A Hardware Intensive Approach for Efficient Implementation of Numerical Integration for FPGA Platforms

Khurshid, Burhan; Mir, Roohie Naz

doi:10.1109/vlsid.2014.60

Cited by 9 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is rather challenging to directly deal with the Eq. ( 7) due to the presence of complicated integral [28]. Thus, the estimation algorithms, such as MLE and EM with MLE, are time-consuming to accomplish for engineering applications in practical.…”

Section: System and Channel Modelmentioning

confidence: 99%

Parameter Estimation of Gamma‐Gamma Fading with Generalized Pointing Errors in FSO Systems

Miao

Cai

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In this paper, the challenges of parameter estimation for the Gamma-Gamma turbulence channels with generalized pointing errors are addressed. The Kolmogorov-Smirnov goodness-of-fit statistical test results indicate that the approximate probability density function obtained by the saddlepoint approximation (SAP) method provides a better approximation for a larger value w z , and this means that the proposed method is more efficient for the FSO links over long distances when the transmit divergence angle at the transmitter side is fixed. Also, an additional parameter k needs to be estimated in addition to the shaping parameters α and β under the SAP method. An estimation scheme for the shaping parameters is proposed based on the SAP method. The performance of the proposed estimation is investigated by using the mean square error (MSE) and normalized mean square error (NMSE). The results indicate the proposed estimator exhibits satisfactory performance in both noiseless and noisy environments. The effects of the receiver aperture on the estimation performance are also discussed.

show abstract

Section: System and Channel Modelmentioning

confidence: 99%

Parameter Estimation of Gamma‐Gamma Fading with Generalized Pointing Errors in FSO Systems

Miao

Cai

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…Furthermore, we show a qualitative comparison of the three types of estimation algorithms for the noiseless situation in Table 1. Note that evaluating moments also involves the computation of the complicated integrals that are time-consuming to accomplish for hardware implementation [30], [31].…”

Section: (16)mentioning

confidence: 99%

Parameter Estimation of the Lognormal-Rician Channel Model Using Saddlepoint Approximation

Miao

2020

IEEE Access

View full text Add to dashboard Cite

In this paper, the challenges of effective channel estimation for the lognormal-Rician turbulence model are addressed. We present a novel maximum likelihood estimation algorithm involving a saddlepoint approximation (SAP) method to estimate the shaping parameters of the lognormal-Rician distribution. An additional parameter k needs to be estimated in addition to r and σ 2 z under the SAP representation. The accuracy of the proposed estimator is investigated by using the mean square error and normalized mean square error. The simulated results show that the proposed estimator exhibits satisfactory performance over a wide range of turbulence conditions, and it can be easily applied to both noiseless and noisy situations. The effect of the estimated shaping parameters errors on the bit error rate (BER) for the on-off key (OOK) modulation is also investigated; it is shown that the BER performance derived with the SAP estimator becomes closer to the system performance with perfect shaping parameters as r increases. In particular, we present a qualitative comparison between the proposed SAP estimator and other algorithms available in the literature. INDEX TERMS Maximum likelihood estimation (MLE), SAP method, lognormal-Rician turbulence model, OOK modulation, qualitative comparison. I. INTRODUCTION Free space optical (FSO) communication, also known as outdoor optical wireless communication, has recently experienced extraordinary advances. High-speed data transmission can be provided by FSO communication in terms of its large available bandwidth. In addition, there are additional advantages of FSO communication over radio frequency (RF) communication including easy deployment, greater security, and unregulated spectrum resources [1]. Moreover, FSO communication has been intensively considered as a complementary technology to the RF communication in many application scenarios, which is known as hybrid (RF-FSO) communication [2]-[5]. Nevertheless, the performance of FSO links can be severely degraded by environment effects such as aerosol scattering, building-sway, and turbulenceinduced scintillation. Hence, in order to improve the reliable operation of FSO systems under a wide range of weather conditions, various types of processing techniques have been proposed to mitigate the adverse effects of the atmosphere (e.g., [6]-[9]). Many statistical models have been proposed to character

show abstract

“…In order to achieve a better performance in implement numerical integration and since the high speed and accurate arithmetic is absolutely essential, the hardware oriented solution is developed upon the setback trending [1].…”

Section: Introductionmentioning

confidence: 99%

High speed numerical integration algorithm using FPGA

Razak¹,

Talip²,

Yakub³

et al. 2018

J. Fundam and Appl Sci.

View full text Add to dashboard Cite

Conventionally, numerical integration to accomplish. Field Programmable Gate Arrays (FPGAs) can be used as a efficient and reliable alternative to implement the proposed a hardware implementation of four numerical integration algorithms using FPGA. The computation is based on Left Riemann Sum (LRS), Right Riemann Sum (RRS), MiddleRiemann Sum (MRS) and Trapezoidal Sum (TS) algorithms. The system performance is evaluated based on target chip Altera Cyclone IV FPGA in the metrics of resources utilization, clock latency, execution time, power consumption and computational error compared to the other algorithms. The result also shows execution time of the FPGA are much faster compared to the software implementation.

show abstract

A Hardware Intensive Approach for Efficient Implementation of Numerical Integration for FPGA Platforms

Cited by 9 publications

References 16 publications

Parameter Estimation of Gamma‐Gamma Fading with Generalized Pointing Errors in FSO Systems

Parameter Estimation of Gamma‐Gamma Fading with Generalized Pointing Errors in FSO Systems

Parameter Estimation of the Lognormal-Rician Channel Model Using Saddlepoint Approximation

High speed numerical integration algorithm using FPGA

Contact Info

Product

Resources

About