Post on 25-Feb-2016
description
Coded Modulation in Coded Modulation in Fading ChannelsFading Channels
Ryan AuresRyan AuresMatthew HollandMatthew Holland
ECE 492 Mobile CommunicationsECE 492 Mobile Communications
MotivationMotivation Benefits/Drawbacks of codingBenefits/Drawbacks of coding
• +Increased capacity+Increased capacity• +Lower BER+Lower BER• -Higher power-Higher power• -Lower throughput-Lower throughput
Benefits/Drawbacks of adaptive Benefits/Drawbacks of adaptive modulationmodulation• +Increased capacity+Increased capacity• +Energy efficient+Energy efficient• -Complexity of demodulation-Complexity of demodulation• -Need accurate channel estimation-Need accurate channel estimation
Coded 16-QAMCoded 16-QAM Increased capacity over current cellular Increased capacity over current cellular
standard 40 – 85%standard 40 – 85% Same QoS as currently used QPSK systemsSame QoS as currently used QPSK systems Use CSI at receiver to decode messageUse CSI at receiver to decode message
• Weighting functionWeighting function
Trellis Coding (coset codes) with Trellis Coding (coset codes) with adaptive modulationadaptive modulation
Superimpose coding techniques for AWGN Superimpose coding techniques for AWGN channels onto fading channels with adaptive channels onto fading channels with adaptive modulationmodulation
Variable rate variable power MQAMVariable rate variable power MQAM Higher order trellis codes approach capacity limitHigher order trellis codes approach capacity limit Achieve same coding gains as seen for AWGN Achieve same coding gains as seen for AWGN
channelschannels Up to 20dB power savingsUp to 20dB power savings
Coding with 16-QAMCoding with 16-QAM
Brief description of the systemBrief description of the system Motivation: Current use of Motivation: Current use of ππ/4-QPSK in /4-QPSK in
new cellular systems lack capacitynew cellular systems lack capacity Solution: Coded 16-QAMSolution: Coded 16-QAM Fast flat fading channelFast flat fading channel Viterbi coding with weighting and channel Viterbi coding with weighting and channel
information aided by pilot tonesinformation aided by pilot tones
Block diagram of the systemBlock diagram of the system
Describe channel estimation with Describe channel estimation with pilot tonespilot tones
Every frame a pilot tone is sent over the Every frame a pilot tone is sent over the channelchannel
This pilot tone is an arbitrary symbol sent This pilot tone is an arbitrary symbol sent that is known at the transmitter and that is known at the transmitter and receiver receiver
For a frame of N symbols the pilot to data For a frame of N symbols the pilot to data ratio is 1:(N-1)ratio is 1:(N-1)• For large N the estimation of the channel will For large N the estimation of the channel will
not be as accuratenot be as accurate• For small N there is a decrease in throughput For small N there is a decrease in throughput
The Viterbi algorithmThe Viterbi algorithm A trellis encoder is used on the bit A trellis encoder is used on the bit
streamstream The encoded data then undergoes The encoded data then undergoes
block interleavingblock interleaving• Block interleaving is to avoid burst Block interleaving is to avoid burst
errorserrors• It destroys the memory of the channelIt destroys the memory of the channel
Describe the weighting functionDescribe the weighting function The signal is reconstructed using the The signal is reconstructed using the
Viterbi algorithm to find the most likely Viterbi algorithm to find the most likely path the message could take.path the message could take.
By applying a weighting function the By applying a weighting function the estimates of the message can be estimates of the message can be improved by removing the weight of improved by removing the weight of symbols that occurred during deep fadessymbols that occurred during deep fades
Block diagram of the systemBlock diagram of the system
BER PerformanceBER Performance
Capacity PerformanceCapacity Performance There is a significant capacity increase in the There is a significant capacity increase in the
coded systemcoded system
General Results – 16-QAMGeneral Results – 16-QAM 16-QAM in flat fading channel16-QAM in flat fading channel
• Gain over un-coded system 7-10 dBGain over un-coded system 7-10 dB• Capacity over QPSK systems 40-85% Capacity over QPSK systems 40-85%
gaingain
Adaptive Coded Modulation Adaptive Coded Modulation
OverviewOverview Motivation: Improve energy efficiency and Motivation: Improve energy efficiency and
increase data rate over a fading channelincrease data rate over a fading channel Coding and modulation designed Coding and modulation designed
separatelyseparately• Trellis, lattice codes normally used for AWGN Trellis, lattice codes normally used for AWGN
channels can be usedchannels can be used• Variable Modulation (MQAM, others)Variable Modulation (MQAM, others)• Same result (gain) as AWGN channelSame result (gain) as AWGN channel
Results approach Shannon Capacity LimitResults approach Shannon Capacity Limit Power Savings up to 20dBPower Savings up to 20dB
System ModelSystem Model
√√g(t) = ergodic channel gain, g(t) = ergodic channel gain, mean(mean(g) = 1g) = 1 Assume perfect channel estimate (ŷ(t) = y(t))Assume perfect channel estimate (ŷ(t) = y(t)) Assume zero delay in feedback path(TAssume zero delay in feedback path(Tff = 0) = 0)
Basic PremiseBasic Premise Coding gain is a function of dCoding gain is a function of dminmin, the minimum , the minimum
distance between signal point sequences.distance between signal point sequences. ddminmin= min{d= min{dss, d, dcc}}
• ddss = minimum distance between coset sequences = minimum distance between coset sequences• ddcc = minimum distance between coset points = minimum distance between coset points
Goal of adaptive modulation is to maintain constant Goal of adaptive modulation is to maintain constant ddminmin across different SNR values across different SNR values
For each SNR level For each SNR level γγ, find values of: , find values of: • M(M(γγ) - constellation size) - constellation size• S(S(γγ) – transmit power) – transmit power• T(T(γγ) – duration of transmission) – duration of transmission
Block DiagramBlock Diagram
Channel coding and modulation separableChannel coding and modulation separable Channel coding same as non-adaptive coded modulationChannel coding same as non-adaptive coded modulation
Trellis coded Adaptive MQAMTrellis coded Adaptive MQAM Specific implementation of general Specific implementation of general
scenario with coding + adaptive scenario with coding + adaptive modulationmodulation
Trellis codesTrellis codes• Four state and Eight state codesFour state and Eight state codes
M-ary QAMM-ary QAM• Only square constellationsOnly square constellations
Coding and Modulation are separableCoding and Modulation are separable
Choose Parameters for MQAMChoose Parameters for MQAM
Symbol period T(Symbol period T(γγ) remains constant, difficult ) remains constant, difficult to change in practiceto change in practice
Choose M(Choose M(γγ) based on SNR, then choose ) based on SNR, then choose power level S within each M power level S within each M
Parameters chosen to maintain desired Parameters chosen to maintain desired minimum distanceminimum distance• Based on required SNRBased on required SNR
Gives power as a continuous function of SNRGives power as a continuous function of SNR
Results for Raleigh fading – MQAMResults for Raleigh fading – MQAM Perfect CSI at Tx and Rx is knownPerfect CSI at Tx and Rx is known
Raleigh fading and lognormal shadowing Raleigh fading and lognormal shadowing simulated, results only for Raleigh fading but simulated, results only for Raleigh fading but similar results found for lognormal shadowingsimilar results found for lognormal shadowing
MQAM restricted to constellation sizes of MQAM restricted to constellation sizes of 0,4,16,64, and 2560,4,16,64, and 256
Results obtained both from simulation and Results obtained both from simulation and analyticallyanalytically
Coding Gain Coding Gain Moderate gain at BER requirement = 10Moderate gain at BER requirement = 10 -3-3, must increase , must increase
BER requirement to 10BER requirement to 10-6-6 to see 3dB improvement to see 3dB improvement Caused by codewords being off by more than one Caused by codewords being off by more than one
neighbor at lower values of SNRneighbor at lower values of SNR
Constellation sizeConstellation size At higher BER, good spectral efficiencyAt higher BER, good spectral efficiency Lowering BER requirement -> higher Lowering BER requirement -> higher
coding gaincoding gain
Higher state trellis codesHigher state trellis codes For higher number of states: better coding gain, better For higher number of states: better coding gain, better
spectral efficiency, closer to capacityspectral efficiency, closer to capacity Exponential increase in complexity of decoding, limited to Exponential increase in complexity of decoding, limited to
eight or fewer states in practiceeight or fewer states in practice
Results – Coded MQAMResults – Coded MQAM Coding gain of 3dB for four state code, Coding gain of 3dB for four state code,
3.6dB gain for eight state code3.6dB gain for eight state code• This gain in addition to gain from adaptive This gain in addition to gain from adaptive
MQAMMQAM Adaptive modulation gives power savings Adaptive modulation gives power savings
of 5dB min, 20dB max for low state codes of 5dB min, 20dB max for low state codes with low required BER’swith low required BER’s
Possible improvements: constellation Possible improvements: constellation shaping and turbo codes, get even close to shaping and turbo codes, get even close to capacity limitcapacity limit
ReferencesReferences
[1] “Adaptive coded modulation for [1] “Adaptive coded modulation for fading channels”, A. Goldsmith and fading channels”, A. Goldsmith and S. ChuaS. Chua
[2] “A coded 16 QAM scheme for fast [2] “A coded 16 QAM scheme for fast fading mobile radio channels”,fading mobile radio channels”,D. Subasinghe-Dias and K. FeherD. Subasinghe-Dias and K. Feher