maximize “revenue” l Subject to some minimum performance for each user
Ad-Hoc Networks l Peer-to-peer communications l l l No backbone infrastructure or centralized control Routing can be multihop. Topology is dynamic. Fully connected with different link SINRs Open questions l l l Fundamental capacity Optimal routing Resource allocation (power, rate, spectrum, etc. ) to meet Qo. S
Power Control l Assume each node has an SIR constraint l Write the set of constraints in matrix form l If r. F<1 a unique solution l P 2 Power control algorithms l Centralized or distributed Feasible Region P* Iterative Algorithm P 1 Power control for random channels more complicated
Wireless Networks with Energy -Constrained Nodes l Limited node processing/communication capabilities l Nodes can cooperate in transmission and reception. l Intelligence must be “in the network” l Data flows to centralized location. l Low per-node rates but 10 s to 1000 s of nodes l Data highly correlated in time and space.
Energy-Constrained Nodes l Each node can only send a finite number of bits. l l l Energy minimized by sending each bit very slowly. Introduces a delay versus energy tradeoff for each bit. Short-range networks must consider both transmit and processing energy. Sophisticated techniques not necessarily energy-efficient. l Sleep modes save energy but complicate networking. l l Changes everything about the network design: l l l Bit allocation must be optimized across all protocols. Delay vs. throughput vs. node/network lifetime tradeoffs. Optimization of node cooperation.
Higher Layer NETWORK ISSUES Networking Issues l Architecture l Mobility Management l Identification/authentication l Routing l Handoff l Control l Reliability and Quality-of-Service 8 C 32810. 53 -Cimini-7/98
Wireless Applications and Qo. S Wireless Internet access Nth generation Cellular Wireless Ad Hoc Networks Sensor Networks Wireless Entertainment Smart Homes/Spaces Automated Highways All this and more… Applications have hard delay constraints, rate requirements, and energy constraints that must be met These requirements are collectively called Qo. S
Challenges to meeting Qo. S l Wireless channels are a difficult and capacitylimited broadcast communications medium l Traffic patterns, user locations, and network conditions are constantly changing l No single layer in the protocol stack can guarantee Qo. S: cross-layer design needed l It is impossible to guarantee that hard constraints are always met, and average constraints aren’t necessarily good metrics.
Crosslayer Design l Application Network l Access l Link l l Delay Constraints Rate Requirements Energy Constraints Mobility Hardware Optimize and adapt across design layers Provide robustness to uncertainty Schedule dedicated resources
4 G l Is 4 G an evolution, an alternative, or a supplement to 3 G, or something more? l What services should 4 G support? l Research challenges associated with 4 G: Air interface l Flexible Qo. S l Support for heterogeneous services l Cross-layer design l
Promising Research Areas l Link Layer l l l Cellular Systems l l How to use multiple antennas Cross-layer design Sensor networks l l l How to use multiple antennas Multihop routing Variable Qo. S Ad Hoc Networks l l l Wideband air interfaces and dynamic spectrum management Practical MIMO techniques (modulation, coding, imperfect CSI) Energy-constrained communication Cooperative techniques Information Theory l l l Capacity of ad hoc networks Imperfect CSI Incorporating delay: Rate distortion theory for networks
The End l Thanks!!! l Have a great winter break