Efficient Implementation of Multiplier for Digital FIR Filters

DOI : 10.17577/IJERTCONV3IS01019

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Efficient Implementation of Multiplier for Digital FIR Filters

Smitha N Mallya

Department of Electronics & Telecommunication FCRIT, Vashi

Navi Mumbai, Maharashtra, India


Department of Electronics & Telecommunication FCRIT, Vashi

Navi Mumbai, Maharashtra, India

AbstractThis paper presents amethodfor implementing the multipliers for digital filters that requires optimized area and low power consumption. Multiplication plays a vital role in most of the high performance systems. By reducing the delay taken for calculations of results one can speed up the system performance.The methods include Modified Booth Encoding Algorithm along with carry selectadder. Comparative study is done between shift/add multiplier, Radix-2, Radix 4 encoded booth multiplier, Radix-4 with Carry select adder. These techniques are applied to filters to minimize the area and speed up the performance. The proposed designs aredesigned using Verilog HDL and synthesized, implemented using Xilinx ISE.

KeyTermsMultiplier, BoothsAlgorithm, Modified Booths Algorithm, Xilinx ISE, FPGA.


Finite impulse response (FIR) filters are widely used in various DSP applications. Few applications, will be such that the FIR filter circuit must be able to operate at high sample rates, while in other applications, the FIR filter circuit must act as a low-power circuit that operates at moderate sample rates. Hence major factor that affects the designing is the structure of the multiplier circuit. It also affects the resultant power consumption and speed. Thus Choosinga multiplier with more hardware breadth rather than depth would not only reduce the delay, but also the total power consumption. A lot of design methods of low power digital filter have beenproposed. They use a modified common sub expression elimination algorithm to reduce the number of adders used in the multiplication operation.

Multiplication is a most commonly used operation in many computing systems. In fact multiplication is nothing but repetitive addition since, multiplicand adds to itself multiplier number of times gives the multiplication value between multiplier and multiplicand. But the facts that this kind of implementation shall take many hardware resources and make the circuit operate at utterly low speed. In order to address this issue so many ideas have been presented so far for the last three decades. Each one is aimed at a particular improvement according to the requirement. One may be aimed at high clock speeds and another may be aimed for low power consumption or less area occupation[1], [2]. Either way ultimate job is to come up

with an efficient architecture which can address three constraints of VLSI speed, area, and power. Among these three, speed is the one

whichrequires most important and special attention.On observing closely, multiplication operation involves two major steps: one is producing partial products and other is adding these partial products. Thus, the speed of a multiplier hardly depends on how fast the partial products are generated and how fast we can add them together. If the numbers of partial products to be generated are less then it is indirectly means that we have achieved the speed in generating partial products. Booths algorithmis meant for achieving speed.To speed up the addition operation among the partial products, we need fast adder architectures. Since the multipliers have a significant impact on the performance of the entire system, one such high performance algorithms and architectures have been proposed by RenukaNarasimha, Rajasekhar and Sujana Rani [3].

The section II give a brief summary of FIR filter theory, section III presents FIR implementation which discusses the different multiplication architectures. Section IV discusses on simulation results. Section Vis conclusion drawn between different multipliers and future work to be carried.


    Digital filters are main components that are usually used to modify or alter the attributes of a signal in the time or frequency domain. The linear time-invariant (LTI) filter isthe most common digital filter.Interaction of an LTI system with input signal through a process called linear convolution, denoted by y = f * x where f is the filters impulseresponse, x is the input signal, and y is the convolved output. The linear convolution process is formally defined by:



    Y[n] = x[n] * f[n] = 1 x[n]f [n k]

    = k=0 f[k]x [n-k] (1)

    LTI digital filters are generally classified as being finite impulse response (i.e., FIR), or infinite impulse response (i.e., IIR). An FIR filter is a filter whose impulse response settles to zero in finite time. An IIR filters may have an internal feedback and continue to respond indefinitely. As the name implies, an FIR filter consists of a finite number

    of sample values, reducing the above convolution sum to a finite sum per output sample instant. An FIR with constant coefficients is an LTI digital filter. The output of an FIR of order or length L, to an input time-series x[n], is given by a finite version of the convolution sum given in Eq(1), namely:


    where f[0] 0 through f[L-1] 0 are the filters L coefficients. They also correspond to the FIRs impulse response.For LTI systems it is sometimes more convenient to express in the z-domain with

    Y(z) = F(z) X(z) (3)

    Where F (z) is the FIRs transfer function defined in the z-domain by


    The Lth-order LTI FIR filter is usually interpreted in Figure.1. It comprises of large number of a tapped delay

    line, adders, and multipliers. One of the operands given to each multiplier is an FIR filter coefficient, often named as a tap weight.

    The FIR filter with transposed structure Figure.1 has registers between the adders and can achieve high throughput without adding any extra pineline registers.

    product. Each step of addition generates a partial product. In most computers, the operand usually contains the same number of bits. When the operands are interpreted as integers, the product is generally twice the length of operands in order to preserve the information content. This repeated addition method that is suggested by the arithmetic definition is slow. It is almost always replaced by an algorithm that makes use of positional representation. It is possible to decompose multipliers into two parts. The first part is dedicated to the generation of partial products, and the second one collects and adds them. The basic multiplication principle is twofold i.e., evaluation of partial products and accumulation of the shifted partial products. It is performed by the successive additions of the columns of the shifted partial product matrix. The multiplier is successfully shifted and gates the appropriate bit of the multiplicand. The delayed, gated instance of the multiplicand must all be in the same column of the shifted partial product matrix. They are then added to form the final product. For high-speed multiplication, there are some of the methods discussed in this paper.

    A. Shift and Add Multiplier

    In this section we present a simple Shift and Add structure for multiplier used in filters [4]. Multiplication is performed by generating partial products and shifting the multiplicand left by one bit after every partial product calculation. The partial product of the current stage is set to the sum of the previous partial product and the shifted multiplicand of the current stage or 0, depending on whether the multiplier bit in the current stage is 1 or 0.

    Refeence Model: Shift-and-Add for 3-bit operands Stage 1.

    Figure 1: FIR filter in the transposed structure



    Stage 2.

    Stage 3.

    Rule a: product = product + mcand if(y [0]) Rule b: product = product + 0 if (! y [0])

    Rule a: product = product + mcand<<1 if(y [1]) Rule b: product = product + 0 if (! y [1])

    The multiplier is one of the essential elements of the digital signal processing such as filtering, convolution, and inner products. Most digital signal processing methods use nonlinear functions such as discrete cosine transform (DCT) or discrete wavelet transform (DWT). Because they involve repetitive application of multiplication and addition, the speed of the multiplication and addition determines the execution speed and performance of the entire calculation. Because the multiplier requires the longest delay among the basic operational blocks in digital system, the critical path is determined by the multiplier, in general.

    Fast multipliers are an important part of digital signal processing systems. The speed of multiply operation is of great importance in digital signal processing as well as in the general purpose processors today. In the past, multiplication was generally implemented via a sequence of addition, subtraction, and shift operations. Multiplication can be considered as a series of repeated additions. The number to be added is the multiplicand, the number of times that it is added is the multiplier, and the result is the

    Rule a: product = product + mcand<<2 if(y [2]) Rule b: product = product + 0 if (! y [2]).

    The same procedure is followed for n-bit multiplication.In this paper we have proposed a 4 bit shift and Add multiplier.

      1. odified Booth Multiplier

        In order to achieve high-speed for multiplication, modified Booth algorithm has been presented in this section. Booth multiplication is a technique that allows for smaller, faster multiplication circuits, by recoding the numbers that are to be multiplied[7]. It is possible to reduce the number of partial products by half, by using the technique of radix-4 Booth recoding. The basic idea is that, instead of shifting and adding for every column of the multiplier term and multiplying by 1 or 0, we only take every second column, and multiply by ±1, ±2, or 0, to obtain the same results. The advantage of this method is the halving of the number of partial products. Booth's multiplication algorithm is a multiplication algorithm that

        multiplies two signed binary numbers in two's complement notation.

        1. Radix-2 Multiplication

          The simple multiplication generator can be used to reduce the number of partial products by grouping the bits of the multiplier into pairs, and selecting the partial products from the set 0, +-M, where M is the multiplicand. Here the multiplier is grouped into two bits. Each encoded digit performs some operation on the multiplicand generating the partial product with the help of the selection Table 1. Each partial product is shifted one bit position to the left with respect to its neighbors. These partial products are then added to obtain the final product.

          Table 1: Partial product selection table for radix 2

          Multiplier bits










        2. Radix -4 Multiplication

          The Radix-4ModifiedBoothsAlgorithmreduces the number of partial products by about a factor of two. This selects the partial products from the set of 0, +-M, +- 2M,where M is the multiplicand.The multiplier is appended by a 0 on LSB; we will call this bit as Z. The multiplier is partitioned into overlapping groups of 3 bits, and each group is decoded to select a single partial product as per the selection Table 2. Each partial product is shifted 2 bit positions with respect to its neighbors. The number of partial products will be reduced from 16 to 9 for a 16X16 multiplication. In general the there will be (n+2)/2 partial products, where n is the operand length.

          Table 2: Partial product selection table for radix 4

          Multiplier bits


















          Figure 2: Recoding of multiplier

          Each block is decoded to generate the correct partial product. The encoding of the multiplier Y, using the modified booth algorithm, generates the following five signed digits, -2, -1, 0, +1, +2. Each encoded digit in the multiplier performs a certain operation on the multiplicand as illustrated in the Table 2.

          The modified Booths algorithm (radix-4 recoding) starts by appending a zero to the right of x0 (multiplier

          LSB). Triplets, group of three bits are taken beginning at position x 1 and continuing to the MSB with one bit overlapping between adjacent triplet group. If the number of bits in the multiplier (excluding x 1) is odd, the sign (MSB) is extended one position to ensure that the last triplet contains 3 bits. In every step we will get a signed digit that will multiply the multiplicand to generate a partial product entering the Carry selectadder.ss

          Proposed Architecture for Multiplication

          Figure 3: Architecture for Booth Multiplication

          The multiplier is designed so that it can take two n-bit inputs: the multiplier (MR) and the multiplicand (MD), and results in producing the 2n-bit multiplication result of the two as its output. The architecture of the booth multiplier primarily consists of four major modules as shown in Fig.3. They are: 2's Complement Generator, Booth Encoder, Partial Product Generator and Carry Select Adder. The multiplier has been constructed in its simplest conceptual form.We will be using original Booth's Algorithm (Radix 4 encoding) for the Booth Encoder[4]. The 2's Complement Generator is used to generate the twos complementof the multiplicand.The 2's Complement Generator takes the multiplicand (MD) as its input and produces -MD as its output. 2's complement is required when recoded multiplier bit signifies negative multiplication.2's complement is generated by inverting all bits of the multiplicand and then adding 1 using a ripple carry adder. The Partial Product Generator uses two control signals x and z produced by the Booth Encoder and uses these signals to choose from and extend signs of '0', MD,-MD,2MD or -2MD for creating partial products. There will be n/2 partial products if n is even, (n+1)/2 partial products, if n is odd. The final intermediate results are added using a Carry Select Adder. Carry select Adder (CSA) adds two numbers with very lower latency.The carry Select adder will avoid the unwanted addition and thus minimize the switching power dissipation.


    The multiplier is designed using Verilog HDL and simulated using Xilinx ISE. The Fig.4 below shows the simulation result for 4-bit Shift and Add Multiplier. Fig.5. shows the simulation result of a radix-2 booth multiplication taking two 16 bit inputs.

    Figure 4: Simulation result of Shift and Add Method

    Figure above gives the output of multiplier that does multiplication by using normal shifting and adding the partial products. Here multiplier an multiplicand is 8 and out put is displayed as 4.


    Figure 5: Simulation result of Radix2 Booth Multiplication

    Figure shows the multiplication done by usig radix 2 encoded multiplier where grouping of two bits are done of multiplier. Input bits are taken here as 12 and 8 and product 96 is displayed.

    Figure 6: Simulation result of Radix 4 Booth Multiplication with CSA

          1. Comparison

    By comparing the time taken for computing the final product calculation by various methods, a clear picture that the number of partial products in Radix 4 is less as compared to Radix 2. Hence Radix 4 architecture is faster than Radix2 .It is clear that Radix 4 requires less number of transistor switching and reduces power consumption. The timing table displayed below is from the timing summary report that will be generated when running the simulation. The delay mentioned is the time taken by various methods to calculate the final product that is it includes the time taken for generation of partial products and its addition by using the adder architecture.

    Table 3: Comparative Table of various methods

    Multiplication methods

    Delay (ns)

    Shift and Add


    Radix 2


    Radix 4


    Radix 4 with Carry Select Adder


    Device utilization summarygives the picture of the LUTs and slices used by the multiplier which estimates the area used by the multiplierAs an example, summary of radix 2 multiplier is shown in figure below

    Figure 7: Device utilization summary of Radix 2 Multiplier


In this paper weare presenting anefficient architecture for multiplier.For reducing power consumption we are using Modified Booth Encoding Algorithm.The above multiplication techniques presented inthis paper result in the reduction of the number of partial products, as the number of partial products reduce the time taken by adder to calculate the final product will be greatly reduced contributing in high speed multiplication.As the number of transistorswitching will be less, the total power consumption will also be reduced leading to efficient implementation of multiplier. Hence it can be concluded that Radix4 is faster compared to Radix2 and normal shift add multiplierand hencecan be used in high speed multiplication. As a future advancement in same, a radix 8 encoded multiplier will be designedwhich will further reduce the partial products and lead to higher speed of calculation and its area will be optimized. The proposed architecturewill bedesigned and synthesized using Verilog in Xilinx ISE. The design will be finally implemented using Spartan3E FPGA.


I would like to thank my guide, SnehaRevankar, Department of Electronics and Telecommunication, FCRIT, Vashi for her constant guidance and encouragement.


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