Impact of Channel Prediction on Adaptive Coded Modulation Performance in Rayleigh Fading

Oien, G.E.; Holm, Henrik; Hole, Kjell

doi:10.1109/tvt.2004.827156

Cited by 129 publications

(99 citation statements)

References 12 publications

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“…The improvement can even be higher when diversity and combining techniques are included [2], [3]. The scheme presented in this paper is a generalization of two recent papers; one by Cai and Giannakis [4], in which an uncoded adaptive modulation system based on M -QAM constellations with single transmit and single receive antenna is investigated, and one by Øien et al [3] where an ACM system with maximum ratio combining (MRC) reception was investigated assuming perfect receiver channel state information (CSI). We extend and unify the idea of these papers by analyzing the case when, as in [3], coding is included and when MRC is implemented on the receiver side.…”

Section: Introductionmentioning

confidence: 99%

“…The scheme presented in this paper is a generalization of two recent papers; one by Cai and Giannakis [4], in which an uncoded adaptive modulation system based on M -QAM constellations with single transmit and single receive antenna is investigated, and one by Øien et al [3] where an ACM system with maximum ratio combining (MRC) reception was investigated assuming perfect receiver channel state information (CSI). We extend and unify the idea of these papers by analyzing the case when, as in [3], coding is included and when MRC is implemented on the receiver side. The pilot spacing and the power allocation to pilot and data symbols are optimized as in [4], for maximal spectral efficiency under an instantaneous bit error rate (BER) constraint.…”

Section: Introductionmentioning

confidence: 99%

“…Based on this, the transmitter dynamically adapts the rate and the power to a mode which is suitable for the channel to improve the average spectral efficiency (ASE) while maintaining the instantaneous BER below some pre-defined target BER0. As in [3], [5], multi-dimensional trellis codes designed for additive white Gaussian noise (AWGN) channels are used as component codes.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Coded Modulation With Receive Antenna Diversity and Imperfect Channel Knowledge at Receiver and Transmitter

Duong

Oien

Hole

2006

IEEE Trans. Veh. Technol.

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We analyze and optimize the performance of a trellis-coded modulation system where receive antenna diversity is implemented. The adaptive coded modulation scheme alone is a promising tool to combat fading and it improves the spectral efficiency in mobile communications. The improvement can be even higher when we have multiple receiver antennas. The analysis is done in the presence of both estimation and prediction errors. Independent Rayleigh fading on each subchannel is considered, and maximum ratio combining is employed on the receiver side. As expected, the average spectral efficiency increases, while bit error rate is always fulfilled.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Coded Modulation With Receive Antenna Diversity and Imperfect Channel Knowledge at Receiver and Transmitter

Duong

Oien

Hole

2006

IEEE Trans. Veh. Technol.

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“…Hence, we can write the joint density f (K, K) by modifying the bivariate gamma density function in [7] as:…”

Section: Conditional Probability Methodsmentioning

confidence: 99%

A Markov Model for MIMO Channel Condition Number with Application to Dual-Mode Antenna Selection

Kuo

Smith

Garth

2007

2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring

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Abstract-The condition number is a well known indicator of the spatial selectivity of a MIMO wireless channel. The objective of this paper is to examine the temporal behavior of this metric using a Markov model construction. Specifically, we have developed two methods to calculate analytically the transition probabilities between Markov states. These methods involve the joint density for the channel eigenvalues at two adjacent time instances and the level crossing rates (LCR) of the condition number. We then use our Markov model to investigate the behavior of dual-mode antenna selection schemes in an i.i.d. Rayleigh fading channel.

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“…Channel estimates are assumed to be error-free at the receiver, so that noncausal channel smoothing with high accuracy can be performed using Wiener interpolator filters [10]. This assumption enables coherent detection at the receiver and is commonly adopted in such systems [11], [12].…”

Section: System Model and Assumptionsmentioning

confidence: 99%

Predictive Transmit Antenna Selection with Maximal Ratio Combining

Prakash

McLoughlin

2009

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

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Abstract-Antenna selection has long been a pragmatic method for exploiting spatial diversity in wireless systems with lower complexity than space-time or MIMO coding, and potentially having reduced hardware cost due to the reduction in the number of RF chains required. Whilst receive antenna selection is perhaps more common, transmit antenna selection also has several advantages, particularly for hardware-costly transmit schemes such as those requiring linearisation. However transmit antenna selection (TAS) requires either channel knowledge, or receiver knowledge at the transmitter, typically achieved using data transmission in the reverse direction, and this implies a delay between the channel being sampled and being acted upon. This outdated channel knowledge degrades system performance. In this paper, the degradation is determined, and related to the channel characteristics. A prediction scheme is then applied to mitigate against this degradation for the case of a (2,1;2) TAS system, where one of two transmit antenna is selected to communicate with two receive antennae employing maximal ratio combining.

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Impact of Channel Prediction on Adaptive Coded Modulation Performance in Rayleigh Fading

Cited by 129 publications

References 12 publications

Adaptive Coded Modulation With Receive Antenna Diversity and Imperfect Channel Knowledge at Receiver and Transmitter

Adaptive Coded Modulation With Receive Antenna Diversity and Imperfect Channel Knowledge at Receiver and Transmitter

A Markov Model for MIMO Channel Condition Number with Application to Dual-Mode Antenna Selection

Predictive Transmit Antenna Selection with Maximal Ratio Combining

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