Beyond Gbps Turbo Decoder on Multi-Core CPUs

International audienceThis paper presents a high-throughput implementation of a portable software turbo decoder. The code is optimized for traditional multi-core CPUs (like x86) and it is based on the Enhanced max-log-MAP turbo decoding variant. The code follows the LTE-Advanced specification. The key of the high performance comes from an inter-frame SIMD strategy combined with a fixed-point representation. Our results show that proposed multi-core CPU implementation of turbo-decoders is a challenging alternative to GPU implementation in terms of throughput and energy efficiency. On a high-end processor, our software turbo-decoder exceeds 1 Gbps information throughput for all rate-1/3 LTE codes with K < 4096

Efficient FPGA Implementation of a CTC Turbo Decoder for WiMAX/LTE Mobile Systems

This chapter describes the implementation on field programmable gate array (FPGA) of a turbo decoder for 3GPP long-term evolution (LTE) standard, respectively, for IEEE 802.16-based WiMAX systems. We initially present the serial decoding architectures for the two systems. The same approach is used; although for WiMAX the scheme implements a duo-binary code, while for LTE a binary code is included. The proposed LTE serial decoding scheme is adapted for parallel transformation. Then, considering the LTE high throughput requirements, a parallel decoding solution is proposed. Considering a parallelization with N = 2p levels, the parallel approach reduces the decoding latency N times versus the serial decoding one. For parallel approach the decoding performance suffers a small degradation, but we propose a solution that almost eliminates this degradation, by performing an overlapped data block split. Moreover, considering the native properties of the LTE quadratic permutation polynomial (QPP) interleaver, we propose a simplified parallel decoder architecture. The novelty of this scheme is that only one interleaver module is used, no matter the value of N, by introducing an even-odd merge sorting network. We propose for it a recursive approach that uses only comparators and subtractors

1.5 Gbit/s FPGA implementation of a fully-parallel turbo decoder designed for mission-critical machine-type communication applications

In wireless communication schemes, turbo codes facilitate near-capacity transmission throughputs by achieving reliable forward error correction. However, owing to the serial data dependencies imposed by the underlying Logarithmic Bahl-Cocke-Jelinek-Raviv (Log- BCJR) algorithm, the limited processing throughputs of conventional turbo decoder implementations impose a severe bottleneck upon the overall throughputs of realtime wireless communication schemes. Motivated by this, we recently proposed a Fully Parallel Turbo Decoder (FPTD) algorithm, which eliminates these serial data dependencies, allowing parallel processing and hence offering a significantly higher processing throughput. In this paper, we propose a novel resource-efficient version of the FPTD algorithm, which reduces its computational resource requirement by 50%, which enhancing its suitability for Field-Programmable Gate Array (FPGA) implementations. We propose a model FPGA implementation. When using a Stratix IV FPGA, the proposed FPTD FPGA implementation achieves an average throughput of 1.53 Gbit/s and an average latency of 0.56 s, when decoding frames comprising N=720 bits. These are respectively 13.2 times and 11.1 times superior to those of the state-of-the- art FPGA implementation of the Log-BCJR Long- Term Evolution (LTE) turbo decoder, when decoding frames of the same frame length at the same error correction capability. Furthermore, our proposed FPTD FPGA implementation achieves a normalized resource usage of 0.42 kALUTs Mbit/s , which is 5.2 times superior to that of the benchmarker decoder. Furthermore, when decoding the shortest N=40-bit LTE frames, the proposed FPTD FPGA implementation achieves an average throughput of 442 Mbit/s and an average latency of 0.18 s, which are respectively 21.1 times and 10.6 times superior to those of the benchmarker decoder. In this case, the normalized resource usage of 0.08 kALUTs Mbit/s is 146.4 times superior to that of the benchmarker decoder

Turbo Decoder with early stopping criteria

The turbo code used in the 3GPP Long Term Evolution(LTE) standard have been chosen specifically to simplify parallel turbo decoding and thus achieving higher throughputs. The higher data rates however leads to an increased computational complexity and thus a higher power and energy consumption of the decoder. This report presents a turbo decoder for the LTE standard with a stopping crite- ria aimed to reduce the power and energy consumption of the turbo decoder. The decoder can be configured to use 1,2 ,4 ,8 or 16 MAP decoders in parallel achiev- ing a throughput of 110 Mb/s for 7 iterations when running at a clock frequency of 200 MHz. The decoder were synthesised with 65 nm low power libraries with an area of 1.6 mm 2 . The post-synthesis simulations shows that the stopping cri- teria can lead to a significant lower energy consumption with no performance loss.The cellular market are constantly growing with more users every day. Today the smart- phone and tablet are common commodities which are able to both stream music as well as high definition video. The increasing amount of user in combination with the increasing data rate requirements puts high demands on the mobile operators networks. However the frequency spectrum is crowded with dif- ferent competing technologies and thus the available bandwidth are scarce. Ensuring a reliable communication and efficient use of the available resources are thus vital

On chip interconnects for multiprocessor turbo decoding architectures

International audienc

VLSI Implementation of a Soft-Output Signal Detector for Multi-Mode Adaptive MIMO Systems

This paper presents a multimode soft-output multiple-input multiple-output (MIMO) signal detector that is efficient in hardware cost and energy consumption. The detector is capable of dealing with spatial-multiplexing (SM),break space-division-multiple-access (SDMA), and spatial-diversity (SD) signals of 4 ✕ 4 antenna and 64-QAM modulation. Implementation-friendly algorithms, which reuse most of the mathematical operations in these three MIMO modes, are proposed to provide accurate soft detection information, i.e., log-likelihood ratio, with much reduced complexity. A unified reconfigurable VLSI architecture has been developed to eliminate the implementation of multiple detector modules. In addition, several block level technologies, such as parallel metric update and fast bit-flipping, are adopted to enable a more efficient design. To evaluate the proposed techniques, we implemented the triple-mode MIMO detector in a 65-nm CMOS technology. The core area is 0.25 mm2 with 83.7 K gates. The maximum detecting throughput is 1 Gb/s at 167-MHz clock frequency and 1.2-V supply, which archives the data rate envisioned by the emerging long-term evolution advanced standard. Under frequency-selective channels, the detector consumes 59.3-, 10.5-, and 169.6-pJ energy per bit detection in SM, SD, and SDMA modes, respectively

System capacity enhancement for 5G network and beyond

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Doctor of PhilosophyThe demand for wireless digital data is dramatically increasing year over year. Wireless communication systems like Laptops, Smart phones, Tablets, Smart watch, Virtual Reality devices and so on are becoming an important part of people’s daily life. The number of mobile devices is increasing at a very fast speed as well as the requirements for mobile devices such as super high-resolution image/video, fast download speed, very short latency and high reliability, which raise challenges to the existing wireless communication networks. Unlike the previous four generation communication networks, the fifth-generation (5G) wireless communication network includes many technologies such as millimetre-wave communication, massive multiple-input multiple-output (MIMO), visual light communication (VLC), heterogeneous network (HetNet) and so forth. Although 5G has not been standardised yet, these above technologies have been studied in both academia and industry and the goal of the research is to enhance and improve the system capacity for 5G networks and beyond by studying some key problems and providing some effective solutions existing in the above technologies from system implementation and hardware impairments’ perspective. The key problems studied in this thesis include interference cancellation in HetNet, impairments calibration for massive MIMO, channel state estimation for VLC, and low latency parallel Turbo decoding technique. Firstly, inter-cell interference in HetNet is studied and a cell specific reference signal (CRS) interference cancellation method is proposed to mitigate the performance degrade in enhanced inter-cell interference coordination (eICIC). This method takes carrier frequency offset (CFO) and timing offset (TO) of the user’s received signal into account. By reconstructing the interfering signal and cancelling it afterwards, the capacity of HetNet is enhanced. Secondly, for massive MIMO systems, the radio frequency (RF) impairments of the hardware will degrade the beamforming performance. When operated in time duplex division (TDD) mode, a massive MIMO system relies on the reciprocity of the channel which can be broken by the transmitter and receiver RF impairments. Impairments calibration has been studied and a closed-loop reciprocity calibration method is proposed in this thesis. A test device (TD) is introduced in this calibration method that can estimate the transmitters’ impairments over-the-air and feed the results back to the base station via the Internet. The uplink pilots sent by the TD can assist the BS receivers’ impairment estimation. With both the uplink and downlink impairments estimates, the reciprocity calibration coefficients can be obtained. By computer simulation and lab experiment, the performance of the proposed method is evaluated. Channel coding is an essential part of a wireless communication system which helps fight with noise and get correct information delivery. Turbo codes is one of the most reliable codes that has been used in many standards such as WiMAX and LTE. However, the decoding process of turbo codes is time-consuming and the decoding latency should be improved to meet the requirement of the future network. A reverse interleave address generator is proposed that can reduce the decoding time and a low latency parallel turbo decoder has been implemented on a FPGA platform. The simulation and experiment results prove the effectiveness of the address generator and show that there is a trade-off between latency and throughput with a limited hardware resource. Apart from the above contributions, this thesis also investigated multi-user precoding for MIMO VLC systems. As a green and secure technology, VLC is achieving more and more attention and could become a part of 5G network especially for indoor communication. For indoor scenario, the MIMO VLC channel could be easily ill-conditioned. Hence, it is important to study the impact of the channel state to the precoding performance. A channel state estimation method is proposed based on the signal to interference noise ratio (SINR) of the users’ received signal. Simulation results show that it can enhance the capacity of the indoor MIMO VLC system