Design of Optimized FIR Filter Using FCSD Representation

Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

Design of Optimized FIR Filter Using FCSD Representation Neha Goel Ashutosh Nandi Dept. of Electronics and Comm. Engg. National Institute of Technology Kurukshetra, India nehagoel0392@gmail.com, ashutosh.chl@gmail.com

Abstract—This paper presents the design and implementation of an eight order efficient FIR filter for wireless communication system. In this work, factored canonical signed digit representation (FCSD) is used for representing the filter coefficients in order to reduce the design complexity, area and delay of the FIR filter. Complexity of the system has been reduced by replacing binary coefficients with FCSD representation. Further area and delay has been improved by replacing multiplication operation with add and shift method where carry save adder (CSA) is used for addition of two numbers and barrel shifter is used for shifting the data words.

Representation of coefficient in the FCSD format along with fastest adder and shifter improves the performance of the system.

FIR filter has been designed using an equiripple method in MATLAB and further synthesized on Spartan 3E XC3S500E target FPGA device. Simulation results show that optimized FCSD based FIR filter offers a less number of slices, look up tables (LUTs) and flip-flops as compared to CSD and conventional FCSD based FIR filter, in addition to enhanced performance.

Keywords— FIR Filter, CSA, Barrel shifter, FCSD. I.

INTRODUCTION

Digital FIR filter is one of the essential components in Digital Signal Processing (DSP) and communication system. With an explosive growth in mobile computing and multimedia applications, demand for low power and high speed DSP system has seen a tremendous growth [1]. Digital filters are used to modify the attributes of signal by removing noise from the original signal and shape the spectral characteristics of the resulting signal [2]. Digital filters are very superior in level of performance as they are highly stable, accurate and versatile as compared to analog filter [3]. Moreover, Portable applications require digital filter which operates at high data rate and low power consumption as high power consumption reduces battery lifetime, affecting device reliability and increasing cool cost [4]. Due to this reason, the requirement of a digital filter with optimized area, power and delay is a challenging task.

DSP applications require a large order FIR filter. However, the complexity increases with increase in filter order because of requirements of larger mathematical computations [5].

Therefore, real time implementation of this filter with precise value is posing as a serious challenge. In order to achieve efficient digital filter, order of FIR filter must be as small as possible. This paper focuses mainly on the FIR filter due to its absolute stability and linear phase response [6]. On the basis of hardware implementation, digital filter can be classified into two categories: multipliers based and memory based [7].

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Multipliers based design includes multiple constant multiplication (MCM) with add and shift operations.MCM based FIR filter uses transposed structure which increases the speed of the system.The area can be further saved by optimizing coefficient with quantization technique. Memory based design are divided into two approaches: distributed arithmetic (DA) and Look Up table (LUT) method. The DA based approach computes the inner product by accumulating bit level partial results in the FIR filter. The LUT based approach stores odd multiple of input signal in ROM to realize constant multiplications in MCM [7].

The main components of digital filter consist of registers to save the samples of signals, adders to carry out sum operations and multiplier for multiplication of the filter coefficients with signal samples [8]. Despite the fact that designing of digital filter seems simple, but the design bottleneck is its multiplier block for speed, area and power consumption [9]. Complexity is mainly dominated by coefficient multiplication operation [10,11]. In order to reduce complexity, the filter coefficients are represented in FCSD representation which requires the least number of adders [12]. The filter can be further optimized by using CSA and a barrel shifter to achieve the operation of multiplication [13].

The rest of the paper is organized as follows: an overview of FIR filter is given in section II. Section III consists of modules for FIR filter. Section IV describes the proposed work for filter optimization. In section V, simulation results are discussed. Finally, section VI concludes the paper by summarizing the main contributes.

II.

FIR FILTER

FIR filters are digital filter with finite impulse response which involves convolution operation given by equation [2]: Y[n] = X[n]*H [n]

(1)

FIR filter is also known as non-recursive digital filters as they don’t have feedback [6]. Output of the FIR filter can be described by the following difference equation

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Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

N 1

Y ( n)   H K x ( n  k )

(2)

k 0

Where N and Hk represents the length and coefficients of the FIR filter respectively [10].Basically FIR filter consists of two structures, i.e., direct form and transposed form. In direct form, signal samples are multiplied by filter coefficients and combined together in adder block [7]. A modification over direct form is transposed structure as shown in fig 1. In transposed form, the same input signal is multiplied by several coefficients. In the present work, transposed form is used which reduces area and delay as compared to direct form [6].

Fig.1. Transposed form of FIR filter

Fig.2. Lowpass FIR filter magnitude response

Digital filter can be designed by calculating the filter coefficient on the basis of filter order, sampling frequency, pass band and stop band frequencies etc.[5]. Generally, power consumption and the amount of computation are directly proportional to filter order. Filter coefficient can be found with the MATLAB FDA tool. Further, the filter can be designed by different method including window functions, frequency sampling and equiripple method [9]. Table I lists the parameters of the low pass FIR filter and the corresponding magnitude response is shown in Fig. 2.

TABLE I. FIR Filter Design Parameter Filter Parameter

Value

Design method

Equiripple

Order

8

Density factor

20

Sampling frequency

FS = 48000 Hz

Passband frequency

Fpass = 9600Hz

Stopband frequency

Fstop = 12000Hz

Passband weight

Wpass = 1

Stopband weight

Wstop = 1

The calculated coefficients of the proposed FIR filter are [9, 16, 17, 32, 33, 32, 17, 16, 9]. Coefficients are symmetric in nature which further reduces area and power consumption [5].

Order for FIR filter is N while the length of the filter is N+1 which is similar to the number of the filter coefficients [10].

As the filter order increases, complexity of the system increases by consuming more amount of time for signal processing.

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III. MODULES FOR FIR FILTER Three modules are needed for implementation of optimized FIR filter, i.e., delay, addition and multiplication. Barrel shifter is used to provide shift operation and CSA is used to carry out a sum operation. The modules used for implementation are:

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A. Carry Save Adder CSA is mainly used for fast arithmetic in a DSP system for addition of three or more binary numbers. In CSA, there is no propagation delay as compared to the ripple carry adder and carry look ahead adder [4]. For sufficient large value of n, it provides results very quickly and relatively occupies less area in comparison to normal adders. CSA includes full adders but the carry output is taken out from each bit to form second result vector instead of passing it to the next most significant bit [8]. It consists of three numbers (x, y, z) as the input which is added together and provides sum (s) and carry (c) as an output. Hence, this adder is called as 3:2 compressor, where the operation is performed in one time unit duration. In carry save operation, the carry is passed until last step whereas ordinary addition is done in the last step only. When CSA is implemented on FPGA, then two LUTs are required for generation of carry and sum bit where as single LUT is required for the carry propagation adder [11]. Fig.3 represents CSA that consists of 17 half adders and 15 full adders.

B. Barrel Shiifter Barrel shifter is an integral component in several computing devices which is mainly used for shifting and rotating multiple bits in a single clock. It can be designed with the help of combinational logic circuits such as logic gates, multiplexers and decoders. However, the MUX based barrel shifter provides less delay and power when compared to other circuits [13]. Therefore, in the present work, BS is designed using multiplexers architecture. Shifting a data word by a specific amount of shift is performed in one clock cycle.

Sequences of multiplexers are used to implement the barrel shifter and the output of one mux is connected to the input of the next mux that depends on the shift distance [7]. The data word can be shifted up to 8 bits either in left or right direction.

If the input pin is zero, then the observed output remains same, i.e., without applying shifting operation. On the other hand,

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Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

if the input is non zero, then output is shifted in either specified direction. After shifting operation, all the partial products (PP) are added together to achieve multiplication operation. Thus, Performance of FIR filter is improved by use of barrel shifter in terms of area and delay [13].

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

representation reduces the area of the filter as compared to the CSD technique, but with the disadvantage of increased delay.

This propagation delay can be improved by using CSA and a barrel shifter. For multiplication of filter coefficients with the input signal add and shift method is used. Therefore, the multiplier consists of one adder unit (CSA) and one shifter unit (barrel shifter). The filter is processed step by step in which coefficients are first factored and subsequently represented in CSD format. CSA is used, when the input signal is multiplied with filter coefficients and added together in the last step. Optimization of FIR Filter considering area and delay constraints has been achieved using FCSD representation, CSA and barrel shifter. These combinations of FCSD technique with CSA and BS can target significant reduction in circuit complexity, area and delay.

V.

Fig.3. Block diagram for 16-bit Carry Save Adder

C. Conventional FCSD Factored Canonical Signed Digit representation is a slight modification over CSD. It replaces multiplier operation with add and shift operations on the basis of prime factors of the coefficients [9]. A combination of effective factorization and CSD representation of filter coefficient leads to a reduction in the number of adders which further hardware cost. It provides a relatively greater reduction in filter area, but at the cost of decreased clock speed [9].Increase in delay is the major drawback of this algorithm. The Factored CSD algorithm provides a trade-off between calculated complexity and convergence [12]. Following example compares CSD and FCSD algorithm. y = 217*x = (11011001)*x % 217 in binary form = (1001’001’1’1’) *x % 217 in signed digit = (256- 32-4-2-1) * x = (x << 8) –(x << 5) – (x << 2) – (x << 1) – x Cost of CSD = 4 adders y = 217*x = (7*31)* x = (x << 3– x) *(x << 5 – x) Cost of FCSD = 2 adders It is concluded that, the number of adders has been reduced by using FCSD instead of CSD technique. Therefore, we have used FCSD formulation for reducing filter complexity.

IV.

PROPOSED WORK FOR OPTIMIZED FIR FILTER

FIR filter based on FCSD technique is proposed that use carry save adder and barrel shifter for addition and shifting operations. FCSD technique used for coefficient

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SIMULATION RESULTS

This section presents the simulation results of the proposed FIR filter. A Low pass FIR Filter is designed using equiripple method in MATLAB FDA tool box for calculation of coefficients. The filter can be designed in two structures, i.e. direct form and transposed form. We have used transposed form structure which reduces the implementation cost in terms of area and delay. FIR filter architecture has been designed and implemented on Xilinx Spartan3E XC3S500E using VHDL. This results in realizing an FIR filter which can be operated at maximum frequency of 238.322 MHz by consuming 79 slices. The characteristics of proposed FPGA based FIR filter are summarized in table II along with the comparison of the proposed filter with CSD and FCSD technique.

TABLE II: Performance Comparison between different approaches Parameter

CSD

FCSD

No. of slices

808

789

Proposed work 79

No. of flip-flops

510

512

126

No. of 4 input LUT’s Frequency (MHz)

1349

1290

146

43.814

44.911

238.322

Min. Period (ns)

22.824

22.266

4.196

As shown in table II, Number of slices has been reduced from 789 to 79 in FCSD technique by consuming 126 numbers of flipflops. Proposed FCSD based FIR filter occupies 146 number of look up tables as compared to FCSD technique. In comparison to FCSD, this result shows the enhanced performance in terms of speed and area due to efficient utilization of embedded multiplier and LUTs inside the device. Fig. 4 compares the proposed FCSD technique with CSD and FCSD method in the form of bar graph. The proposed work offers very less number of slices, LUTs and flipflops as compared to other two techniques generated by MATLAB. Simulation results shows that proposed filter consumes 89.98% less number of slices, 88.682% less number of LUTs and 75.39 % less number of flipflops as compared to FCSD technique to provide cost effective filter. Time delay of

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Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

the proposed filter has been improved considerably which in turn increases the operational speed of the system. This reduction in design complexity, area and delay of proposed FCSD based filter can be viewed as a possible alternative for circuit designer.

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

concluded that, use of FCSD representation in FIR filters along with fastest adder and shifter can target significant reduction in design complexity, area and delay when compared to other approaches.

REFERENCES [1]

1200

[2] [3]

800 [4]

400 [5]

0 slices

flip-flops

CSD

FCSD

LUT’s

[6]

Frequency (MHz)

Proposed work

Fig.4. Bar graph representing CSD, FCSD and proposed work comparison

VI.

[8]

[9] [10]

CONCLUSION

The proposed FIR filter has been designed for 8 tap using FCSD representation of filter coefficients. An optimized FIR filter has been designed using barrel shifter and CSA in VHDL which is further simulated on Xilinx Spartan3E based XC3S500E target FPGA device. The results show that optimized FCSD based FIR filter can be operated at a maximum frequency of 238.322 MHz by consuming 79 slices, 126 flip-flops and 146 LUTs. Simulation results shows that optimized filter occupies 89.98% less number of slices, 88.682% less number of LUTs and 75.39 % less number of flipflops as compared to FCSD technique. Delay of the optimized FIR filter has been reduced by 18.071 ns. It is

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[7]

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[11]

[12]

[13]

D. L. Maskell, “ Design of Efficient Multiplierless FIR filters,” IET Circuits Device System, vol.1, no. 2, pp. 175-180, May 2007.

M. D. Cilletti, Advance Digital Design with Verilog HDL, PHI learning, first edition, 2003.

A. Nandi, A. K. Saxena and S. Dasgupta, “Design and Analysis of Analog Performance of Dual-k Spacer Based Underlap N/P-FinFET at 12nm Gate Length,” IEEE Trans. on Electron Devices, vol. 60, no. 5, pp. 1529-1535, May 2013.

R. Mahesh and A. P. Vinod,“A New Common Subexpression Elimination Algorithm for Realizing Low Complexity Higher Order Digital Filters,” IEEE Trans. On Computer Aided Design of Integreted Circuits and Sytems, vol. 27, no. 2, pp. 217-229, Feb. 2008.

L. Wu, Y. Cui and J. Huang, “Design and Implemenation of an Optimized FIR Filter for IF GPS Signal Simulator,” IEEE conf. on Microelectronics and Electronics, pp. 25-28, Sept. 2010.

J. Proakis and D. Manolakis, Digital Signal Processing, fourth edition, 2008.

S. F. Hsiao and J. H. Z. Jian, “ Low Cost FIR Filter Designs Based on Faithfully Rounded Truncated Multiple Constant Multiplications,” IEEE Trans. on Circuits and Systems-II: Expression Briefs, vol. 60, no. 5, pp.

287-291, May 2013.

J. Um and T. Kim, “An Optimal Allocation of Carry Save Adders in Arithmetic Circuits, ” IIEEE Trans. on computer, vol. 50, no. 3, pp. 215230, Mar. 2001.

Mathworks, User Guide Filter Design Toolbox,Version-2, 2007.

L. Litwin, “ FIR and IIR Digital Filters,” IEEE Potentials, vol. 19, no. 4, pp. 28–31, Oct. i2000.

L. Aksoy, E. Costa, P. Flores and J. Monteiro, “ Exact and Approximate Algorithms for the Optimization of Area and Delay in Multiple Constant Multiplications”, IEEE Trans. on Comp. Aided Design of Integreted Circuits and Sytems, vol. 27, no. 6, pp. 1013-1026, iJune 2008.

K. Priya and R. Mehra, “ FPGA Based Cost Efficient FIR Filter Using Factored CSD technique ,” International iJournal of Recent Technology and Engineering,vol. 6, issue 6, pp. 130-134, Jan. 2013.

R. Rajalakshmi and P. ArunaPriya, “ Design and Analysis of A 4-Bit Low Power Universal Barrel-Shifter in 16nm FINFET Technology,” IEEE International Conference on Advanced Communication Control and Computing Technologies, pp. 527-532, May 2014.

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