Fundamentals of Wireless Communications

Xinzhou Wu Qualcomm Flarion Technologies 1

Part I. Point-to-point communication: detection, diversity and channel uncertainty

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Main story

• Communication over a flat fading channel has poor performance due to significant probability that channel is in a deep fade .

• Reliability is increased by providing more resolvable signal paths that fade independently.

• Diversity can be provided across time , frequency space .

and • Name of the game is how to exploit the added diversity in an efficient manner.

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Baseline: AWGN Channel

BPSK modulation Error probability decays exponentially with SNR.

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Gaussian Detection

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Rayleigh Flat Fading Channel

BPSK: Conditional on h, Coherent detection.

Averaged over h, at high SNR.

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Rayleigh vs AWGN

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Typical Error Event

Conditional on h, When error probability is very small.

When error probability is large: Typical error event is due to channel being in deep fade rather than noise being large.

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Time Diversity

• Time diversity can be obtained by interleaving symbols across different coherent time periods.

and coding over Coding alone is not sufficient!

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Example:GSM

• Amount of time 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 f c = 900Mhz.

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Simplest Code: Repetition

After interleaving over L coherence time periods, Repetition coding: for all where and This is classic vector detection in white Gaussian noise.

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Geometry

For BPSK Is a sufficient statistic (match filtering).

Reduces to scalar detection problem: 12

Deep Fades Become Rarer

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Performance

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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?

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Example: Rotation code (L=2)

Send two symbols over two degrees of freedom: •Can we still achieve full diversity gain?

where d 1 and d 2 two directions. are the distances between the codewords in the 16

Product Distance

product distance Choose the rotation angle to maximize the worst-case product distance to all the other codewords: 17

Antenna Diversity

Receive Transmit Both 18

Receive Diversity

Same as repetition coding in time diversity, except that there is a further power gain.

Optimal reception is via match filtering ( receive beamforming ).

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Transmit Diversity

If transmitter knows the channel, send: maximizes the received SNR by in-phase addition of signals at the receiver ( transmit beamforming ).

Reduce to scalar channel: same as receive beamforming.

What happens if transmitter does not know the channel?

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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.

• Space-time codes are designed specifically for the transmit diversity scenario.

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Alamouti Scheme

Over two symbol times: Projecting onto the two columns of the H matrix yields: Double the symbol rate of repetition coding.

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Space-time Code Design

A space-time code is a set of matrices Full diversity is achieved if all pairwise differences have full rank.

Coding gain determined by the determinants of Time-diversity codes have diagonal matrices and the determinant reduces to squared product distances.

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Frequency Diversity

• Resolution of multipaths provides diversity.

• Full diversity is achieved by sending one symbol every L symbol times.

• But this is inefficient (like repetition coding).

• Sending symbols more frequently may result in intersymbol interference.

• Challenge is how to mitigate the ISI while extracting the inherent diversity in the frequency-selective channel.

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Approaches

• Time-domain equalization (eg. GSM) • Direct-sequence spread spectrum (eg. IS-95 CDMA) • Orthogonal frequency-division multiplexing OFDM (eg. 802.11a, Flash-OFDM) 25

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?

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Reduction to Transmit Diversity

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MLSD Achieves Full Diversity

Space-time code matrix for input sequence Difference matrix for two sequences first differing at is full rank.

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Direct Sequence Spread Spectrum

• Information symbol rate is much lower than chip rate (large processing gain).

• ISI is not significant compared to interference from other users and match filtering (Rake) is near-optimal.

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Frequency Diversity via Rake

• Considered a simplified situation (uncoded).

• Each information bit is spread into two pseudorandom sequences x A and x B (x B = -x A ).

• Each tap of the match filter is a finger of the Rake.

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OFDM: Basic Concept

• Most wireless channels are underspread (delay spread << coherence time) .

• Can be approximated by a linear time invariant over a long time scale.

channel • Complex sinusoids are the only eigenfunctions of linear time-invariant channels.

• Should signal in the frequency domain transform to the time domain.

and then 31

OFDM

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OFDM

OFDM transforms the communication problem into the frequency domain : a bunch of non-interfering sub-channels, one for each sub-carrier.

Can apply time-diversity techniques. 33

Cyclic Prefix Overhead

• OFDM overhead = length of cyclic prefix / OFDM symbol time • Cyclic prefix dictated by delay spread .

• OFDM symbol time limited by channel coherence time .

• Equivalently, the inter-carrier spacing should be much larger than the Doppler spread.

• Since most channels are underspread , the overhead can be made small. 34

Example: Flash OFDM (Flarion)

• Bandwidth = 1.25 MHz • OFDM symbol = 128 samples = 100 m s • Cyclic prefix = 16 samples = 11 m s delay spread • 11 % overhead.

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Summary

• Fading makes wireless channels unreliable.

• Diversity increases reliability and makes the channel more consistent.

• Smart codes yields a coding gain in addition to the diversity gain.

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Part II. Cellular Systems: Multiple Access and Interference Management

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Cellular Systems

• So far we have focused on point-to-point communication. • In a cellular system, additional issues come into forefront: – Multiple access – Inter-cell interference management 38

History of Cellular Systems

• Cellular concept in 1950s & 1960s at AT&T Bell Lab.

– Cell splitting and frequency reuse

BASE STATION

Mobile Telephone Switching Office 39

Evolution of Cellular Standards

3G Multimedia Pre-4G 2.75G

Intermediate Multimedia 2G Digital Voice 2.5G

Packet Data 1G Analog Voice WiMAX GPRS GSM W-CDMA (UMTS) EDGE

115 Kbps

NMT

9.6 Kbps

384 Kbps

3GPP-LTE GSM/ GPRS TD-SCDMA TDMA TACS

(Overlay) 115 Kbps 2 Mbps?

9.6 Kbps

iDEN

9.6 Kbps

iDEN

(Overlay)

Flash OFDM UMB PDC

9.6 Kbps

AMPS CDMA CDMA 1xRTT cdma2000

1X-EV-DV

14.4 Kbps / 64 Kbps

PHS (IP-Based)

144 Kbps Over 2.4 Mbps

PHS

64 Kbps

2006+ 2003 - 2004+ 2003+

2001+

Source: U.S. Bancorp Piper Jaffray

1992 - 2000+ 1984 - 1996+

• 3GPP evolution path and 3GPP2 evolution path 40

Three Systems

• Narrowband (GSM) • Wideband system: CDMA (IS-95) • Wideband system: OFDM (Flash OFDM) 41

Narrowband (GSM)

• The total bandwidth is divided into many narrowband channels. (200 kHz in GSM) • Users are given time slots in a narrowband channel (8 users) • Multiple access is orthogonal: users within the cell never interfere with each other.

• Interference between users on the same channel in different cells is minimized by reusing the same channel only in cells far apart.

• Users operate at high SINR regime • The price to pay is in reducing the overall available degrees of freedom. 42

Frequency Reuse

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• • •

Wideband System: CDMA

Universal frequency reuse: all the users in all cells share the same bandwidth (1.25 MHz in IS-95 and 1x) Main advantages: – Maximizes the degrees of freedom usage – Allows interference averaging across many users.

– Soft capacity limit – Allows soft handoff – Simplify frequency planning Challenges – Very tight power control to solve the near-far problem.

– More sophisticated coding/signal processing to extract the information of each user in a very low SINR environment.

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Design Goals

• Make the interference look as much like a white Gaussian noise as possible: – Spread each user’s signal using a pseudonoise noise sequence – Tight power control for managing interference within the cell – Averaging interference from outside the cell as well as fluctuating voice activities of users.

• Apply point-to-point design for each link – Extract all possible diversity in the channel 45

Point-to-Point Link Design

• Extracting maximal diversity is the name of the game. • Time diversity is obtained by interleaving across different coherence time and convolutional coding.

• Frequency diversity is obtained by Rake combining of the multipaths. • Transmit diversity in 3G CDMA systems 46

IS-95 Uplink

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Power Control

• Maintain equal received power for all users in the cell • Tough problem since the dynamic range is very wide. Users’ attenuation can differ by many 10’s of dB • Consists of both open-loop and closed loop • Open loop sets a reference point • Closed loop is needed since IS-95 is FDD (frequency division duplex) • Consists of 1-bit up-down feedback at 800 Hz.

• Latency in access due to slow powering up of mobiles 48

Power Control

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Interference Averaging

The received signal-to-interference-plus-noise ratio for a user: In a large system, each interferer contributes a small fraction of the total out-of-cell interference.

This can be viewed as providing

interference diversity

.

Same interference-averaging principle applies to voice activity and imperfect power control.

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Soft Handoff

• Provides another form of diversity: macrodiversity 51

Uplink vs Downlink

• Can make downlink signals for different users orthogonal at the transmitter. Still because of multipaths, they are not completely orthogonal at the receiver.

• Rake is highly sub-optimal in the downlink. Equalization is beneficial as all users’ data go thru the same channel and the aggregate rate is high.

• Less interference averaging: interference come from a few high-power base stations as opposed to many low power mobiles.

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Issues with CDMA

• In-cell interference requires power control.

• Power control is expensive, particularly for data applications where users have low duty cycle but require quick access to resource.

• In-cell interference is not an inhererent property of systems with universal frequency reuse.

• We can keep users in the cell orthogonal. 53

Wideband System: OFDM

• We have seen OFDM as a point-to-point modulation scheme, converting the frequency-selective channel into a parallel channel.

• It can also be used as a multiple access technique.

• By assigning different time/frequency slots to users, they can be kept orthogonal, no matter what the multipath channels are.

• Equalization is not needed.

• The key property of sinusoids is that they are eigenfunctions of all linear time-invariant channels. 54

In-cell Orthogonality

• The basic unit of resource is a virtual channel: a hopping sequence.

• Each hopping sequence spans all the sub-carriers to get full frequency-diversity.

• Coding is performed across the symbols in a hopping sequence. • Hopping sequences of different virtual channels in a cell are orthogonal.

• Each user is assigned a number of virtual channels depending on their data rate requirement.

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Example

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Out-of-Cell Interference Averaging

• The hopping patterns of virtual channels in adjacent cells are designed such that any pair has minimal overlap.

• This ensures that a virtual channel sees interference from many users instead of a single strong user.

• This is a form of interference diversity.

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Example: Flash OFDM

• Bandwidth = 1.25 Mz • # of data sub-carriers = 113 • OFDM symbol = 128 samples = 100 m • Cyclic prefix = 16 samples = 11 m s s delay spread OFDM symbol time determines accuracy requirement of user synchronization (not chip time).

Ratio of cyclic prefix to OFDM symbol time determines overhead (fixed, unlike power control) 58

Another look on universal reuse

• Universal reuse increases the degrees of freedom in the system • Gain is more prominent when mobiles are close to the basestations • All mobiles are degree of freedom limited

A caveat

• If a significant portion of mobiles lives on cell boundary, universal reuse performs badly.

A step further from universal reuse

• When both types of mobiles are present, interests conflict!

– Typical cellular deployment has >30% users on the cell boundary • Flexband: (Fractional frequency reuse) – Compromise between the demand for degrees of freedom from close-to-basestation users and the demand for power from cell boundary users.

How Flexband helps?

• Schedule the cell boundary users in the strong carriers and schedule the close-to-basestation users in the weak carriers – The cell boundary users get huge improvement when scheduled in their performance due to the reduction in interference and requires less degrees of freedom to achieve a certain channel performance – The close-to-basestation users can be scheduled in more degrees of freedom as a consequence – Both types of users can be improved – Trade power and degree of freedom between two types of users

Deployment of fractional frequency reuse

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Summary

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