Fundamentals of Wireless Communication PDF

Fundamentals of Wireless Communication Course Objective • Past decade has seen a surge of research activities in the field of wireless communication. • Emerging from this research thrust are new points of view on how to communicate effectively over wireless channels. • The goal of this course is t...

Fundamentals of Wireless Communication Course Objective • Past decade has seen a surge of research activities in the field of wireless communication. • Emerging from this research thrust are new points of view on how to communicate effectively over wireless channels. • The goal of this course is to study in a unified way the fundamentals as well as the new research developments. • The concepts are illustrated using examples from several modern wireless systems (GSM, IS-95, CDMA 2000 1x EV-DO, Flarion's Flash OFDM, ArrayComm systems.) Course Outline Day 1: Fundamentals 1. The Wireless Channel 2. Diversity 3. Capacity of Wireless Channels Course Outline (2) Day 2: MIMO 4. Spatial Multiplexing and Channel Modelling 5. Capacity and Multiplexing Architectures 6. Diversity-Multiplexing Tradeoff Course Outline (3) Day 3: Wireless Networks 7. Multiple Access and Interference Management: A comparison of 3 systems. 8. Opportunistic Communication and Multiuser Diversity 9. MIMO in Networks 1. The Wireless Channel Wireless Mulipath Channel Channel varies at two spatial scales: large scale fading small scale fading Large-scale fading • In free space, received power attenuates like 1/r2. • With reflections and obstructions, can attenuate even more rapidly with distance. Detailed modelling complicated. • Time constants associated with variations are very long as the mobile moves, many seconds or minutes. • More important for cell site planning, less for communication system design. Small-scale multipath fading • Wireless communication typically happens at very high carrier frequency. (eg. fc = 900 MHz or 1.9 GHz for cellular) • Multipath fading due to constructive and destructive interference of the transmitted waves. • Channel varies when mobile moves a distance of the order of the carrier wavelength. This is 0.3 m for Ghz cellular. • For vehicular speeds, this translates to channel variation of the order of 100 Hz. • Primary driver behind wireless communication system design. Game plan • We wish to understand how physical parameters such as carrier frequency, mobile speed, bandwidth, delay spread impact how a wireless channel behaves from the communication system point of view. • We start with deterministic physical model and progress towards statistical models, which are more useful for design and performance evaluation. Physical Models • Wireless channels can be modeled as linear timevarying systems: where ai(t) and i(t) are the gain and delay of path i. • The time-varying impulse response is: • Consider first the special case when the channel is timeinvariant: Passband to Baseband Conversion • Communication takes place at [f_c-W/2, f_c+ W/2]. • Processing takes place at baseband [-W/2,W/2]. Baseband Equivalent Channel • The frequency response of the system is shifted from the passband to the baseband. • Each path is associated with a delay and a complex gain. Sampling Multipath Resolution Sampled baseband-equivalent channel model: where hl is the l th complex channel tap. and the sum is over all paths that fall in the delay bin System resolves the multipaths up to delays of 1/W . Flat and Frequency-Selective Fading • Fading occurs when there is destructive interference of the multipaths that contribute to a tap. Time Variations fc i’(t) = Doppler shift of the i th path Two-path Example v= 60 km/hr, f_c = 900 MHz: direct path has Doppler shift of + 50 Hz reflected path has shift of - 50 Hz Doppler spread = 100 Hz Types of Channels Statistical Models • Design and performance analysis based on statistical ensemble of channels rather than specific physical channel. • Rayleigh flat fading model: many small scattered paths Complex circular symmetric Gaussian . • Rician model: 1 line-of-sight plus scattered paths Correlation over Time • Specifies by autocorrelation function and power spectral density of fading process. • Example: Clarke’s (or Jake’s) model. Additive Gaussian Noise • Complete baseband-equivalent channel model: • Will use this throughout the course. 2. Diversity Main story • Communication over a flat fading channel has poor performance due to significant probability that channel is in deep fading. • Reliability is increased by provide more signal paths that fade independently. • Diversity can be provided across time, frequency and space. • Name of the game is how to expoited the added diversity in an efficient manner. Baseline: AWGN Channel y = x+ w BPSK modulation x = § a Error probability decays exponentially with SNR. Gaussian Detection Rayleigh Flat Fading Channel Rayleigh vs AWGN Typical Error Event BPSK, QPSK and 4-PAM • • • • BPSK uses only the I-phase.The Q-phase is wasted. QPSK delivers 2 bits per complex symbol. To deliver the same 2 bits, 4-PAM requires 4 dB more transmit power. QPSK exploits the available degrees of freedom in the channel better. Time Diversity • Time diversity can be obtained by interleaving and coding over symbols across different coherent time periods. Example:GSM • Amount of diversity limited by delay constraint and how fast channel varies. • In GSM, delay constraint is 40ms (voice). • To get full diversity of 8, needs v > 30 km/hr at fc = 900Mhz. Repetition Coding Geometry Deep Fades Become Rarer Performance Beyond Repetition Coding • Repetition coding gets full diversity, but sends only one symbol every L symbol times: does not exploit fully the degrees of freedom in the channel. • How to do better? Example: Rotation code (L=2) Rotation vs Repetition Coding Product Distance Antenna Diversity Receive Transmit Both Receive Diversity h1 h2 Transmit Diversity h1 h2 Space-time Codes • Transmitting the same symbol simultaneously at the antennas doesn’t work. • Using the antennas one at a time and sending the same symbol over the different antennas is like repetition coding. • More generally, can use any time-diversity code by turning on one antenna at a time. Alamouti Scheme Space-time Code Design Cooperative Diversity • Different users can form a distributed antenna array to help each other in increasing diversity. • Distributed versions of space-time codes may be applicable. • Interesting characteristics: – Users have to exchange information and this consumes bandwidth. – Operation typically in half-duplex mode – Broadcast nature of the wireless medium can be exploited. Frequency Diversity Approaches • Time-domain equalization (eg. GSM) • Direct-sequence spread spectrum (eg. IS-95 CDMA) • Orthogonal frequency-division multiplexing OFDM (eg. 802.11a ) ISI Equalization • Suppose a sequence of uncoded symbols are transmitted. • Maximum likelihood sequence detection is performed using the Viterbi algorithm. • Can full diversity be achieved? Reduction to Transmit Diversity MLSD Achieves Full Diversity OFDM OFDM Channel Uncertainty • In fast varying channels, tap gain measurement errors may have an impact on diversity combining performance • The impact is particularly significant in channel with many taps each containing a small fraction of the total received energy. (eg. Ultra-wideband channels) 3. Capacity of Wireless Channels Information Theory • So far we have only looked at uncoded or simple coding schemes. • Information theory provides a fundamental characterization of coded performance. • It succintly identifies the impact of channel resources on performance as well as suggests new and cool ways to communicate over the wireless channel. • It provides the basis for the modern development of wireless communication. Capacity of AWGN Channel Power and Bandwidth Limited Regimes Frequency-selective AWGN Channel Waterfilling in Frequency Domain Slow Fading Channel Outage for Rayleigh Channel Receive Diversity Transmit Diversity Repetition vs Alamouti Time Diversity Fast Fading Channel Waterfilling Capacity Transmit More when Channel is Good Performance Performance: Low SNR Summary • A slow fading channel is a source of unreliability: very poor outage capacity. Diversity is needed. • A fast fading channel with only receiver CSI has a capacity close to that of the AWGN channel: only a small penalty results from fading. • A fast fading channel with full CSI can have a capacity greater than that of the AWGN channel: fading now provides more opportunities for performance boost. • The idea of opportunistic communication is even more powerful in multiuser situations, as we will see.