Optimal training and redundant precoding for block transmissions with application to wireless OFDM

Ohno, Shûichi; Giannakis, Georgios B.

doi:10.1109/icassp.2001.940481

Cited by 51 publications

(102 citation statements)

References 17 publications

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“…Also, as β is decreased from 1 to 0 the MSEE keeps improving at the cost of bandwidth efficiency. When β = 0 and T p = 1, the MSEE expression becomes identical to the comb type pilot based channel estimation as discussed in [9]. When β = 1 and T p = 1, the MSEE expression becomes identical to the superimposed training based channel estimation scheme as discussed in [10].…”

Section: Mean Square Estimation Errormentioning

confidence: 63%

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Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

Nair

Kumar

2009

Circuits Syst Signal Process

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This work pertains to the use of superimposed training (ST) for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. A time domain coherent averaging based channel estimator is derived from the least squares criterion. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and the bit error rate (BER) of the OFDM system. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.

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Section: Mean Square Estimation Errormentioning

confidence: 63%

“…When β = 0, there is no influence of the data symbols on the channel estimate and the method is identical to the comb type pilots based channel estimation method as in [9]. In this case, the most superior performance may be achieved at the cost of a loss in bandwidth due to training.…”

Section: The Proposed Controlled Superimposition Of Training Sequencesmentioning

confidence: 84%

Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

Nair

Kumar

2009

Circuits Syst Signal Process

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“…Alice sends her training matrix, X a , to Bob. For channel identifiability, X a should be full-rank (M) and such that (L ≥ M) [4,8]. Following (1), Bob receives:…”

Section: Echo-mimo: An Overviewmentioning

confidence: 99%

Transparent Inband Feedback for Training-Based MIMO Systems

Souihli

Ohtsuki

2010

Wireless Pers Commun

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Recently, Echo-MIMO, a delay-free feedback scheme has been proposed for Closed-Loop MIMO systems, where the receiver echoes the received signal on the fly to the transmitter without any processing. While this reduced feedback latency allows for more use of the channel's coherence time for data transmission, it comes at high power-and-bandwidth costs, as two MIMO transmissions are required in the feedback phase. In this paper, we present a feedback scheme that preserves the advantages of Echo-MIMO while requiring only one feedback transmission. The echoed signals are judiciously combined with the receiver's signals such that their separation at the transmitter be lossless, and that no extra transmit power nor bandwidth be required. In addition, we highlight the estimation accuracy degradation in Echo-MIMO owing to the echoed noise, and analytically confirm the intuition that removing the noise prior to echoing the received signal provides better estimation than echoing the noisy received signal as is and later account for the noise effect upon echo reception. Simulation results show that the proposed scheme outperforms Echo-MIMO in terms of channel estimation accuracy and achievable capacity.

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“…In [13] it has been derived using a lower bound on the average ergodic capacity of the channel as an optimisation criterion. Alternatively, authors of [12] and [14] searched for the optimal pilot-to-data power ratio (PDR) to minimise probability of error.…”

Section: Introductionmentioning

confidence: 99%

“…There have been a number of studies dedicated to the training structure optimisation in the single-input-single-output (SISO) OFDM systems. It has been analytically established that the best channel estimation performance is achieved by loading pilot symbols on separate equispaced [11] [12][13] [14] and equipowered [12][13] [14] subcarriers. The other question is power allocation between pilot and data subcarriers.…”

Section: Introductionmentioning

confidence: 99%

Optimal Training for the SM-MIMO-OFDM Systems with MMSE Channel Estimation

Golovins

Ventura

2008

6th Annual Communication Networks and Services Research Conference (Cnsr 2008)

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Spatially multiplexed multiple-input-multiple-output orthogonal frequency division multiplexing (SM-MIMO-OFDM) systems are expected to provide a considerable increase of transmission capacity paving the way for the next generation broadband wireless communication standards. Considered MIMO-OFDM receiver performs estimation of the channel state information based on transmission of pilots concurrently with data symbols. The channel estimates are subsequently used for data detection. In this paper we discuss optimal placement and number of pilot subcarriers and derive the closed-form expression for the optimal power allocation between pilot and data symbols. The latter factor is important as under total transmit energy constraint there is a trade-off between boosting power of the pilot symbols to gain more accurate channel estimates and maintaining higher signal-to-noise ratio at the data subcarriers to minimise probability of detection error in the assumption of sufficiently reliable channel state information. KeywordsSpatial multiplexing, multipath channels, minimum mean squared error, pilot-to-data power ratio

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Optimal training and redundant precoding for block transmissions with application to wireless OFDM

Cited by 51 publications

References 17 publications

Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

Transparent Inband Feedback for Training-Based MIMO Systems

Optimal Training for the SM-MIMO-OFDM Systems with MMSE Channel Estimation

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