OFDM (DMT) Bit and Power Loading for Unequal Error Protection

OFDM (DMT) Bit and Power Loading for Unequal Error Protection Werner Henkel and Khaled Hassan School of Engineering and Science International Universities Bremen (IUB)

11th International OFDM-Workshop, 2006

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Werner Henkel & Khaled Hassan

OFDM (DMT) Bit and Power Loading for Unequal Error Protection

Outline

Outline

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Motivations Why Unequal Error Protection (UEP)? Why UEP Physical Transport?

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UEP: Bit-Loading Previous Work Proposed UEP Bit-Rate Maximization

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Channel Model Noise Environment

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Simulation Results UEP Performance: SER Analysis Bit and Power Loading

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Conclusions Werner Henkel & Khaled Hassan


Motivations

Outline

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Motivations

Why Unequal Error Protection (UEP)?

Realizing UEP

Source encoders of some applications deliver data of different importance. The different error sensitivities of different communication devices, e.g., PDAs, laptops, · · · . Matching the channel variations to enhance performance and throughput.

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Motivations


Realizing UEP


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Motivations


Realizing UEP


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Motivations

Why UEP Physical Transport?

Advantages of UEP Physical Transport

UEP Bit/Power Loading Original− ordering

Importance levels

SNR−sorting UEP Channel Encoder

P1 P2

multimedia input stream Source Encoder

S/P

IFFT

P/S & CP

PN

time domain channel state information

original order bit−loading map

Why UEP physical transport? Reduce effort and complexity Arbitrary performance steps

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Motivations



UEP Bit/Power Loading Original− ordering

Importance levels

SNR−sorting

UEP Channel Encoder

P1 P2


S/P

IFFT

P/S & CP

PN




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Motivations



UEP Bit/Power Loading Original−

Importance levels

SNR−sorting

UEP Channel Encoder

ordering P1 P2


S/P

IFFT

P/S & CP

PN




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Motivations



UEP Bit/Power Loading Original−

Importance levels

SNR−sorting

UEP Channel Encoder

ordering P1 P2


S/P

IFFT

P/S & CP

PN




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UEP: Bit-Loading

Outline

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UEP: Bit-Loading

Previous Work

Bit-Loading Algorithms

Bit-Loading solutions: Optimum: add bits to the locations of minimum incremental power, e.g.: Hughes-Hartogs and Campello Sub-optimum: based on Shannon capacity (Chow et. al.) or Lagrange-optimization (Fischer-Huber and Yu-Willson)

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UEP: Bit-Loading

Previous Work

Bit-Loading Algorithms Bit-Loading solutions: Optimum: add bits to the locations of minimum incremental power, e.g.: Hughes-Hartogs and Campello Sub-optimum: based on Shannon capacity (Chow et. al.) or Lagrange-optimization (Fischer-Huber and Yu-Willson)

Bit-Loading by Chow et. al.:

SNRk bk = log2 1 + γ

Bit-Rate Maximization Problem: ( ) N−1

max Btot = b∈Z

∑ bk k=0

N−1

subject to

∑ Pk (bk ) < PT , k=0

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UEP: Bit-Loading

Previous Work

Bit-Loading Algorithms

Bit-Loading solutions: Optimum: add bits to the locations of minimum incremental power, e.g.: Hughes-Hartogs and Campello Sub-optimum: based on Shannon capacity (Chow et. al.) or Lagrange-optimization (Fischer-Huber and Yu-Willson)

Bit-Loading by Chow et. al.:

SNRk bk = log2 1 + γ

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Quantization Error:

bˆ k = bbk + 0.5cb0max ∆bk = bk − bˆ k


UEP: Bit-Loading

Proposed UEP Bit-Rate Maximization

Modifications to Bit-Loading by Chow et. al. Modified bit-loading:

Problem definitions Ng levels of protections with noise margins γj Noise margin step size ∆γj Target-rates Tj for each class Over all target bit-rate BT

bk,j = log2 1 +

SNRk,j

γj ˆbk,j = bbk,j + 0.5cbmax 0 ∆bk,j = bk,j − bˆ k,j

SNR-sorting SNRs have to be allocated to Ng levels. Allocate important data to weaker subcarriers to protect them against non-stationary noise. 8



UEP: Bit-Loading




bk,j = log2 1 +

SNRk,j





UEP: Bit-Loading




bk,j = log2 1 +

SNRk,j





UEP: Bit-Loading




bk,j = log2 1 +

SNRk,j





UEP: Bit-Loading




bk,j = log2 1 +

SNRk,j





UEP: Bit-Loading




bk,j = log2 1 +

SNRk,j





UEP: Bit-Loading


UEP Bit-Loading and SNR-Sorting Algorithms τ1 SNR

Input: SNRk,j in kth subcarrier of jth class, N, Ng , BT , Tj , and ∆γ Output: γj , average probability of error Pej , and bit-loading

τ0

Compute bkj using γj (γj = γ0 − j · ∆γ). Adjust Mj iteratively,

τ1 Btot −BT N

SNR

If Btot 6= BT , γ0,new = γ0,old · 2

τ0

If Btot 6= BT again, add or subtract bits according to ∆bk,j The power is allocated according to Pej

M0


M2

Class2(γ2)

Class1(γ1)

Class0(γ0)

inver. SNR-sorting Class0(γ0)

Class1(γ1)

Class2(γ2)

SNR-sorting

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M1


UEP: Bit-Loading




τ0


τ1 Btot −BT N

SNR


τ0


M0


M2

Class2(γ2)

Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)

SNR-sorting

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M1


UEP: Bit-Loading




τ0


τ1 Btot −BT N

SNR


τ0


M0


M2

Class2(γ2)

Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)

SNR-sorting

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M1


UEP: Bit-Loading




τ0

Compute bkj using γj (γj = γ0 − j · ∆γ). Adjust Mj iteratively, if ∑k,j bk,j < Tj If Btot 6= BT , γ0,new = γ0,old · 2

Btot −BT N


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SNR

τ1

τ0

M0

M1

M2

with SNR-sorting Class2(γ2)

Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)


UEP: Bit-Loading




τ0

Compute bkj using γj (γj = γ0 − j · ∆γ). Adjust Mj iteratively, if ∑k,j bk,j > Tj If Btot 6= BT , γ0,new = γ0,old · 2

Btot −BT N


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SNR

τ1

τ0

M0

M1

M2


Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)


UEP: Bit-Loading




τ0

Compute bkj using γj (γj = γ0 − j · ∆γ).


Btot −BT N


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τ1 SNR

Adjust Mj iteratively, repeat unit ∑k,j bk,j = Tj or maximum iteration

τ0

M0

M1

M2


Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)


UEP: Bit-Loading




τ0



Btot −BT N


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τ1 SNR


τ0

M0

M1

M2


Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)


UEP: Bit-Loading




τ0



Btot −BT N


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τ1 SNR


τ0

M0

M1

M2


Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)


UEP: Bit-Loading




τ0



Btot −BT N


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τ1 SNR


τ0

M0

M1

M2


Class1(γ1)

Class0(γ0)


Class1(γ1)

Class2(γ2)


Channel Model

Outline

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Channel Model

Noise Environment

ADSL2plus with 512 subcarriers is considered for this channel. A wireline cable of diameter 0.4 mm and 2 km length is assumed. A combination of T1 + HDSL NEXT and −130 dBm/Hz AWGN is used for the bit-loading. Additionally, real measured impulse noise is introduced after bit allocation.

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Channel Model

Noise Environment


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Channel Model

Noise Environment


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Channel Model

Noise Environment


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Simulation Results

Outline

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Simulation Results

UEP Performance: SER Analysis

SER for Stationary and Non-stationary Noise SER for stationary noise

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SER for non-stationary noise


Simulation Results

Bit and Power Loading

UEP bit-loading and power-allocation: SNR-Sorting Scheme

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Inverse SNR-Sorting Scheme


Conclusions

Outline

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Conclusions

Conclusions We described an UEP bit-allocation scheme as an extension of the algorithm by Chow et al.. Allows arbitrary margin definitions and bit-rates according to the priorities. SNR-sorting will ensure that the high-priority class will still be well protected even under non-stationary noise.

Modified bit-loading:

bk,j = log2 1 +

SNRk,j

γj

bˆ k,j = bbk,j + 0.5cb0max ∆bk,j = bk,j − bˆ k,j

Open points: Possible mixed allocation and hierarchical modulation.

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Conclusions

Conclusions We described an UEP bit-allocation scheme as an extension of the algorithm by Chow et al.. Allows arbitrary margin definitions and bit-rates according to the priorities. SNR-sorting will ensure that the high-priority class will still be well protected even under non-stationary noise. Open points: Possible mixed allocation and hierarchical modulation.

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Conclusions


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Conclusions


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Conclusions

Conclusions We described an UEP bit-allocation scheme as an extension of the algorithm by Chow et al.. Allows arbitrary margin definitions and bit-rates according to the priorities.

Thank you!

SNR-sorting will ensure that the high-priority class will still be well protected even under non-stationary noise. Open points: Possible mixed allocation and hierarchical modulation.

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