An Implementation Method of a Ultra-High Speed Variable Block Code Data Encoding and Decoding Structure

Iterative decoding structure is the main feature of Turbo code decoding. It can improve the performance of Turbo decoding, but also increase the decoding complexity, time delay and power consumption. This paper proposes a parallel decoding structure of Turbo code based on double prediction control, i.e., using double prediction control module instead of two iterative decoding algorithms. Since the computation quantity and computing time of the Double Prediction Control Algorithm (DPCA) is smaller than the traditional decoding algorithm, the complexity and delay of the decoding algorithm can be reduced by the new decoding scheme presented in this paper. Exterior information simulations show that comparing to the traditional iterative decoding, time delay can be reduced by at least three times by using prediction scheme each time, while the BER performance simulation results show that the error-rate performance of the new decoding structure based on DPCA is only lower by 0.1 dB than the traditional Turbo decoding structure, but has a good approximation BER curves to the traditional one. When reasonably choose the two prediction intervals, it can achieve the coincident BER curve.

In this paper, we propose three categories of iterative decoding structures of three-dimensional(3-D) turbo product code(TPC), which is based on soft-input-soft-output(SISO) iterative decoding algorithm. Then by weighing the bit-error-rate(BER) curves of the 3-D TPC serial iterative decoder, a hybrid form of serial and parallel decoder and the parallel iterative decoder, and an optimal iterative decoding scheme is emerged. Furthermore, via adjusting the iterative weighing coefficient of the extrinsic information and equilibrating the proportion between the extrinsic information and the received information while decoding, the soft information of each bit is continuously modified to increase its reliability, delivering better decoding performance. Moreover, based on the enhanced structure of the 3-D TPC parallel iterative algorithm, we test different kinds of combinations of weighing coefficient, and pick out the best choice to achieve the lowest BER. Simulation results show that the performance of the modified 3-D TPC parallel decoder is substantially augmented under the circumstance of 3dB signal noise ratio(SNR) and 0.706 code rate, where the BER is quite close to the Shannon limit. under where its BER is almost approaching 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−6</sup> , which meets the BER requirements in modern wireless communication systems.

: Many optical computing problems are centered around the processing of incoherent images. These images may be conventional visible light such as those taken with a CCD imager or camcorder. They may also take the form of infrared images in the case of missile seekers or x-ray images from medical or other sources. For optical processing, these images must be converted to either phase or amplitude modulated coherent light. This is typically accomplished by electronically feeding the originally captured image into a spatial light. modulator (e.g., liquid crystal- or deformable mirror array) and modulating a coherent reference beam with the 2 dimensional data pattern. The electrical input to the SLM creates a data flow bottleneck in the optical processing system due to - the inherently serial input architecture. SMD - has proposed a - novel - incoherent to coherent Image converter which solves this problem by providing a massively parallel, optical input feed capability. The proposed architecture utilizes a novel combination of micromachining and ultra-thinned wafer technology to achieve an integrated incoherent to coherent image converter. The converter is capable of directly converting UV, IR, visible, and x-ray energy to a coherent light representation allowing for maximum utilization of downstream optical processing.

We consider message-passing strategies for the iterative decoding of multiple turbo codes (MTCs). We contradict the conventional wisdom that the parallel decoding structure is the best for MTCs by proposing new non-parallel decoding structures which give better BER performances for the same computational complexity. Under a modified independent Gaussian assumption (IGA), we are able to theoretically validate our design, which is further supported by extensive simulation results.

Call admission control (CAC) is one of the techniques deployed in managing network resources. Recently, the dynamic QoSaware CAC (DQA-CAC) algorithm was proposed to reduce the new connection blocking rate and improve resource utilization. However, the algorithm admits new connections and degrades existing ones without recourse to delay requirements of delay-intolerant extended real-time polling service (ertPS) and real-time polling service (rtPS) connections—which may incur additional delay, leading to an increase in packet drop rate and, consequently, reduced throughput. In this article, a QoS-guaranteed call admission control (QOG-CAC) algorithm is proposed to ensure QoS and consequently increase the throughput of all class of connections. The proposed QOG-CAC is simulated using a Java-based discrete event simulator. The results of the extensive simulation experiments conducted show that the proposed algorithm outperforms the compared scheme with regard to average system throughput, new connection blocking rate, and per-flow throughput of real-time as well as non-real-time connections

Ultra low bit error rate (BER) is required in high speed communications such as the 100 Gbit/s long haul optic communications. In this paper, a type of simple product codes is proposed using low density parity check (LDPC) codes with very high rate algebraic block codes by exploiting the sparsity of LDPC decoding failure and sparse error distribution in an LDPC frame with errors. Specifically, different with traditional product codes, the information bits are first encoded with very high rate algebraic block codes of low encoding and decoding complexity. Even the block codes correcting a single error using algebraic decoding method can be used. Then, LDPC codes are used as the inner code to obtain a low decoding threshold using iterative decoding. This design scheme can achieve the ultra low bit error rate at relatively low signal-to-noise ratios. The cost of the proposed scheme is the relatively large latency, which is not so critical for the ultra high speed communications.

Throughput maximization in multi-slice cooperative NOMA-based system with underlay D2D communications

Spatially-coupled low-density parity-check (SC-LDPC) codes have been shown to be superior in performance than LDPC block codes. In order to comply with the practical constraints on latency, SC-LDPC codes are decoded using a window decoder that reduces the decoder latency and complexity compared to traditional block-wise decoding. However, so far the literature only considers the structural decoding latency of window decoder, ignoring the processing latency. Note that the processing latency directly impacts the decoder's throughput and is an important parameter in any modern communication system. The throughput of an iterative decoder is directly influenced by the number of iterations and hence in this paper we propose a fully parallel window decoder architecture for SC-LDPC codes where the decoding iterations are performed in parallel. This guarantees a high throughout while fulfilling the low latency requirements. The overall decoding latency (structural and processing latency) of the proposed window decoder architecture is compared with the classical window decoder.

The concatenation scheme MLC-STBC combining multilevel codes (MLC) and space-time block codes (STBC) is proposed over Rayleigh fading channels. Through performance analysis and computer simulation, the asymptotic behavior of the new system is provided, which is proportional to the product of the space diversity and the minimum Hamming distance of the component codes. The simulation results show that, with the same bandwidth efficiency, the concatenation scheme has better power efficiency than the MLC system. Considering the fact that multistage decoding (MSD) and parallel decoding on levels (PDL) have a little difference in the system performance, the concatenation scheme MLC-STBC with PDL decoding method (MLC-STBC/PDL) achieves better trade-off between performance and complexity.

By using the time-varying channel responses of individual users, suitable dynamic resource allocation (DRA) strategies can improve resource utilization to provide broadband multimedia services of different QoS requirements over OFDM downlink in mobile cellular systems (Damji, N. and Le-Ngoc, T., ICC04, 2004). For non-realtime traffic, queueing can be used in conjunction with DRA to enhance further the system performance in terms of system spectral efficiency (b/s/Hz/cell) and system throughput. Performance of the proposed DRA schemes with queueing in various traffic and propagation conditions is evaluated and compared.

Heterogeneous network (HetNet) is considered to be the most promising approach for increasing communication capacity. However, HetNet control problems are difficult due to their intertier interference. Recently, the enhanced intercell interference coordination (eICIC) technology is introduced to offer several benefits, including a more equitable traffic load distribution across the macro and embedded small cells. In this paper, we design a new resource allocation scheme for the eICIC-based HetNet. Our proposed scheme is formulated as a joint cooperative game to handle conflicting requirements. By adopting the ideas of Kalai and Smorodinsky solution (KSS), multicriteria Kalai and Smorodinsky solution (MCKSS), and sequential Raiffa solution (SRS), we develop a hybrid control algorithm for an adaptive resource sharing between different base stations. To effectively adjust the eICIC fraction rates, the concepts of MCKSS and SRS are applied in an interactive manner. For mobile devices in the HetNet, the assigned resource is distributed by using the idea of KSS. The key insight of our algorithm is to translate the originally competitive problem into a hierarchical cooperative problem to reach a socially optimal outcome. The main novelty of our approach is its flexibility to reach a reciprocal consensus under dynamic HetNet environments. Exhaustive system simulations illustrate the performance gains along different dimensions, such as system throughput, device payoff, and fairness among devices. The superiority of our proposed scheme is fully demonstrated in comparison with three other existing eICIC control protocols.

In this paper, we present a practical adaptive multiple-input multiple-output (MIMO) transmission approach for broadband wireless multiuser systems. The proposed scheme adaptively switches between open-loop and closed-loop MIMO modes, depending on the users' channel conditions and required rates, as a means to enhance the system throughput and performance. Each mode is a combination of a MIMO transmission technique (space-time block coding and/or spatial multiplexing or beamforming) and a modulation/coding scheme. We first evaluate the spectral efficiency of each mode and provide a simple way to select adaptively the best mode among the open-loop and closed-loop available transmission modes in a Rayleigh/composite fading environment. Based on these results, we propose a simple and practical switching criterion that is shown to yield significant spectral efficiency improvements over independent adaptive open-loop or closed-loop schemes for typical multiuser system scenarios. Simulations in an IEEE 802.16e framework illustrate significant improvements in throughput performance.

In cellular communications, deploying a larger number of antennas at the base station, also called massive multiple-input multiple-output (MIMO), can offer a significant improvement in system throughput. In this paper, we exploit the spatial fading correlations in massive MIMO to reduce the downlink training and the corresponding feedback overhead in frequency division duplexing systems. We first study the user clustering, where the users with similar spatial channel correlations are clustered together. In the study, we provide the optimal metric and prove the convergence of the user clustering. Then, we propose an efficient eigenspace training and precoding (EETP) framework, where two different prebeamforming matrices are designed to minimize the channel estimation error and to manage the inter-user interference, respectively. In the results, we show that the channel estimation error for EETP decreases monotonically when either the number of prebeamforming vectors or the number of clusters increases. The spectral efficiency of the new algorithms is evaluated extensively with different user distributions, errors in channel correlations, different numbers of clusters, and different coherence block lengths, as well as with dynamic user scheduling for a large number of users. The new EETP not only achieves significant savings in the downlink training and the corresponding feedback, but also offers significantly higher system throughput compared with the existing schemes in the literature.

We consider the decoding problem for low-density parity-check codes, and apply nonlinear programming methods. This extends previous work using linear programming (LP) to decode linear block codes. First, a multistage LP decoder based on the branch-and-bound method is proposed. This decoder makes use of the maximum-likelihood-certificate property of the LP decoder to refine the results when an error is reported. Second, we transform the original LP decoding formulation into a box-constrained quadratic programming form. Efficient linear-time parallel and serial decoding algorithms are proposed and their convergence properties are investigated. Extensive simulation studies are performed to assess the performance of the proposed decoders. It is seen that the proposed multistage LP decoder outperforms the conventional sum-product (SP) decoder considerably for low-density parity-check (LDPC) codes with short to medium block length. The proposed box-constrained quadratic programming decoder has less complexity than the SP decoder and yields much better performance for LDPC codes with regular structure

International audience