Prototyping of a high performance generic Viterbi decoder

Convolutional code is a coding scheme used in communication systems including deep space communications and wireless communications.It provides an alternative approach to block codes for transmission over a noisy channel.The block codes can be applied only for the block of data.The Convolutional coding has an advantage over the block codes in that it can be applied to a continuous data stream as well as to blocks of data.Viterbi decoder employed in digital wireless communication plays a rife role in the overall power consumption of trellis coded modulation decoder.Power reduction in Viterbi decoder could be achieved by reducing the number of states.A pre-computation architecture with T-algorithm was implemented for this purpose, and when we compare this result with full Trellis Viterbi decoder, this approach significantly reduces power consumption without degrading decoding speed.Convolutional encoding with viterbi decoding is a powerful FEC technique that is particularly suited to a channel in which the transmitted signal is corrupted mainly by Additive White Gaussian Noise (AWGN).It operates on data stream and has memory that uses previous bits to encode.The Viterbi Algorithm (VA) is proposed, used for decoding a bit stream that has been encoded using FEC code.The Convolutional encoder adds redundancy to a continuous stream of input data by using a linear shift register.A pre-computation architecture with Viterbi algorithm is implemented for this purpose, Viterbi (Convolutional) encoder and Viterbi decoder are designed and implemented using FPGA technology, which are the essential blocks in digital communication systems.It is particularly suited to a channel in which the transmitted signal is corrupted mainly by AWGN.The Viterbi decoder of Constraint length 7 and code rate ½ is considered.The design is implemented using verilog on Xilinx Spartan 3E and advanced Spartan 6 board and the results and Comparisons are presented.

This paper presents a high throughput (1Gbps) and moderate area for constraint length K=3, code rate R=1/2 and four states (N=4) hard decision state parallel Viterbi decoder. The Add Compare Select (ACS) unit in path metric unit is designed to reduce the latency of ACS loop delay by using Modified Carry Look Ahead Adder and Digital Comparator. We also consider the design of Survivor Memory Unit (SMU) which combines the advantages of both Register Exchange method and Trace Back method, to reduce the decoding latency and total area of the Viterbi decoder. The proposed Viterbi decoder design is described using Verilog HDL and implemented in standard cell ASIC flow using Synopsys EDA tool. The design operation is verified by decoding the one million bits. The behavior of the decoder is verified by using Synopsys simulator and synthesized using Synopsys Design Compiler in 65nm CMOS technology library. The proposed decoder operates at 250MHz, supply voltage 1.32V and operating temperature range -40°C to 125°C. The ACS architecture achieves 67.07% improvement in reduction of latency compared to the conventional ACS architecture and achieves 1.235 Gbps throughput. The results show that, the Viterbi decoder architecture achieves 73.03% to 92.46% improvement in area as compared to the other architectures. This reduction in latency and area finds application in high data rate communication.

Convolutional coding and Viterbi decoding, along with binary phase-shift keyed modulation, is presented as an efficient system for reliable communication on power limited satellite and space channels. Performance results, obtained theoretically and through computer simulation, are given for optimum short constraint length codes for a range of code constraint lengths and code rates. System efficiency is compared for hard receiver quantization and 4 and 8 level soft quantization. The effects on performance of varying of certain parameters relevant to decoder complexity and cost is examined. Quantitative performance degradation due to imperfect carrier phase coherence is evaluated and compared to that of an uncoded system. As an example of decoder performance versus complexity, a recently implemented 2-Mbit/s constraint length 7 Viterbi decoder is discussed. Finally a comparison is made between Viterbi and sequential decoding in terms of suitability to various system requirements.

This paper presents an approach of model-based design for implementing a digital communication system on a field programmable gate array (FPGA) for a software defined radio (SDR). SDR is a popular prototyping platform for wireless communication systems due to its flexibility and utility. A traditional SDR system performs nearly all computations and signal processing tasks on the host computer, and then sends the waveform to the RF front end. For complex algorithms or high data rate, the host computer becomes the processing bottleneck and FPGA is often employed as a hardware accelerator. This paper demonstrates the procedure of using model-based design for SDR targeted on FPGA hardware. A complete digital communication system, including a transmitter with convolutional encoder and a receiver with Viterbi decoder, is implemented on an FPGA-based SDR platform and validated by over-the-air demonstration. Synchronization algorithms, such as carrier frequency offset, phase offset, and time recovery, are also optimized for hardware efficiency.

SUMMARYIn wireless communication, Viterbi decoding algorithm (VDA) is the one of most popular channel decoding algorithms, which is widely used in WLAN, WiMAX, or 3G communications. However, the throughput of Viterbi decoder is constrained by the convolutional characteristic. Recently, the three‐point VDA (TVDA) was proposed to solve this problem. In TVDA, the whole procedure can be divided into three phases, the forward, trace‐back, and decoding phases. In this paper, we analyze the parallelism of TVDA and propose parallel TVDA on the multi‐core CPU, graphics processing unit (GPU), and field programmable gate array (FPGA). We demonstrate approaches that fully exploit its performance potential on CPU, GPU, and FPGA computing platforms. For CPU platforms, we perform two optimization methods, single instruction multiple data and multithreading to gain over 145 × speedup over the naive CPU version on a quad‐core CPU platform. For GPU platforms, we propose the combination of cached memory optimization, coalesced global memory accesses, codeword packing scheme, and asynchronous data transition, achieving the throughput of 404.65 Mbps and 12 × speedup over initial GPU versions on an NVIDIA GeForce GTX580 card and 7 × speedup over Intel quad‐core CPU i5‐2300, under the same manufacturing year and both with fully optimized schemes. In addition, for FPGA platforms, we customize a radix‐4 pipelined architecture for the TVDA in a 45‐nm FPGA chip from Xilinx (XC6VLX760). Under 209.15‐MHz clock rate, it achieves a throughput of 418.30 Mbps. Finally, we also discuss the performance evaluation and efficiency comparison of different flexible architectures for real‐time Viterbi decoding in terms of the decoding throughput, power consumption, optimization schemes, programming costs, and price costs.Copyright © 2013 John Wiley & Sons, Ltd.

At present, the Viterbi algorithm (VA) is widely used in communication systems for decoding and equalization. The achievable speed of conventional Viterbi decoders (VD's) is limited by the inherent nonlinear add-compare-select (ACS) recursion. The aim of this paper is to describe system design and VLSI implementation of a complex system of fabricated ASIC's for high speed Viterbi decoding using the minimized method (MM) parallelized VA. We particularly emphasize the interaction between system design, architecture and VLSI implementation as well as system partitioning issues and the resulting requirements for the system design flow. Our design objectives were 1) to achieve the same decoding performance as a conventional VD using the parallelized algorithm, 2) to achieve a speed of more than 1 Gb/s, and 3) to realize a system for this task using a single cascadable ASIC. With a minimum system configuration of four identical ASIC's produced by using 1.0 /spl mu/ CMOS technology, the design objective of a decoding speed of 1.2 Gb/s is achieved. This means, compared to previous implementations of Viterbi decoders, the speed is increased by an order of magnitude.

The Viterbi algorithm is widely applied to problems of the state estimation of a finite-state discrete-time Markov process, such as convolutional and trellis decoding. Although conventional Viterbi decoders process all states concurrently, the sequential nature of this algorithm limits the decoding throughput for a given integrated circuit technology and thereby restricts its applications. This paper presents the architecture of a single-chip Viterbi decoder combining two methods to speed-up the data rate: the "radix" trellis method and the interleaved method. The resulting architecture is very attractive for applications where high-speed decoding is essential, such as satellite digital communication systems.

Todays need is for increased content and bandwidth to drive communication systems, error control coding has a great demand. To maintain high reliable data and to improve the Bit Error Rate (BER), error correction technique like the Viterbi algorithm is one of the promising solutions. Though it is useful for error correction it dissipates large power. A lot many researches were carried out at architectural as well as algorithmic level to optimize the ACS (Add compare and Select) unit and Survival Memory Management in Synchronous Viterbi Decoders. But still there is a problem of power dissipation which requires more technical solutions. Due to requirements of high speed, low power, low weight and long battery life a low power Viterbi decoders has a great demand in the communication field. This paper proposed the method for survivor path storage and decoding as Minimum Transition Hybrid Register Exchange Method along with handshaking protocol as Level Encoded dual rail (LEDR) encoding to make the system asynchronous. The whole system has been designed on algorithmic level and Simulation is done on Xilinx Tool for Asynchronous Viterbi Decoder using MTHREM.

Increasing the speed of the wireless communication requires a reliable solution for data transfer. The signal to noise ratio (SNR) of the channel in digital wireless communication is one of the major limitations on the operating performance. To enhance the performance, solution in terms of coded data and error-correcting code has been introduced. Viterbi decoder is one of the techniques used for this purpose and Viterbi algorithm is used for decoding. This algorithm is an extremely fast and efficient method of decoding the coded data from the channel. In this paper, the structure of baseband processing unit and implementation of convolutional encoder and Viterbi decoder is described. The convolutional encoder of rate 1/2 and constraint length 3 and Viterbi decoder of rate 1/2 and constraint length 3 using a TMS320C54 DSP chip is designed.

A new approach to a reduced states Viterbi decoder (VD) is introduced which is based on a bounded metric. This approach is most attractive for combatting intersymbol interference (ISI) using a Viterbi algorithm, specifically if trellis coded modulation (TCM) is used. It has been shown that in the case of ISI the overall compound Viterbi decoding of ISI and TCM is much better than any other decoding algorithm, for example decision feedback. The most aggravating drawback of such an overall VD is its large number of states, resulting from both the TCM encoder and ISI memory. However, this large number of states can be substantially reduced by our method of a bounding metric, with a negligible performance degradation.

The Viterbi algorithm (VA) is the maximum likelihood decoding algorithm for convolutionally encoded data. Improvements in the performance of a concatenated coding system that uses VA decoding (inner decoder) can be obtained when, in addition to the standard VA output, an indicator of the reliability of the VA decision is delivered to the outer stage of processing. Two different approaches of extending the VA are considered. In the first approach, the VA is extended with a soft output (SOVA) unit that calculates reliability values for each of the decoded output information symbols. In the second approach, coding gains are obtained by delivering a list of the L best estimates of the transmitted data sequence, namely the list Viterbi decoding algorithm (LVA). Our main interest is to evaluate the LVA and the SOVA in comparison with each other, determine suitable applications for both algorithms and to construct extended versions of the LVA and the SOVA with low complexity that perform the task of the other algorithm. We define a list output VA using the output symbol reliability information of the SOVA to generate a list of size L and that also has a lower complexity than the regular LVA for a long list size. We evaluate the list-SOVA in comparison to the LVA. Further, we introduce a low complexity soft symbol output viterbi algorithm that accepts the (short) list output of the LVA and calculates for each of the decoded information bits a reliability value. The complexity and the performance of the soft-LVA (LVA and soft decoding unit) is a function of the list size L. The performance of the soft-LVA and the SOVA are compared in a concatenated coding system. A new software implementation of the iterative serial version of the LVA is also included. >

Software defined radio adapts various modulation schemes, encoding techniques by changing its configuration. It has earned great attention in the recent years for its flexibility to adapt various techniques without the need of replacement of the existing hardware. SDR reduces the cost complexity and provides the flexible communication system. This paper presents the viterbi decoder architecture with improved trace back unit for a code rate of 1/2 and a constraint length of k = 3. This decoder finds advantages in software defined radio applications due to its area efficiency and speed. The proposed decoder is simulated in Xilinx 14.1 and implemented in a field programmable gate array (FPGA).

In this work, we present a novel bitsliced high-performance Viterbi algorithm suitable for high-throughput and data-intensive communication. A new column-major data representation scheme coupled with the bitsliced architecture is employed in our proposed Viterbi decoder that enables the maximum utilization of the parallel processing units in modern parallel accelerators. With the help of the proposed alteration of the data scheme, instead of the conventional bit-by-bit operations, 32-bit chunks of data are processed by each processing unit. This means that a single bitsliced parallel Viterbi decoder is capable of decoding 32 different chunks of data simultaneously. Here, the Viterbi’s Add-Compare-Select procedure is implemented with our proposed bitslicing technique, where it is shown that the bitsliced operations for the Viterbi internal functionalities are efficient in terms of their performance and complexity. We have achieved this level of high parallelism while keeping an acceptable bit error rate performance for our proposed methodology. Our suggested hard and soft-decision Viterbi decoder implementations on GPU platforms outperform the fastest previously proposed works by and , achieving 21.41 and 8.24 Gbps on Tesla V100, respectively.

ABSTRACTA Viterbi algorithm (VA) is the optimal decoding strategy for the convolutional code. The Viterbi algorithm is complex and requires a large memory and delay. In this paper, an alternative sub‐optimal decoder based on the artificial neural network (ANN) is proposed and studied using a sliding block decoding algorithm. The ANN is trained in a supervised manner and the system parameters are optimised using computer simulations for the optimum performance. Comparative study with the Viterbi decoder is carried out. The performance of the ANN decoder is found to be comparable to the Viterbi ‘soft’ decoding with much reduced decoding length. The key advantages of the proposed ANN decoder compared with other ANN decoders are the reduced decoding and training length, adaptive decoding, no iteration required and possibility of parallel decoding. Copyright © 2012 John Wiley & Sons, Ltd.

Side-match vector quantization is a finite-state technique for image coding. This research shows that the side-match vector quantization is an error-propagating code and it is similar to a catastrophic convolutional code. Here, we propose a Viterbi-based algorithm to solve this problem. Various noise detection algorithms are integrated into the Viterbi algorithm (to yield the Viterbi-based algorithm) for a much better performance. According to the simulation of a binary symmetric channel with random bit-error rate (BER) 0.1%-0.01%, the Viterbi-based algorithm provides 2.8-9.6 dB and 2.3-8.4 dB gain compared with the conventional side-match vector quantization decoder and the Viterbi decoder, respectively. In addition, the proposed algorithm requires much fewer computations than the Viterbi algorithm.