LCMV algorithm is a common-used anti-jamming method for GPS navigation. It requires the complex computation of matrix inversion. In this paper, an improved method for complex matrix inversion based on Gaussian elimina...
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ISBN:
(纸本)9781467381956
LCMV algorithm is a common-used anti-jamming method for GPS navigation. It requires the complex computation of matrix inversion. In this paper, an improved method for complex matrix inversion based on Gaussian elimination is given. The combination of C and assembly language program design process of improved algorithm based on Digital signal Processor hardware platform is developed. Experimental results show that the time consumption of improved complex matrix inversion method based on Gaussian elimination is the least, compared to the method of the original complex inversion based on Gaussian elimination and the method of the traditional direct matrix inversion.
Periodic characteristics arise in many communications scenarios. Two major examples are interference-limited communications and power line communications. The most general point-to-point periodic channel model include...
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ISBN:
(纸本)9781509017508
Periodic characteristics arise in many communications scenarios. Two major examples are interference-limited communications and power line communications. The most general point-to-point periodic channel model includes periodic variations of the channel transfer function and of the noise statistics. In this work we study carrier frequency offset estimation for linear channels with periodic characteristics. We design a maximum likelihood estimator (MLE), analytically characterize its asymptotic performance, and provide guidelines for its low-complexity implementation. We compare the strengths and weaknesses of the new estimator to those of an ad-hoc extended estimator obtained by adapting an MLE, originally designed for time-invariant channels, to periodically time-varying channels via a time partitioning approach. We numerically evaluate the performance of the new estimator and of the ad-hoc estimator, and illustrate the gain of rigorously accounting for the periodic characteristics of the channel, as opposed to the currently prevailing ad-hoc approach.
The oil debris sensor has been widely used in the fault detection of mechanical equipments. However, some key parameters used in the sensor have not been solved in theory, such as the estimation of solenoid coil turns...
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ISBN:
(纸本)9781467396042
The oil debris sensor has been widely used in the fault detection of mechanical equipments. However, some key parameters used in the sensor have not been solved in theory, such as the estimation of solenoid coil turns. A new method to optimally determine the coil turns is proposed in this work. In addition, the circuits system for detecting debris and sensing signals have been also developed. Experiments for detecting micro debris by using the designed sensor system well demonstrate its effectiveness.
Dataflow models of computation are widely used for modeling signalprocessingsystems. These models have inherent concurrency and the task (actor) execution depends only on the availability of the input data (tokens)....
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ISBN:
(纸本)9781467396042
Dataflow models of computation are widely used for modeling signalprocessingsystems. These models have inherent concurrency and the task (actor) execution depends only on the availability of the input data (tokens). This property of dataflow models can be exploited for dynamic power management by automatically switching off the actors with no available input tokens. This idea is applied in this paper for efficient modeling and implementation of an adaptive Digital Predistortion (DPD) filter. The DPD filter is required to operate with different profiles under varying operation scenarios, hence requiring a methodology to manage power dynamically. The paper presents a dataflow model for Adaptive Digital Predistortion based on the Core Functional Dataflow (CFDF) model of computation using the Light Weight Dataflow (LWDF) programming methodology. The paper also provides a methodology for dynamic power management under the dataflow paradigm. To the authors' best knowledge, this work is the first to integrate dataflow-based power management systematically in the context of adaptive DPD implementation.
This paper describes the simulation results and hardware implementation of an inexpensive, low-complexity LED based indoor positioning system. Localization by multiple LEDs estimation model (MLEM) approximates positio...
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ISBN:
(纸本)9781509017508
This paper describes the simulation results and hardware implementation of an inexpensive, low-complexity LED based indoor positioning system. Localization by multiple LEDs estimation model (MLEM) approximates position of a mobile receiver by the acquisition of positional information from LED transmitters. Multiple LED orientation can either be with or without overlap. Receivers in a no-overlap LED orientation experience only single access while multiple access receivers are designed for orientations with overlaps. Single and multiple access systems were developed and implemented by the use of low cost ATMEG 328 microcontroller. Since multiple LEDs transmit data at the same wavelength and are asynchronous, overlap in multiple access system causes interference. The possibility of this interference is reduced by packet based pulse duration multiplexing (PDM) and a low duty cycle transmission protocol. By the use of MLEM, root mean square error in position estimation is reduced to about 1 percent of the length an indoor location. Experimental results show that overlap increases positional accuracy over a wider coverage region and that the multiple access system allows for a more reliable positioning.
In this paper, an implementation of turbo equalization using cyclic prefix in LTE downlink system is proposed. In comparison with conventional equalization schemes, the using of cyclic prefix can enhance the SNR perfo...
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ISBN:
(纸本)9781467396042
In this paper, an implementation of turbo equalization using cyclic prefix in LTE downlink system is proposed. In comparison with conventional equalization schemes, the using of cyclic prefix can enhance the SNR performance by about 1 dB in AWGN channel and more in multi-path channel with Doppler frequency influence [3]. In this paper, the turbo equalizer presented in [3] is extended to 16QAM and 64QAM to support LTE system. Furthermore turbo encoder and decoder, scrambler and interleaver are designed according to the demands of LTE standard. The simulation results show that the algorithms can achieve ideal performance enhancement in LTE system comparing to conventional schemes.
In this paper, we propose a low-complexity decoding message truncation technique for nonbinary LDPC decoders by exploiting the extended min-sum algorithm. The proposed technique dynamically adjusts the decoding messag...
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ISBN:
(纸本)9781467396042
In this paper, we propose a low-complexity decoding message truncation technique for nonbinary LDPC decoders by exploiting the extended min-sum algorithm. The proposed technique dynamically adjusts the decoding message length according to channel conditions, thereby reducing the decoding complexity while conforming to the desired level of decoding performance. Utilizing the proposed technique, the decoding operations as well as the power consumption of the non-binary LDPC decoder can be greatly reduced. Simulation results demonstrate that the proposed technique can achieve a better power-performance tradeoff over conventional techniques.
In modern wireless communication systems, the adaptive digital predistortion (DPD) is widely used to compensate for the nonlinearity in the radio front-end. In the DPD implementation, the conventional coefficient esti...
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ISBN:
(纸本)9781467396042
In modern wireless communication systems, the adaptive digital predistortion (DPD) is widely used to compensate for the nonlinearity in the radio front-end. In the DPD implementation, the conventional coefficient estimation algorithm is computationally intensive and prevents the application of complex DPD models. In [1], we have derived an efficient coefficients estimation algorithm based on orthonormal basis functions that achieves the low computational complexity while maintaining the estimation accuracy. In this paper, we focus on the implementation of this efficient coefficients estimation algorithm on a field programmable gate array (FPGA) platform. Compared with the conventional recursive least squares (RLS) algorithm, the low complexity algorithm can achieve the same linearization performance while saving about 80% hardware resources.
The interest towards programming of streaming applications using dataflow models of computation has been increasing steadily in the recent years. Among the numerous dataflow formalisms, the ISO-standardized RVC-CAL da...
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ISBN:
(纸本)9781467396042
The interest towards programming of streaming applications using dataflow models of computation has been increasing steadily in the recent years. Among the numerous dataflow formalisms, the ISO-standardized RVC-CAL dataflow language has offered a solid basis for programming tool development and research. To this date RVC-CAL programming tools have enabled transforming dataflow programs into concurrent executables for multicore processors, as well as for generating synthesizable hardware descriptions. In this paper it is shown how the RVC-CAL dataflow language can be used for programming graphics processing units (GPUs) with high efficiency. Considering the processing architectures of recent mobile and desktop computing devices, this advance is of high importance, as most consumer devices contain a graphics processing unit nowadays. To evaluate the proposed solution, the paper presents a video processing application case study. At best, the solution is shown to provide a speedup of 42x over single-threaded CPU execution.
We implement a binocular vision system based on a disparity-energy model that emulates the hierarchical multilayered neural structure in the primary visual cortex. Layer 1 performs difference-of-Gaussian filtering tha...
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ISBN:
(纸本)9781467396042
We implement a binocular vision system based on a disparity-energy model that emulates the hierarchical multilayered neural structure in the primary visual cortex. Layer 1 performs difference-of-Gaussian filtering that mimicks the center-surround receptive fields (RF) in the retina, layer 2 performs Gabor filtering mimicking the orientation selective filtering performed by simple cells and layer 3 has complex cells tuned to detecting 5 different disparities. A VLSI architecture is developed based on stochastic computing that is compact and adder-free. Even with a short stream length, the proposed architecture achieves better disparity detection than a floating-point version by using a modified disparity-energy model. A 1 x 100 pixel processing system is synthesized using TSMC 65nm CMOS technology and achieves up to 79% reduction in area-delay product compared to a fixed point implementation.
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