Abstract

Common to all DMT/OFDM systems is a large peak-to-average ratio (PAR), which can lead to low power efficiency and nonlinear distortion. Tone reservation uses unused or reserved tones to design a peak-canceling signal to lower the PAR of a transmit block. In DMT ADSL systems, the power allocated to these tones may be limited due to crosstalk issues with many users in one twisted pair bundle. This PSD limitation not only limits PAR reduction ability, but also makes the optimization problem more challenging to solve. Extending the recently proposed active set tone reservation method, we develop an efficient algorithm with performance close to the optimal solution.

Highlights

  • Communication systems using multicarrier modulation have recently become widely used both in wireless (DVB-T, DAB, IEEE 802.11a) and wireline (ADSL, VDSL) environments [1, 2, 3]

  • Multicarrier systems have distinct advantages over single-carrier systems, but suffer from a serious drawback: the approximately Gaussian-distributed output samples cause a high peak-to-average ratio (PAR) that results in low power efficiency and possible nonlinear distortion

  • A technique known as tone reservation was initially developed in [4, 5] and is well suited for discrete multitone modulation (DMT) ADSL systems over twisted pair copper wiring

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Summary

INTRODUCTION

Communication systems using multicarrier modulation have recently become widely used both in wireless (DVB-T, DAB, IEEE 802.11a) and wireline (ADSL, VDSL) environments [1, 2, 3]. In ADSL and other practical systems, the peak-reduction signal may be power limited on each of the reserved tones due to crosstalk constraints with many users being serviced in one twisted pair bundle. This is, for instance, manifested in the recent ADSL2 standard [19] as a −10 dB PSD limit on the reserved tones compared to the data-carrying tones.

DMT AND TONE RESERVATION
Tone selection
Active set tone reservation
PSD-constrained tone reservation
Modifications for PSD constraints
Cost-versus-performance issues
Low complexity algorithm
Bound on minimum PAR
Amax bound
SIMULATIONS
Restrictive PSD constraint
Loosening the PSD constraint
Increasing the number of tones
Randomly chosen tones
Findings
CONCLUSIONS

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