A NOVEL APPROACH FOR LOWER POWER DESIGN IN TURBO CODING SYSTEM

International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 DOI : 10.5121/vlsic.2011.2202 16 A NOVEL APPROACH FOR LOWER POWER DESIGN IN TURBO CODING SYSTEM Dayadi.Lakshmaiah 1 Dr.M.V.Subramanyam 2 Dr.K.Sathaya Prasad 3 1 Asso.professor of ECE Department, Sree Dattha Engineering and Science, Hyderabad, India. [email protected] , [email protected] 2 Principal and Professorof ECE Department, Santhi Ram Engineering College, Nandyal, India. [email protected] 3 Professor of ECE Department and Rector, JNTU Kakinada, Kakinada, India. [email protected] Abstract : Low Power is an extremely important issue for future mobile communication systems; The focus of this paper is to implementat turbo codes for low power solutions. The effect on performance due to variation in parameters like frame length, number of iterations, type of encoding scheme and type of the interleave in the presence of additive white Gaussian noise is studied with the floating point model. In order to obtain the effect of quantization and word length variation, a fixed point model of the application is also developed.. The application performance measure, namely bit-error rate (BER) is used as a design constraint while optimizing for power and area coverage. Low power Optimization is Performed on Implementation levels by the use of Voltage scaling. With those Techniques we can reduced the power 98.5%and Area(LUT) is 57% and speed grade is Increased .This type of Power maneger is proposed and implemented based on the timing details of the turbo decoder in the VHDL model. Keywords: low power consumption, Turbo Encoder, Turbo Decoder, Power Ooptimization, AreaOptimization. I INTRODUCTION Application specific design is a process of alternative design evaluations and refined implementations at various abstraction levels to provide efficient and cost effective solutions. Turbo codes were presented in 1993, by Berrou et al. [20] and since then these codes have received a lot of interest from the research community as they offer better performance thanany of the other codes at very low signal to noise ratio. Turbo codes achieve near Shannonlimit error correction performance with relatively simple component codes. Efficient methodology for the application specific design reduces the time and effort spentduring design space exploration. The turbo code application from the area of wirelesscommunications is chosen as the key application for which an application specific designmethodology is developed. The International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 17 functionality and specific characteristics of the applicationare needed to carry out the design space exploration. The application characteristics studiedare, the impact on the performance of the turbo codes with variation in the size of the inputmessage (frame-length), type of the interleaver and the number of decoding iterations.Turbo coding is a forward error correction (FEC) scheme. Iterative decoding is the key feature of turbo codes. [1-15] Turbo codes consist of concatenation of two convolution codes. Turbo codes give better performance at low SNRs (signal to noise ratio) .Interestingly, the name Turbo was given to this codes because of the cyclic feedback mechanism (as in Turbo machines) to the decoders in an iterative manner. The algorithmic specifications and the performance characterization of the turbo codes. Form a pre-requisite study to develop a low power solution. Functional analysis of turbo decoder with simplified computation metric to save on power as well as the architectural features like bit-width are closely related to the application parameter like bit-error rate (BER). II SYSTEM LEVEL MODELING System level modeling is the phase of design aimed at architecture exploration before theactual HDL implementation. The availability of system level modeling and implementation techniques helps us to ensure functional correctness as well as explore the design space.The memory access patterns in the application are studied. The data flowanalysis as well as synchronization requirement between the different modules form the basis for identifying parallelism in the algorithm. This drives the hardware solution of the turbo encoder and decoder design at system level in the design methodology. Identifying the access pattern of the computationally intensive routines, it is proposed to use FIFO/LIFO buffers to store the intermediate results in the four state turbo decoder.To test the implementation correctness, the turbo encoder and one four state turbo decoder is synthesized onto Xilinx ISE simulators. International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 18 Figure 1: The turbo coding system 1.Generate the message to be transmitted through the channel, which is a binary data offrame size N. Generating this message to be transmitted through the AWGN channel is done using a random number generator. 2. The two encoders, depicted in figure 4.1 encode the message into a bit stream and transmit it through the channel. To the encoder1, the input is the message to be transmitted and to the second, it is the interleaved message using symmetric interleaver of size N. The encoded data is concatenated and mapped to the (1, 0) channel symbols onto an antipodal baseband signal (+1, - 1), producing transmitted channel symbols. 3. Add AWGN noise to these transmitted channel symbols to obtain the noisy receiver input. 4. Perform MAP decoding for six iterations to retrieve the message that is transmitted. Bit error rate is computed to obtain the performance of the turbo decoder for varyingsignal-to-noise ratios. International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 19 Turbo encoder Turbo coding system consists of the turbo encoder and the turbo decoder. The description of the four state and eight state (3GPP). Four state turbo encoder The general structure of turbo encoder architecture consists of two Recursive SystematicConvolutional (RSC) encoders Encoder 1 and Encoder 2. The constituent codes are RSCsbecause they combine the properties of non-systematic codes and systematic codes.In the encoder architecture displayed in the two RSCs are identical. The N bitdata block is first encoded by Encoder 1. The same data block is also interleaved and encoded by Encoder 2. The main purpose of the interleaver is to randomize burst error patterns so that it can be correctly decoded. It also helps to increase the minimum distance of the turbo code . Input data blocks for a turbo encoder consist of the user data and possible extra data being appended to the user data before turbo encoding.The encoder consists of a shift register and adders . The structureof the RSC encoder is fixed for the design because enabling varying encoder structures would significantly increase the complexity of the decoder by requiring to adapt to the new trellis structure and computation of the different metrics in the individual decoders. The input bits are fed into the left end of the register and for each new input bit two output bits are transmitted over the channel. These bits depend not only on the present input bit, but also on the two previous input bits, stored in the shift register. Turbo Decoder  In turbo decoder the iterative decoding process of the turbo decoder is described. The maximum a posteriori algorithm (MAP) is used in the turbo decoder. There are three types of algorithms used in turbo decoder namely MAP, Max-Log-MAP and Log-MAP. The MAPalgorithm is a forward-backward recursion algorithm, which minimizes the probability of bit error, has a high computational complexity and numerical instability. The solution to these problems is to operate in the log-domain. One advantage of operating in log-domain is that multiplication becomes addition. Addition however is not straight forward. Addition is a maximization function plus a correction term in the log domain. The Max-LogMAP algorithm approximates addition solely as maximization. Max-Log-MAP algorithm in turbo decoder is used in our work. International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 20 The block diagram of the turbo decoder is shown inabove Figure. There are two decoders corresponding to the two encoders. The inputs to the first decoder are the observed systematicbits, the parity bit stream from the first encoder and the de interleaved extrinsic information from the second decoder. The inputs to the second decoder are the interleaved systematic bit stream, the observed parity bit stream from the second RSC and the interleaved extrinsic information from the first decoder. The main task of the iterative decoding procedure, in each component decoder is an algorithm that computes the a posteriori probability (APP) of the information symbols which is the reliability value for each information symbol. 1) Branch metric computation Turbo decoding the first computational block is the branch metriccomputation. The branch metrics is computed based on the knowledge of input and output associated with the branch during the transition from one state to another Eq. 1 International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 21 2) Forward metric computation The forward metric is the next computation in the algorithm, which represents the probability of a state at time k, given the probabilities of states at previous time instance. Eq. 2 Where the summation is over all the state transitions, which is to be computed at each node at a time instance k in the forward direction traversing through the trellis and is computed for states 00, 01, 10 and 11. 3) Backward metric unit The backward state probability being in each state of the trellis at each time k, given the knowledge of all the future received symbols, is recursively calculated and stored The backward metric is computed using equation 3 in the backward direction, Eq. 3 Where the state transition is from s’, β. is computed for states 00, 01, 10 and 11 in a 4 state decoder. In an 8 state decoder - 3GPP version is computed for states 000, 001,010, 011, 100, 101, 110 and 111. 4) Log likelihood ratio (lr) Log likelihood ratio llr is the output of the turbo decoder. This output llr for each symbol at time k is calculated as Eq. 4 The sign of the number corresponds to the hard decision while the magnitude gives a reliability estimate . 5) Extrinsic unit Compute the extrinsic information that is to be fed to the next decoder in the iteration sequence. This is the llr minus the input probability estimate. Extrinsic information ext [k-1] is obtained from the log likelihood ratio llr [k-1] by subtracting the weighted channel systematic bits and the information fed from the other decoder. International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 22 III. DESIGN MODULES In application specific designs, impact of architectural parameters on the power consumption and area is significant. With increasing demand for low power battery driven electronic systems, power efficient design is presently an active research area. Batteries contribute a significant fraction of the total volume and weight of the portable system. Ap plications like digital cellular phones, modems and video compression are compute and memory intensive. The basic components in these are the input-output units, on-chip mem ory, off chip memory and the central processing unit. Power dissipation is highly dependent on the switching activity, load capacitance, frequency of operation and supply voltage. Further design parameters like memory size and bit width influence the power consumption significantly. The power dissipation of the application design needs to be lowered using suitable architectural optimizations. In this project work a digital design for log MAP coding for turbo encoding/decoding is developed for such portable devices. C) FSM Controller Unit The top-level controller, whose purpose is to activate the modules in proper order, manages the turbo decoding process. The turbo decoder which constitutes of the two decoders is iterative in nature. The simulations have to be performed for six iterations. Hence a top-level finite state machine (FSM) controller unit is essential. A FSM consists of a set of states, a start state and a transition signal to move from the current state to the next state (in turbo decoder from one iteration to the next iteration). The FSM design appears explicitly in the turbo decoder design system for the control and the sequencing of the iterations. At the data flow level, iteration control and the data computation of the decoder system are separated then the description of the FSM has a close correspondence to the typical behavior of the algorithm. International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 23 IV.SIMULATION RESULTS The design is first modeled in VHDL and then synthesized using Leonardo tools. XPower brings an extra-level of design assurance to the low-power device analysis. Accurate power estimation during programmable design is done with XPower. XPower reads in either pre-routed or postrouted design data and provides accurate device power estimation either by net, or for the overall device. Results are provided either in report or graphic format. The VHDL designs were simulated and only synthesized. The estimates are for 0.18 m technology. The voltage that is used in our estimation is 2.5V. There is a facility to set the input capacitance and frequency of operation for whichthe design power estimation is to be done. There is a provision to give a specific switching activity for the design power estimation. The estimate for 20 and 50 activity factor is found. XPower calculates the power as a summation of the power consumed by each component in the design. The power consumed is the product of capacitance, square of the voltage, activity factor and frequency of operation and is reported in mW. International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 24 Figure:2 (A)Turbo encoder and Decoder Top module Power report Figure:2 (B)Turbo encoder and Decoder Top module Power report with date International Journal of VLSI design & Communication Systems (VLSICS) Vol.2, No.2, June 2011 31 Authors Dayadi.Lakshmaiah is currently working as an Associate professor of Electronics & Communications Engineering.SreeDattha Engineering and Science, Hyderabad, AndraPradesh (State), India. He Received B.Tech Degree in ECE From National Institute of Technology, Warangal (RECW),India and M.Tech (DSCE) Degree From JNTUniversity , Anantapur AndhraPradesh. India Now He is Pursuing Ph.D in Low Power VLSI at JNTUniversity ,Kakinada, AndhraPradesh, India. Dr.M.V.Subramanyam Professor of ECE is currently working as a Principal of In Santhiram Engineering College Nandyal, AndraPredesh, India. He has 20 year of Experience in Teaching. He authored STLD, Computer Networks and Basic Electronics and Microprocessor& Microcontroller Interfacing and Application. He published more than 26 Technical papers and National and International Journals and Confereces, He has International Editorial Member for the International journal “Information Technology”His Area of interest is Adhoc Wireless Networks, Cellular and Mobile Communications. He is anEditorial and Technical Member for Three International Journals and Two National Journals. He has Received B.Tech & M.Tech and Degree in ECE from JNTU, Ph.D (Adhocwire less Network) Degree from JNTUH Hyderabad Andhra Pradesh India. Dr. K. Sathaya Prasad Professor of ECE is currently working as a Rector of JNTUK, Kakinada. He has more than 30 years of experience in teaching and 20 years of R & D. He is an expert in Digital Signal Processing. He has Guided to 10Ph.D’s and guiding 10Ph.Dscholars. He authored Electronic Devices and Circuits text book. He held different positions in his career like Head of theDepartment, vice principal, and principal for JNTU Engineering College (JNTUK). He published more than 30 technical papers in nationaland International Journals and conferences. He also received best Teacher Award from Govt of Andhra Pradesh in 2010. He is Received B.Tech Degree in ECE from JNTUA Anantapur, M.E(Communication Systems) Degree from University of Madras, and Ph.D (signal Processing) Degree from the Indian Institute of Technology Madras, India.