5 research outputs found
Multi-standard programmable baseband modulator for next generation wireless communication
Considerable research has taken place in recent times in the area of
parameterization of software defined radio (SDR) architecture. Parameterization
decreases the size of the software to be downloaded and also limits the
hardware reconfiguration time. The present paper is based on the design and
development of a programmable baseband modulator that perform the QPSK
modulation schemes and as well as its other three commonly used variants to
satisfy the requirement of several established 2G and 3G wireless communication
standards. The proposed design has been shown to be capable of operating at a
maximum data rate of 77 Mbps on Xilinx Virtex 2-Pro University field
programmable gate array (FPGA) board. The pulse shaping root raised cosine
(RRC) filter has been implemented using distributed arithmetic (DA) technique
in the present work in order to reduce the computational complexity, and to
achieve appropriate power reduction and enhanced throughput. The designed
multiplier-less programmable 32-tap FIR-based RRC filter has been found to
withstand a peak inter-symbol interference (ISI) distortion of -41 dB
Automated optimization of reconfigurable designs
Currently, the optimization of reconfigurable design parameters is typically done manually and often involves substantial amount effort. The main focus of this thesis is to reduce this effort. The designer can focus on the implementation and design correctness, leaving the tools to carry out optimization. To address this, this thesis makes three main contributions.
First, we present initial investigation of reconfigurable design optimization with the Machine Learning Optimizer (MLO) algorithm. The algorithm is based on surrogate model technology and particle swarm optimization. By using surrogate models the long hardware generation time is mitigated and automatic optimization is possible. For the first time, to the best of our knowledge, we show how those models can both predict when hardware generation will fail and how well will the design perform.
Second, we introduce a new algorithm called Automatic Reconfigurable Design Efficient Global Optimization (ARDEGO), which is based on the Efficient Global Optimization (EGO) algorithm. Compared to MLO, it supports parallelism and uses a simpler optimization loop. As the ARDEGO algorithm uses multiple optimization compute nodes, its optimization speed is greatly improved relative to MLO. Hardware generation time is random in nature, two similar configurations can take vastly different amount of time to generate making parallelization complicated. The novelty is efficient use of the optimization compute nodes achieved through extension of the asynchronous parallel EGO algorithm to constrained problems.
Third, we show how results of design synthesis and benchmarking can be reused when a design is ported to a different platform or when its code is revised. This is achieved through the new Auto-Transfer algorithm. A methodology to make the best use of available synthesis and benchmarking results is a novel contribution to design automation of reconfigurable systems.Open Acces
Optimising and evaluating designs for reconfigurable hardware
Growing demand for computational performance, and the rising cost for chip design and
manufacturing make reconfigurable hardware increasingly attractive for digital system implementation.
Reconfigurable hardware, such as field-programmable gate arrays (FPGAs),
can deliver performance through parallelism while also providing flexibility to enable
application builders to reconfigure them. However, reconfigurable systems, particularly
those involving run-time reconfiguration, are often developed in an ad-hoc manner. Such
an approach usually results in low designer productivity and can lead to inefficient designs.
This thesis covers three main achievements that address this situation. The first
achievement is a model that captures design parameters of reconfigurable hardware and
performance parameters of a given application domain. This model supports optimisations
for several design metrics such as performance, area, and power consumption. The second
achievement is a technique that enhances the relocatability of bitstreams for reconfigurable
devices, taking into account heterogeneous resources. This method increases the flexibility
of modules represented by these bitstreams while reducing configuration storage size and
design compilation time. The third achievement is a technique to characterise the power
consumption of FPGAs in different activity modes. This technique includes the evaluation
of standby power and dedicated low-power modes, which are crucial in meeting the
requirements for battery-based mobile devices