Effects of imperfect channel estimation on space–time coding performance

Hoteit, Wajih; Shayan, Yousef R.; Elhakeem, A.K.

doi:10.1049/ip-com:20045101

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…Observe that the second derivative of C lower with respect to α 2 (15) is nonpositive, therefore, the maximum on ∂C lower /∂α 2 (14) occurs at α 2 = 0, irrespective of α 1 . Furthermore, by adopting similar steps as in [16], one can show that ∂C lower /∂α 2 | α2=0 = 0, which proves that the maximum on the mutual information lower bound occurs at α 2 = 0 for any value of α 1 .…”

Section: Lemma 2 the Mutual Information Bounds Of D-stbcs Are Maximumentioning

confidence: 99%

“…In particular, it has been proven that spatio-temporal water-filling is the optimal power allocation strategy that achieves the capacity lower bound [11]. In addition, the performance of space-time coding in the presence of channel estimation error is studied in [13][14][15]. In particular, closed-form expressions for the pairwise error probability (PEP) of space-time codes in Rayleigh flatfading channels have been obtained in [15].…”

Section: Introductionmentioning

confidence: 99%

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Distributed Space-Time Block Coded Transmission with Imperfect Channel Estimation: Achievable Rate and Power Allocation

Musavian

Aı̈ssa

2007

EURASIP J. Adv. Signal Process.

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This paper investigates the effects of channel estimation error at the receiver on the achievable rate of distributed space-time block coded transmission. We consider that multiple transmitters cooperate to send the signal to the receiver and derive lower and upper bounds on the mutual information of distributed space-time block codes (D-STBCs) when the channel gains and channel estimation error variances pertaining to different transmitter-receiver links are unequal. Then, assessing the gap between these two bounds, we provide a limiting value that upper bounds the latter at any input transmit powers, and also show that the gap is minimum if the receiver can estimate the channels of different transmitters with the same accuracy. We further investigate positioning the receiving node such that the mutual information bounds of D-STBCs and their robustness to the variations of the subchannel gains are maximum, as long as the summation of these gains is constant. Furthermore, we derive the optimum power transmission strategy to achieve the outage capacity lower bound of D-STBCs under arbitrary numbers of transmit and receive antennas, and provide closed-form expressions for this capacity metric. Numerical simulations are conducted to corroborate our analysis and quantify the effects of imperfect channel estimation.

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Section: Lemma 2 the Mutual Information Bounds Of D-stbcs Are Maximumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Space-Time Block Coded Transmission with Imperfect Channel Estimation: Achievable Rate and Power Allocation

Musavian

Aı̈ssa

2007

EURASIP J. Adv. Signal Process.

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“…In a practical scenario, the CSI acquired by the transmitter and the receiver is imperfect because of a variety of sources such as channel estimation errors, quantisation and delay in the feedback channel. The imperfect CSI may cause high bit-error-rates (BERs) if not handled properly [3]. Therefore a robust design is necessary where the receiver can recover the symbols robustly and effectively from a noisy channel subject to model uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Worst-case mean square error (MSE) transceiver design for imperfect estimate multi-input-multi-output communication channels

2012

IET Commun.

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The authors consider the worst-case transceiver design problem under spectrum bounded channel uncertainty matrices. Their design aims to minimise the trace and the determinant of the estimate error covariance matrix, respectively. The authors relax the formulated problem into an optimisation problem with bilinear matrix inequality constraints (i.e. BMI problem), from which a local optimal solution is obtained by applying semi-definite programming. Furthermore, the authors consider norm bounded source symbols and extend their approach to design the worst-case transceiver with respect to both channel uncertainties and norm bounded source symbols.

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“…The radio channels in mobile radio systems are usually multipath fading channels that are causing intersymbol interference (ISI) in the received signal. To remove ISI from the signal, many kinds of channel estimation techniques are applied [6][7][8]. Since COST207 is a severe fading channel, it is necessary to employ powerful channel estimator such as artificial neural network (ANN) at the receiver side [9,10].…”

Section: Introductionmentioning

confidence: 99%

Performance of multi level‐turbo coding with neural network‐based channel estimation over WSSUS MIMO channels

Gose

2008

Int J Communication

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SUMMARYThis paper presents the performance of the transmit diversity-multi level turbo codes (TD-MLTC) over the multiple-input-multiple-output (MIMO) channels based on the wide sense stationary uncorrelated scattering (WSSUS). The multi level-turbo code (ML-TC) system contains more than one turbo encoder/decoder block in its structure. At the transmitter side, the ML-TC uses the group partitioning technique that partitions a signal set into several levels and encodes each level separately by a proper component of the encoder to improve error performance. The binary input sequence is passed through the MLTC encoder and mapped to 4-PSK and then fed into the transmit diversity scheme for high data transmission over wireless fading channels. At the receiver side, distorted multi-path signals are received by multiple receiver antennae. WSSUS MIMO channel parameters are estimated by using an artificial neural network and an iterative combiner. Input sequence of the first level of the MLTC encoder is estimated at the first level of MLTC decoder. Subsequently, the other input sequences are computed by using the estimated input bit streams of the previous levels. 4-PSK two-level turbo codes are simulated for 2T x −1R x and 2T x −2R x antenna configurations over WSSUS MIMO channels. Here, TD-MLTC and its efficient implementations are discussed and simulation results are given.

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Effects of imperfect channel estimation on space–time coding performance

Cited by 7 publications

References 5 publications

Distributed Space-Time Block Coded Transmission with Imperfect Channel Estimation: Achievable Rate and Power Allocation

Distributed Space-Time Block Coded Transmission with Imperfect Channel Estimation: Achievable Rate and Power Allocation

Worst-case mean square error (MSE) transceiver design for imperfect estimate multi-input-multi-output communication channels

Performance of multi level‐turbo coding with neural network‐based channel estimation over WSSUS MIMO channels

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