34 research outputs found
Flexible Multi-ASIP SoC for Turbo/LDPC Decoder
International audienceIn order to meet flexibility and performance constraints of current and future digital communication applications, multiple ASIPs combined with dedicated communication and memory architectures are required. In this work we consider the design of an innovative universal channel decoder architecture model by unifying flexibility-oriented and optimization-oriented approaches. Towards this objective, we have designed a flexible and scalable multiprocessor platform based on a novel ASIP architecture for high throughput turbo/LDPC decoding. The proposed platform supports turbo and LDPC codes of most emerging wireless communication standards (WiFi, WiMax, LTE, and DVB-RCS). Energy-aware optimisation techniques have been also proposed and implemented. Finally, a fully functional FPGA demonstrator is available and the proposed Multi-ASIP architecture has been successfully integrated into a new generation telecom chip
Improving Network-on-Chip-based Turbo Decoder Architectures
In this work novel results concerning Networkon- Chip-based turbo decoder architectures are presented. Stemming from previous publications, this work concentrates first on improving the throughput by exploiting adaptive-bandwidth-reduction techniques. This technique shows in the best case an improvement of more than 60 Mb/s. Moreover, it is known that double-binary turbo decoders require higher area than binary ones. This characteristic has the negative effect of increasing the data width of the network nodes. Thus, the second contribution of this work is to reduce the network complexity to support doublebinary codes, by exploiting bit-level and pseudo-floatingpoint representation of the extrinsic information. These two techniques allow for an area reduction of up to more than the 40 % with a performance degradation of about 0.2 d
Turbo NOC: a framework for the design of Network On Chip based turbo decoder architectures
This work proposes a general framework for the design and simulation of
network on chip based turbo decoder architectures. Several parameters in the
design space are investigated, namely the network topology, the parallelism
degree, the rate at which messages are sent by processing nodes over the
network and the routing strategy. The main results of this analysis are: i) the
most suited topologies to achieve high throughput with a limited complexity
overhead are generalized de-Bruijn and generalized Kautz topologies; ii)
depending on the throughput requirements different parallelism degrees, message
injection rates and routing algorithms can be used to minimize the network area
overhead.Comment: submitted to IEEE Trans. on Circuits and Systems I (submission date
27 may 2009
Configurable and Scalable Turbo Decoder for 4G Wireless Receivers
The increasing requirements of high data rates and quality of service (QoS) in fourth-generation (4G) wireless communication require the implementation of practical capacity approaching codes. In this chapter, the application of Turbo coding schemes that have recently been adopted in the IEEE 802.16e WiMax standard and 3GPP Long Term Evolution (LTE) standard are reviewed. In order to process several 4G wireless standards with a common hardware module, a reconfigurable and scalable Turbo decoder architecture is presented. A parallel Turbo decoding scheme with scalable parallelism tailored to the target throughput is applied to support high data rates in 4G applications. High-level decoding parallelism is achieved by employing contention-free interleavers. A multi-banked memory structure and routing network among memories and MAP decoders are designed to operate at full speed with parallel interleavers. A new on-line address generation technique is introduced to support multiple Turbo
interleaving patterns, which avoids the interleaver address memory that is typically necessary in the traditional designs. Design trade-offs in terms of area and power efficiency are analyzed for different parallelism and clock frequency goals
Exploiting generalized de-Bruijn/Kautz topologies for flexible iterative channel code decoder architectures
Modern iterative channel code decoder architectures have tight constrains on the throughput but require flexibility to support different modes and standards. Unfortunately, flexibility often comes at the expense of increasing the number of clock cycles required to complete the decoding of a data-frame, thus reducing the sustained throughput. The Network- on-Chip (NoC) paradigm is an interesting option to achieve flexibility, but several design choices, including the topology and the routing algorithm, can affect the decoder throughput. In this work logarithmic diameter topologies, in particular generalized de-Bruijn and Kautz topologies, are addressed as possible solutions to achieve both flexible and high throughput architectures for iterative channel code decoding. In particular, this work shows that the optimal shortest-path routing algorithm for these topologies, that is still available in the open literature, can be efficiently implemented resorting to a very simple circuit. Experimental results show that the proposed architecture features a reduction of about 14% and 10% for area and power consumption respectively, with respect to a previous shortest-path routing-table-based desig
Turbo NOC: a framework for the design of Network-on-Chip-basedturbo decoder architectures
This paper proposes a general framework for the design and simulation of network-on-chip-based turbo decoder architectures. Several parameters in the design space are investigated, namely, network topology, parallelism degree, the rate at which messages are sent by processing nodes over the network, and routing strategy. The main results of this analysis are as follows: 1) the most suited topologies to achieve high throughput with a limited complexity overhead are generalized de Bruijn and generalized Kautz topologies and 2) depending on the throughput requirements, different parallelism degrees, message injection rates, and routing algorithms can be used to minimize the network area overhead