Turbo Decoder for Low-Power Ultrawideband Communication Systems

A new method to reduce the computational complexity of the turbo decoding in ultrawideband (UWB) orthogonal frequency division multiplexing (OFDM) system is proposed. Existing stopping techniques for turbo decoding process using constrained decoding assume fixed signal-to-noise ratio (SNR) for all the OFDM symbol bits so they fail to yield an acceptable bit-error rate (BER) performance in multicarrier systems. In this paper, we propose a bit-level stopping technique for turbo decoding process based on the constrained decoding method. In this technique, we combine the cyclic redundancy check (CRC) with an adaptive threshold on the log likelihood ratio (LLR) on each subcarrier to detect for convergence. The threshold is adaptive in the sense that the threshold on the LLR of a bit is determined by the average SNR of the OFDM symbol and the channel gain of the transmission subcarrier. Results show that when the channel state information (CSI) is used to determine the threshold on LLR, the stopping technique can reduce the computational complexity by about 0.5–2.5 equivalent iterations compared to GENIE turbo without degradation in the BER performance

Turbo Decoder for Low-Power Ultrawideband Communication Systems

A new method to reduce the computational complexity of the turbo decoding in ultrawideband (UWB) orthogonal frequency division multiplexing (OFDM) system is proposed. Existing stopping techniques for turbo decoding process using constrained decoding assume fixed signal-to-noise ratio (SNR) for all the OFDM symbol bits so they fail to yield an acceptable bit-error rate (BER) performance in multicarrier systems. In this paper, we propose a bit-level stopping technique for turbo decoding process based on the constrained decoding method. In this technique, we combine the cyclic redundancy check (CRC) with an adaptive threshold on the log likelihood ratio (LLR) on each subcarrier to detect for convergence. The threshold is adaptive in the sense that the threshold on the LLR of a bit is determined by the average SNR of the OFDM symbol and the channel gain of the transmission subcarrier. Results show that when the channel state information (CSI) is used to determine the threshold on LLR, the stopping technique can reduce the computational complexity by about 0.5-2.5 equivalent iterations compared to GENIE turbo without degradation in the BER performance

ENHANCEMENT OF ITERATIVE TURBO DECODING FOR HARQ SYSTEMS

This paper presents a new method for stopping the iterative turbo decoding. First, a bit-level convergence test using the cross-entropy analyses is used to select non converged bits and establish a simple and effective stopping rule. Next, an adaptive approach is used to compute a scaling factor for normalizing the extrinsic information of the previously selected bits. The extra coding gain obtained from this normalization can compensate for the performance degradation of the stopping rule. The simulation results of the proposed stopping criterion show an interesting application in a hybrid automatic repeat request systems with turbo coding scheme, where the decoding complexity can be fairly reduced. Simulation results of the proposed criterion, in comparison with previously published stopping rules, were presented for illustrating the adaptive termination according to a changing SNR environment

Iterative Decoding and Turbo Equalization: The Z-Crease Phenomenon

Iterative probabilistic inference, popularly dubbed the soft-iterative paradigm, has found great use in a wide range of communication applications, including turbo decoding and turbo equalization. The classic approach of analyzing the iterative approach inevitably use the statistical and information-theoretical tools that bear ensemble-average flavors. This paper consider the per-block error rate performance, and analyzes it using nonlinear dynamical theory. By modeling the iterative processor as a nonlinear dynamical system, we report a universal "Z-crease phenomenon:" the zig-zag or up-and-down fluctuation -- rather than the monotonic decrease -- of the per-block errors, as the number of iteration increases. Using the turbo decoder as an example, we also report several interesting motion phenomenons which were not previously reported, and which appear to correspond well with the notion of "pseudo codewords" and "stopping/trapping sets." We further propose a heuristic stopping criterion to control Z-crease and identify the best iteration. Our stopping criterion is most useful for controlling the worst-case per-block errors, and helps to significantly reduce the average-iteration numbers.Comment: 6 page

Information-Coupled Turbo Codes for LTE Systems

We propose a new class of information-coupled (IC) Turbo codes to improve the transport block (TB) error rate performance for long-term evolution (LTE) systems, while keeping the hybrid automatic repeat request protocol and the Turbo decoder for each code block (CB) unchanged. In the proposed codes, every two consecutive CBs in a TB are coupled together by sharing a few common information bits. We propose a feed-forward and feed-back decoding scheme and a windowed (WD) decoding scheme for decoding the whole TB by exploiting the coupled information between CBs. Both decoding schemes achieve a considerable signal-to-noise-ratio (SNR) gain compared to the LTE Turbo codes. We construct the extrinsic information transfer (EXIT) functions for the LTE Turbo codes and our proposed IC Turbo codes from the EXIT functions of underlying convolutional codes. An SNR gain upper bound of our proposed codes over the LTE Turbo codes is derived and calculated by the constructed EXIT charts. Numerical results show that the proposed codes achieve an SNR gain of 0.25 dB to 0.72 dB for various code parameters at a TB error rate level of $10^{-2}$, which complies with the derived SNR gain upper bound.Comment: 13 pages, 12 figure

Approximate MIMO Iterative Processing with Adjustable Complexity Requirements

Targeting always the best achievable bit error rate (BER) performance in iterative receivers operating over multiple-input multiple-output (MIMO) channels may result in significant waste of resources, especially when the achievable BER is orders of magnitude better than the target performance (e.g., under good channel conditions and at high signal-to-noise ratio (SNR)). In contrast to the typical iterative schemes, a practical iterative decoding framework that approximates the soft-information exchange is proposed which allows reduced complexity sphere and channel decoding, adjustable to the transmission conditions and the required bit error rate. With the proposed approximate soft information exchange the performance of the exact soft information can still be reached with significant complexity gains.Comment: The final version of this paper appears in IEEE Transactions on Vehicular Technolog