EC 723 Satellite Communication Systems Mohamed Khedr http://webmail.aast.edu/~khedr

Syllabus Tentatively Week 1 Overview Week 2 Orbits and constellations: GEO, MEO and LEO Week 3 Satellite space segment, Propagation and satellite links , channel modelling Week 4 Satellite Communications Techniques Week 5 Satellite Communications Techniques II Week 6 Satellite Communications Techniques III Satellite error correction Techniques Week 7 Multiple Access I Week 8 Multiple access II Week 9 Satellite in networks I, INTELSAT systems , VSAT networks, GPS Week 10 GEO, MEO and LEO mobile communications INMARSAT systems, Iridium , Globalstar, Odyssey Week 11 Presentations Week 12 Week 13 Week 14 Week 15 Tentatively

Frequency Shift Keying Two signals are used to convey information In principle, the transmitted signal appears as 2 sinx/x functions at carrier frequencies Each of the two states represents a single bit of information Each state persists for a single bit period and then may be replaced either state BER is: 2x BPSK BER for coherent for non-coherent Constant Modulus =>

Frequency Shift Keying

Other Modulations (cont.) M-ary PSK PSK with 2n states where n>2 Incr. spectral eff. - (More bits per Hertz) Degraded BER compared to BPSK or QPSK QAM - Quadrature Amplitude Modulation Not constant envelope Allows higher spectral eff.

M-ary PSK

M-ary QAM

Other Modulations OQPSK MSK QPSK One of the bit streams delayed by Tb/2 Same BER performance as QPSK MSK QPSK - also constant envelope, continuous phase FSK 1/2-cycle sine symbol rather than rectangular

Noncoherent receivers. (a) Quadrature receiver using correlators Noncoherent receivers. (a) Quadrature receiver using correlators. (b) Quadrature receiver using matched filters. (c) Noncoherent matched filter.

Output of matched filter for a rectangular RF wave: (a) q  0, and (b) q  180 degrees.

Noncoherent receiver for the detection of binary FSK signals.

Factors that Influence Choice of Digital Modulation Techniques A desired modulation scheme Provides low bit-error rates at low SNRs Power efficiency Performs well in multipath and fading conditions Occupies minimum RF channel bandwidth Bandwidth efficiency Is easy and cost-effective to implement Depending on the demands of a particular system or application, tradeoffs are made when selecting a digital modulation scheme.

Power Efficiency of Modulation Power efficiency is the ability of the modulation technique to preserve fidelity of the message at low power levels. Usually in order to obtain good fidelity, the signal power needs to be increased. Tradeoff between fidelity and signal power Power efficiency describes how efficient this tradeoff is made Eb: signal energy per bit N0: noise power spectral density PER: probability of error

Bandwidth Efficiency of Modulation Ability of a modulation scheme to accommodate data within a limited bandwidth. Bandwidth efficiency reflect how efficiently the allocated bandwidth is utilized R: the data rate (bps) B: bandwidth occupied by the modulated RF signal

Shannon’s Bound There is a fundamental upper bound on achievable bandwidth efficiency. Shannon’s theorem gives the relationship between the channel bandwidth and the maximum data rate that can be transmitted over this channel considering also the noise present in the channel. Shannon’s Theorem C: channel capacity (maximum data-rate) (bps) B: RF bandwidth S/N: signal-to-noise ratio (no unit)

Shannon Bound 1948 Shannon demonstrated that, with proper coding a channel capacity of Required channel quality for error free communications =>we’re doing much worse

Tradeoff between BW Efficiency and Power Efficiency There is a tradeoff between bandwidth efficiency and power efficiency Adding error control codes Improves the power efficiency Reduces the requires received power for a particular bit error rate Decreases the bandwidth efficiency Increases the bandwidth occupancy M-ary keying modulation Increases the bandwidth efficiency Decreases the power efficiency More power is requires at the receiver

Example: SNR for a wireless channel is 30dB and RF bandwidth is 200kHz. Compute the theoretical maximum data rate that can be transmitted over this channel? Answer:

Modulation Schemes Error Performance

M-ary PSK Error Performance

Operation Point Comparison

Union bound Union bound GMU - TCOM 507 - Spring 2001 Union bound Class: Feb-22-2001 Union bound The probability of a finite union of events is upper bounded by the sum of the probabilities of the individual events. Let denote that the observation vector is closer to the symbol vector than , when is transmitted. depends only on and . Applying Union bounds yields 2006-02-07 Lecture 5 (C) Leila Z. Ribeiro, 2001

Example of union bound Union bound: 2006-02-07 Lecture 5 GMU - TCOM 507 - Spring 2001 Example of union bound Class: Feb-22-2001 Union bound: 2006-02-07 Lecture 5 (C) Leila Z. Ribeiro, 2001

Upper bound based on minimum distance GMU - TCOM 507 - Spring 2001 Upper bound based on minimum distance Class: Feb-22-2001 Minimum distance in the signal space: 2006-02-07 Lecture 5 (C) Leila Z. Ribeiro, 2001

Example of upper bound on av. Symbol error prob. based on union bound GMU - TCOM 507 - Spring 2001 Example of upper bound on av. Symbol error prob. based on union bound Class: Feb-22-2001 2006-02-07 Lecture 5 (C) Leila Z. Ribeiro, 2001

Summary of Useful Formulas

Summary of Digital Communications -1 Legend of variables mentioned in this section: M = modulation size. (Ex: 2, 4, 16, 64) Bw = Bandwidth in Hertz  = Roll-off factor (from 0 to 1) Gc = Coding Gain (convert from dB to linear to use in formulas) Ov = Channel Overhead (convert from % to fraction : 0 to1) BER = Bit Error Rate

Summary of Digital Communications - 2 Bits per Symbol: Symbol Rate [symbol/second]: Gross Bit Rate [bps]: Net Data Rate [bps]:

BER Calculation as a Function of Modulation Scheme and Eb/No Available Equations given on next slide are used to calculate the bit error rate (BER) given the bit energy by spectral noise ratio (Eb/No) as input. These functions are used in their direct form for the bit error rate calculations. Excel and some scientific calculators provide the solution for the “erfc” function. The formulas provided can be inverted by numerical methods to obtain the Eb/No required as a function of the BER. Also possible to draw the graphic and obtain the “inverse” by graphical inspection.

BER Calculation as a Function of Modulation Scheme and Eb/No Available - 2

Maximum Likelihood (ML) Detection: Concepts

Likelihood Principle Experiment: The ball is black. Pick Urn A or Urn B at random Select a ball from that Urn. The ball is black. What is the probability that the selected Urn is A?

Likelihood Principle (Contd) Write out what you know! P(Black | UrnA) = 1/3 P(Black | UrnB) = 2/3 P(Urn A) = P(Urn B) = 1/2 We want P(Urn A | Black). Gut feeling: Urn B is more likely than Urn A (given that the ball is black). But by how much? This is an inverse probability problem. Make sure you understand the inverse nature of the conditional probabilities! Solution technique: Use Bayes Theorem.

Likelihood Principle (Contd) Bayes manipulations: P(Urn A | Black) = P(Urn A and Black) /P(Black) Decompose the numerator and denomenator in terms of the probabilities we know. P(Urn A and Black) = P(Black | UrnA)*P(Urn A) P(Black) = P(Black| Urn A)*P(Urn A) + P(Black| UrnB)*P(UrnB) We know all these values Plug in and crank. P(Urn A and Black) = 1/3 * 1/2 P(Black) = 1/3 * 1/2 + 2/3 * 1/2 = 1/2 P(Urn A and Black) /P(Black) = 1/3 = 0.333 Notice that it matches our gut feeling that Urn A is less likely, once we have seen black. The information that the ball is black has CHANGED ! From P(Urn A) = 0.5 to P(Urn A | Black) = 0.333

Likelihood Principle Way of thinking… Hypotheses: Urn A or Urn B ? Observation: “Black” Prior probabilities: P(Urn A) and P(Urn B) Likelihood of Black given choice of Urn: {aka forward probability} P(Black | Urn A) and P(Black | Urn B) Posterior Probability: of each hypothesis given evidence P(Urn A | Black) {aka inverse probability} Likelihood Principle (informal): All inferences depend ONLY on The likelihoods P(Black | Urn A) and P(Black | Urn B), and The priors P(Urn A) and P(Urn B) Result is a probability (or distribution) model over the space of possible hypotheses.

Maximum Likelihood (intuition) Recall: P(Urn A | Black) = P(Urn A and Black) /P(Black) = P(Black | UrnA)*P(Urn A) / P(Black) P(Urn? | Black) is maximized when P(Black | Urn?) is maximized. Maximization over the hypotheses space (Urn A or Urn B) P(Black | Urn?) = “likelihood” => “Maximum Likelihood” approach to maximizing posterior probability

Maximum Likelihood (ML): mechanics Independent Observations (like Black): X1, …, Xn Hypothesis  Likelihood Function: L() = P(X1, …, Xn | ) = i P(Xi | ) {Independence => multiply individual likelihoods} Log Likelihood LL() = i log P(Xi | ) Maximum likelihood: by taking derivative and setting to zero and solving for  Maximum A Posteriori (MAP): if non-uniform prior probabilities/distributions Optimization function P

OFDM GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 (C) Leila Z. Ribeiro, 2001

Motivation High bit-rate wireless applications in a multipath radio GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 Motivation High bit-rate wireless applications in a multipath radio environment. OFDM can enable such applications without a high complexity receiver. OFDM is part of WLAN, DVB, and BWA standards and is a strong candidate for some of the 4G wireless technologies. (C) Leila Z. Ribeiro, 2001

What is OFDM? Modulation technique Requires channel coding Solves multipath problems Transmitter: I/Q RF Source coding Channel coding / interleaving OFDM modulation I/Q-mod., up- converter Info Source e.g. Audio 0110 01101101 OFDM de-modulation Source decoding Down-converter, I/Q-demod. I/Q RF Decoding / deinter-leaving Receiver: Radio- channel Info Sink f PSD * f PSD fc -fc

Multipath Transmission GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 Multipath Transmission Fading due to constructive and destructive addition of multipath signals. Channel delay spread can cause ISI. Flat fading occurs when the symbol period is large compared to the delay spread. Frequency selective fading and ISI go together. (C) Leila Z. Ribeiro, 2001

Multipath Propagation GMU - TCOM 507 - Spring 2001 Multipath Propagation Class: Feb-22-2001 Reflections from walls, etc. Time dispersive channel Impulse response: Problem with high rate data transmission: inter-symbol-interference t [ns] p ( ) (PDP) Multipath Radio Channel (C) Leila Z. Ribeiro, 2001

Delay Spread Power delay profile conveys the multipath delay spread GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 Delay Spread Power delay profile conveys the multipath delay spread effects of the channel. RMS delay spread quantifies the severity of the ISI phenomenon. The ratio of RMS delay spread to the data symbol period determines the severity of the ISI. . Figure of a typical PDP used in WLAN say Channel A should be given along with the rms delay spread, this figure is available in the electronic format . Give an indication of the severity of the ISI in terms of the number of data symbols to the rms/max. delay spread .. Take the WLAN example (C) Leila Z. Ribeiro, 2001

Inter-Symbol-Interference Transmitted signal: Received Signals: Line-of-sight: Reflected: The symbols add up on the channel Delays  Distortion! Multipath Radio Channel

Concept of parallel transmission (1) GMU - TCOM 507 - Spring 2001 Concept of parallel transmission (1) Class: Feb-22-2001 Channel impulse response Time 1 Channel (serial) 2 Channels Channels are transmitted at different frequencies (sub-carriers) 8 Channels In practice: 50 … 8000 Channels (sub-carriers) OFDM Technology (C) Leila Z. Ribeiro, 2001

The Frequency-Selective Radio Channel GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 The Frequency-Selective Radio Channel -10 -5 5 10 15 20 Frequency Power response [dB] Interference of reflected (and LOS) radio waves Frequency-dependent fading Multipath Radio Channel (C) Leila Z. Ribeiro, 2001

Concept of parallel transmission (2) GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 Concept of parallel transmission (2) Channel impulse response Channel transfer function Frequency Time Signal is “broadband” 1 Channel (serial) Frequency 2 Channels Frequency 8 Channels Frequency Channels are “narrowband” OFDM Technology (C) Leila Z. Ribeiro, 2001

Concept of an OFDM signal Ch.1 Ch.2 Ch.3 Ch.4 Ch.5 Ch.6 Ch.7 Ch.8 Ch.9 Ch.10 Conventional multicarrier techniques frequency Ch.2 Ch.4 Ch.6 Ch.8 Ch.10 Ch.1 Ch.3 Ch.5 Ch.7 Ch.9 Saving of bandwidth 50% bandwidth saving Orthogonal multicarrier techniques frequency Implementation and System Model

A Solution for ISI channels GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 A Solution for ISI channels Conversion of a high-data rate stream into several low-rate streams. Parallel streams are modulated onto orthogonal carriers. Data symbols modulated on these carriers can be recovered without mutual interference. Overlap of the modulated carriers in the frequency domain - different from FDM. - figure difference between OFDM and FDM would be useful here (C) Leila Z. Ribeiro, 2001

OFDM OFDM is a multicarrier block transmission system. GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 OFDM OFDM is a multicarrier block transmission system. Block of ‘N’ symbols are grouped and sent parallely. No interference among the data symbols sent in a block. (C) Leila Z. Ribeiro, 2001

OFDM Mathematics t º [ 0,Tos] Orthogonality Condition In our case For p ¹ q Where fk=k/T

Transmitted Spectrum GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 (C) Leila Z. Ribeiro, 2001

Spectrum of the modulated data symbols Rectangular Window of duration T0 Has a sinc-spectrum with zeros at 1/ T0 Other carriers are put in these zeros  sub-carriers are orthogonal T0 Magnitude Frequency N sub-carriers: resembles IDFT!

OFDM terminology Orthogonal carriers referred to as subcarriers {fi,i=0,....N-1}. OFDM symbol period {Tos=N x Ts}. Subcarrier spacing Df = 1/Tos.

OFDM and FFT Samples of the multicarrier signal can be obtained using GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 OFDM and FFT Samples of the multicarrier signal can be obtained using the IFFT of the data symbols - a key issue. FFT can be used at the receiver to obtain the data symbols. No need for ‘N’ oscillators,filters etc. Popularity of OFDM is due to the use of IFFT/FFT which have efficient implementations. (C) Leila Z. Ribeiro, 2001

OFDM Signal t º [ 0,Tos] Otherwise K=0,..........N-1

By sampling the low pass equivalent signal at a rate N times higher than the OFDM symbol rate 1/Tos, OFDM frame can be expressed as: m = 0....N-1

Interpretation of IFFT&FFT IFFT at the transmitter & FFT at the receiver Data symbols modulate the spectrum and the time domain symbols are obtained using the IFFT. Time domain symbols are then sent on the channel. FFT at the receiver to obtain the data.

Interference between OFDM Symbols GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 Interference between OFDM Symbols Transmitted Signal OS1 OS2 OS3 Due to delay spread ISI occurs Delay Spread IOSI Solution could be guard interval between OFDM symbols (C) Leila Z. Ribeiro, 2001

Cyclic Prefix Zeros used in the guard time can alleviate interference between OFDM symbols (IOSI problem). Orthogonality of carriers is lost when multipath channels are involved. Cyclic prefix can restore the orthogonality.

Cyclic Prefix Convert a linear convolution channel into a circular This restores the orthogonality at the receiver. Energy is wasted in the cyclic prefix samples.

Cyclic Prefix Illustration GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 Cyclic Prefix Illustration Tg Tos OS 1 OS 2 Cyclic Prefix OS1,OS2 - OFDM Symbols Tg - Guard Time Interval Ts - Data Symbol Period Tos - OFDM Symbol Period - N * Ts (C) Leila Z. Ribeiro, 2001

Guard interval (2) - Cyclic extension

Design of an OFDM System Nr. of carriers Data rate; modulation order Channel impulse response Guard interval length x(4 … 10) FFT symbol length Other constraints: Nr. of carriers should match FFT size and data packet length considering coding and modulation schemes Channel Parameters are needed Introduction

Spectral Shaping by Windowing OFDM System Design

OFDM Symbol Configuration Not all FFT-points can be used for data carriers Lowpass filters for AD- and DA-conversion oversampling required Design of an OFDM System

Advantages of OFDM Solves the multipath-propagation problem Simple equalization at receiver Computationally efficient For broadband systems more efficient than SC Supports several multiple access schemes TDMA, FDMA, MC-CDMA, etc. Supports various modulation schemes Adaptability to SNR of sub-carriers is possible Elegant framework for MIMO-systems All interference among symbols is removed

Problems of OFDM (Research Topics) GMU - TCOM 507 - Spring 2001 Problems of OFDM (Research Topics) Class: Feb-22-2001 20 40 60 80 100 120 140 160 180 200 -0.2 -0.1 0.1 0.2 time domain signal (baseband) sample nr. imaginary real Synchronization issues: Time synchronization Find start of symbols Frequency synchr. Find sub-carrier positions Non-constant power envelope Linear amplifiers needed Channel estimation: To retrieve data Channel is time-variant OFDM Technology (C) Leila Z. Ribeiro, 2001

OFDM Transmitter Input Symbols X0 x0 Parallel to Serial and add CP GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 OFDM Transmitter X0 x0 Parallel to Serial and add CP Serial to Parallel Input Symbols Add CP IFFT XN-1 xN-1 RF Section DAC Windowing (C) Leila Z. Ribeiro, 2001

OFDM Receiver x0 X0 ADC and Remove CP Parallel to Serial and Decoder GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001 OFDM Receiver x0 X0 ADC and Remove CP Parallel to Serial and Decoder Serial to Parallel Output Symbols FFT xN-1 XN-1 (C) Leila Z. Ribeiro, 2001

Synchronization Timing and frequency offset can influence performance. Frequency offset can influence orthogonality of subcarriers. Loss of orthogonality leads to Inter Carrier Interference.

Peak to Average Ratio Multicarrier signals have high PAR as compared to single carrier systems. PAR increases with the number of subcarriers. Affects power amplifier design and usage.

Peak to Average Power Ratio