Yuheng Huang

Tight BER bounds for iteratively decoded bit-interleaved space-time coded modulation

Iteratively decoded bit-interleaved space-time coded modulation (BI-STCM) greatly lowers bit error rate (BER) over fast Rayleigh fading multiple-input multiple-output (MIMO) channels. We develop a general, tight and efficient theoretical error-free feedback bound (EF bound) to analyze the asymptotic BER. The convergence to the EF bound and the accuracy of the prediction are verified by simulation. With the best rate 1/2 4-state convolutional code and the 16-QAM modified set partitioning labeling, the BER of 10/sup -6/ can be achieved at E/sub b//N/sub 0/=1.6 dB with 2 transmit and 2 receive antennas.

16-QAM BICM-ID in fading channels with imperfect channel state information

We analyze the impact of imperfect channel state information (CSI) on the performance of bit-interleaved coded modulation with iterative decoding (BICM-ID) over fading channels. We develop a general, accurate and efficient theoretical error-free feedback bound (EF bound) to analyze the asymptotic bit-error rate (BER) of BICM-ID with imperfect CSI, and predict the BER floor due to channel estimation error. The convergence to the EF bound and the accuracy of the BER floor prediction are verified by simulation with various sets of code and channel parameters. These results are canonical, in that they apply to a variety of system configurations. Pilot symbol assisted modulation is used as a particular example for Rayleigh-fading channels.

Joint iterative channel estimation and decoding for bit-interleaved coded modulation over correlated fading channels

We design and evaluate a novel and highly efficient algorithm, named sparsely interleaved estimation and decoding (SIED), for joint iterative channel estimation and decoding for bit-interleaved coded modulation (BICM) over flat correlated fading channels. In SIED, in order to effectively prevent error propagation, the decoding proceeds until the current decoder stage converges, and only then feeds back the best achievable decoding results to refine channel estimates. The on-line convergence is detected through the soft decoding metrics (SDMs). Further, we provide a unified analytic framework for both the choice of filter length and an asymptotic bit error rate (BER) analysis, where the key parameter is the power correlation coefficient between the fading and its estimate. Simulation results verify that our SIED algorithm can successfully break the barrier of the channel estimation error caused by conventional pilot symbol-assisted modulation (PSAM), and lead the BER to approach the ideal asymptotic performance. Compared to the classical iteratively filtered PSAM (IF-PSAM) algorithm, our proposed SIED algorithm has more than 0.5-dB improvement in E/sub b//N/sub 0/ for the normalized fade rate f/sub d/T/sub s/=0.05 with much lower complexity.

EXIT chart analysis of BICM-ID with imperfect channel state information

We analyze the convergence of iteratively decoded bit-interleaved coded modulation with imperfect channel state information using the extrinsic information transfer (EXIT) chart. A canonical analysis model is adopted, where the power correlation coefficient between the fading and its estimate becomes the key parameter affecting the extrinsic transfer characteristics of the demapper and hence the convergence of iterative decoding. We further illustrate that decoding convergence can be triggered by tradeoff between the quality of channel estimation and code rate.

EXIT chart analysis of BICM-ID over AWGN channels with SNR mismatch

We use the extrinsic information transfer (EXIT) chart to analyze the convergence of iteratively decoded bit-interleaved coded modulation with channel signal-to-noise ratio mismatch. For additive white Gaussian noise channels, we develop a generalized model for the a priori inputs, which is parameterized by the ratio /spl eta/ between the noise variance estimate and its true value. We show that the demapper and decoder transfer functions are very sensitive to overestimation of the noise variance (/spl eta/>0 dB), while indifferent to underestimation in a fairly large region (/spl eta//spl isin/[-6,0] dB). The accuracy of our EXIT chart prediction is verified by simulation.

The capacity of bit-interleaved space-time coded modulation with imperfect channel state information

We analyze the capacity of bit-interleaved space-time coded modulation (BI-STCM) over fast fading multiple-input multiple-output (MIMO) channels. The channel capacity and cutoff rate are computed under the uniform inputs constraint, when only imperfect channel state information (CSI) is available. A canonical model is adopted to analyze the impact of imperfect CSI, where the key parameter is the correlation coefficient between the corresponding fading gain and its estimate. Our results show that imperfect CSI can cause significant performance degradation in channel capacity, which implies that communication at high SNR can be very power inefficient with imperfect CSI.

Performance analysis for bit-interleaved space-time coded modulation with iterative decoding

Iteratively decoded bit-interleaved space-time coded modulation (BI-STCM) greatly lowers bit error rate (BER) over fast Rayleigh fading multiple-input multiple-output (MIMO) channels. We develop a general, tight and efficient theoretical error-free feedback bound (EF bound) to analyze the asymptotic BER when the receiver has either perfect or imperfect channel state information (CSI). The convergence to the EF bound and the accuracy of the prediction are verified by simulation for both cases. With the best rate 1/2 4-state convolutional code and the 16-QAM modified set partitioning labeling, the BER of 10/sup -6/ can be achieved at E/sub b//N/sub 0/ = 1.6 dB with 2 transmit and 2 receive antennas for the case of perfect CSI.