Iaetsd vlsi implementation of spatial modulation receiver

VLSI Implementation of Spatial Modulation Receiver Irshad begum Mohammad M.Tech.,(VLSID) Student Shri Vishnu Engineering College for Women Bhimavaram, AndhraPradesh, India e-mail ID: [email protected] Abstract—In this paper, a new transmission approach, called Spatial Modulation(SM) is presented. The use of multiple antennas at the transmitter and receiver sides (MIMO) can significantly enhance the capacity and reliability of wireless links. Spatial modulation (SM) is a relatively new modulation technique for multiple antenna systems which addresses these issues.In SM, the stream of bits to be transmitted in one channel is divided into two groups. One group i.e., m-bit sequence chooses one antenna from a total of Nt =2m antennas. A known signal is transmitted on this chosen antenna. The remaining Nt-1 antennas remain silent. The second group determines the symbol to be transmitted from the chosen antenna. By doing so, the problem of detection at the receiver becomes one of merely finding out which antenna is transmitting. This leads to a significantly reduced complexity at the Receiver. We have implemented the design of SM-MIMO receiver in VLSI with low complexity and achieved high performance. Keywords- Spatial Modulation, MIMO systems, IEEE-754 single precision floating point numbers, Complex number multiplication, Floating point adder/subtractor. . I.INTRODUCTION MIMO is an acronym that stands for Multiple Input Multiple Output. MIMO technology utilizes multiple antennas at both transmitter and receiver terminals.The need to improve the spectral efficiency and reliability of radio communication is driven by the ever increasing requirement for higher data rates and improved Quality of service (QOS) across wireless links. MIMO technology is one solution to attain this by transmitting multiple data streams from multiple antennas [1]. MIMO transmission strongly depends on transmit and receive antenna spacing, transmit antenna synchronization and the reduction of interchannel interference (ICI) at the receiver input. An alternative transmission approach that entirely avoids ICI at the receiver input is used for BPSK and QPSK transmission respectively. The basic idea is to compress a block of Nt symbols into a single symbol prior to transmission, where Nt indicates the number of transmit antennas. Information is retained by this symbol

Pushpa Kotipalli Professor: ECE Department, Head of ATL Shri Vishnu Engineering College for Women Bhimavaram, AndhraPradesh, India e-mail ID: [email protected] and is mapped to one and only one of the Nt antennas. The task of the receiver is twofold: First, to estimate the single symbol and second to detect the respective antenna number from which the symbol is transmitted. However this scheme suffers from a loss of Spectral efficiency. Traditional modulation techniques such as BPSK (binary phase shift keying), QPSK (Quadrature phase shift keying) etc. map a fixed number of information bits into one symbol. Each symbol represents a constellation point in the complex two dimensional signal planes. This is referred to as signal modulation. In this paper an alternative transmission approach is proposed in which this two dimensional plane is extended to a third dimension i.e., spatial dimension. This is referred as Spatial modulation. This new transmission technique will result in a very flexible mechanism which is able to achieve high spectral efficiency and very low receiver complexity. Spatial modulation (SM) is introduced by Mesleh in an effort to remove ICI, and the need for precise time synchronization amongst antennas. SM is a pragmatic approach for transmitting information, where the modulator uses well known modulation techniques (e.g., QPSK, BPSK), but also employs the antenna Index to convey information. Ideally, only one antenna remains active during transmission so that ICI is avoided. Spatial Modulation (SM) is a recently proposed spatial multiplexing scheme for Multiple-Input-Multiple-Output (MIMO) systems without requiring extra bandwidth or extra transmission power. SM does not place any restriction on the minimum number of receive-antennas. This is particularly beneficial for mobile handsets because of the limited available space and the cost constraints for these mass market devices. All these properties and requirements make SM a very attractive MIMO scheme for many potential applications. The idea of using the transmit antenna number as an additional source of information is utilized in spatial modulation. The number of information bits that can be transmitted using spatial modulation depends on the used constellation diagram and the given number of transmit antennas. In view of the fact that information is not only included in the transmitted symbol but also in the actual physical location of the antenna. Estimation of transmit antenna number is of key importance. The antenna number may change at the subsequent

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transmission instants, but at any given time only a single transmit antenna is transmitting. The channel vectors between each transmit antenna and the number of receive antennas are considered separately at the receiver. Assuming full knowledge of the channel at the receiver, the receiver chooses the transmit antenna number which gives highest correlation. In addition to eliminating ICI at the receiver [5], spatial modulation produces no correlation between the transmit antennas and it requires no synchronization between them. On the other hand, lack of synchronization is shown to have a major effect on system performance. Furthermore, in spatial modulation, the symbol duration is unchanged while the transmitted symbol carries a higher number of information bits due to the novel extension of modulation to the spatial domain. As a result, an improvement in spectrum efficiency is obtained. II.SYSTEM MODEL This paper is organized as follows: In section II System model is discussed, in section III hardware implementation is discussed, section IV is simulation results and section V is conclusion. We consider a generic Nt × Nr Multiple-Input-Multiple-output (MIMO) system with Nt and Nr being the number of transmit and receive antennas respectively[2]. Moreover, we assume that the transmitter can send digital information via M distinct signal waveforms (i.e., the so-called signal-constellation diagram).

Fig1: MIMO System with Nt Transmit Antennas and Nr receive antennas

The basic idea of SM is to map block of information bits into two information carrying units. 1. A symbol is chosen from a complex signal

constellation diagram. 2. A unique transmit antenna index is chosen

from the set of transmit antennas in the antenna-array.

The principal working mechanism of SM is depicted in fig 2:

Fig 2: Three dimensional constellation diagram of SM Each Spatial constellation point defines an independent complex plane of signal constellation points. For illustrative purpose only two of such planes are shown in Fig2. For i) Nt =4 and ii) M =4 Legend: i) Re = real axis of the signal constellation diagram and ii) Im = imaginary axis of the signal constellation diagram. The spatial modulation system model is shown in Fig 3. q (k) is a vector of n bits to be transmitted. The binary vector is mapped into another vector x(k). Symbol number l in the resulting vector x(k) is xl , where l is the mapped transmit antenna number l € [1:Nt]. The symbol xl is transmitted from the antenna number l over the MIMO channel, H(k). H(k) can be written as a set of vectors where each vector corresponds to the channel path gains between transmit antenna v and the receive antennas as follows: H = [h1 h2 h3 ….. h Nt] (1) Where: hv = [h1,v h2,v … hNr,v]T (2) The received vector is then given by y(k)=hxl + w(k); Where w(k) is the additive white Gaussian noise vector. The number of transmitted information bits n, can be adjusted in two different ways, either by changing the signal modulation and/or changing the spatial modulation. Different modulation techniques can be used for SM-MIMO such as BPSK, QPSK or 4QAM, 8QAM, 16QAM etc. These modulation techniques will be used to map the information bits to the symbols by using constellation diagrams. These symbols have to be transmitted from the chosen transmitting antennas. For example we consider only BPSK and QPSK modulation techniques for mapping of information bits to the symbols of BPSK and QPSK constellation diagrams.BPSK (Binary Phase Shift Keying) has two symbols +1 and -1 represented by 0 or 1 and QPSK (Quadrature Phase Shift Keying) has four quadtatures with 90 degrees phase shift each. It requires two bits to represent four symbols such as [-1-1i, -1+1i, +1-1i, +1+1i]



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Fig 3: Spatial modulation system model III. HARDWARE IMPLEMENTATION OF

SM-MIMO SYSTEM

A. .Transmitter Design of the SM-MIMO System using BPSK/QPSK modulation

The transmitter of the SM-MIMO system has to transmit the symbol and also have to select the antenna for the transmission of the symbol from among the group of antennas. A block of information bits is mapped into the constellation point in the signal and the spatial domain (antenna

Fig 4: Spatial Modulation Transmitter From the binary source the serially generated binary data will be converted into parallel data. This binary data will be segmented into two groups containing log2 (Nt) +log2(M) bits each, with log2(Nt ) and log2 (M) being the number of bits needed to identify a transmit-antenna in the antenna-array and a symbol in the signal-constellation diagram, respectively. The bits in the first sub-block are used to select the antenna that is switched on for data transmission, while all other transmit-antennas are kept silent in the current signaling time interval. The bits in the second sub-block are used to choose a symbol in the signal-constellation diagram using SM Mapper [3] as shown in Fig.4. Then symbol will be transmitted from antenna which is chosen among Nt transmitting antennas as shown in Fig.4. In general, the number of bits that can be transmitted using Spatial modulation is given as follows: n = log2 (Nt) + m (3) m = log2 (M) where ‘ M’ is the used constellation size.

Fig 5: Block diagram of MIMO Transmitter The SM-MIMO transmitter is implemented in the hardware using multiplexers. The multiplexers are designed in such away to select the antenna and choose the symbol from the input bit sequence based on the modulation technique used. Flip flops and ROM are used to store the binary input bits. If BPSK modulation is considered for symbol mapping, it requires two bits to represent antenna index and four transmit antennas are required. If the modulation is changed to QPSK, it requires only one bit to represent antenna index and hence only two transmit antennas will be sufficient. The Random Binary data which is to be transmitted is stored in an N-bit register. The random binary sequence can be of any length and it is given to the serial to parallel converter. From there we send 3bits parallely to the antenna. This 3-bit vector has the transmitted symbol and also the antenna index. The symbol is modulated using modulation techniques such as BPSK or QPSK. Here we are considering the noise free transmission over the Rayleigh Fading Channel. The number of bits that can be transmitted using spatial modulation is given in equ 3 and it depends on the used modulation technique. Here we consider only BPSK and QPSK modulation techniques. 3bits transmission using 4x4 antenna configuration and 2x4 antenna configuration is shown in Fig.6 & 7.



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Fig 6: 3bits transmission using BPSK Fig 7: 3bits transmission using QPSK B. SM Wireless Channel The transmission of binary data using spatial modulation is carried out over a Wireless Flat Fading Channel. The channel is a complex matrix of channel path gains. It varies according to the number of antennas and used signal constellation.

Fig 8. SM Wireless Channel C. Receiver design of SM-MIMO systems for BPSK

and QPSK modulated transmission The receiver of the SM-MIMO system is having the full knowledge of the channel. The task of the receiver is twofold:

i) To estimate the transmitted symbol and

ii) To detect the respective antenna number from which the symbol is transmitted.

Fig 9. Block diagram of Receiver Task The receiver iteratively computes the maximum ratio combining results between the channel paths from each transmit antenna to the corresponding receive antenna. Assuming to have full knowledge of the channel at the receiver, the receiver chooses the transmit antenna number which gives highest correlation.

Fig 10: Spatial modulation Receiver Assume the following sequence of bits to be transmitted, q(k) = [0 1 1]. Mapping this to BPSK symbol and four transmit antennas results in x(k) = [0,-1,0,0]T. The vector x(k) is transmitted over the MIMO channel H(k). We have to note that only antenna number 2 will be transmitting the symbol xl and the remaining three antennas will be



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transmitting zero energy. The channel matrix for the noise free transmission using BPSK modulation is given as follows.

According to the given sequence the symbol ‘-1’ is detected at antenna 2 and maximum correlation is obtained at that antenna position. The received vector at the receiver input is obtained as follows: y(k) = H(k)xl (4) Where 0.5377+0.1229i y(k) = 0.5450+0.0964i -0.4624+0.2680i -0.2854+0.1493i The resultant is obtained by applying maximum ratio combining to the received vector y(k) and results in g and is given as follows: gj =hj

H y, For j = 1 : Nt (5) where g = [ g1 g2 …gNt]T (6) The obtained resultant g for the received vector y(k) is given as follows: g = -0.3124-0.0146 -1.0000 -0.1951+0.0719 -0.1811 Hence we can observe from the above resultant vector that maximum correlation is obtained at antenna 2 and it is transmitting the BPSK symbol. Similarly, for QPSK modulated transmission of 3bits in the Spatial modulation the receiver of the SM-MIMO system functions as follows: Consider another 3bit sequence for transmission, q(k) = [0 1 0].Mapping this to QPSK symbol and two transmit antennas, results in x(k) = [1-i , 0]T. The vector x(k) is transmitted over the MIMO channel H(k). We have to note that only antenna number 1 will be transmitting the symbol xl and the antenna 2 will be transmitting zero energy.The channel matrix H(k) and the noise free transmission for QPSK modulation is given as follows:

The received vector at the receiver input is obtained as follows:

y(k) = -0.6606+0.4149i -0.6415+0.4486i 0.1944-0.7304i 0.1361-0.4348i The resultant is obtained by applying maximum ratio combining to the received vector y(k) and results in g.The obtained resultant g for the received vector y(k) is given as follows: g = 1.0000-1.0000i 0.2978-0.3271i Hence we can observe from the above resultant vector that maximum correlation is obtained at antenna 1 and it is transmitting the QPSK symbol. The Receiver in the SM-MIMO System has to perform the matrix multiplications and additions of complex numbers between the channel matrix H(k) and the received vector y(k) at the receiver inputs. The number of complex multiplications performed by the receiver is given as Nt Nr and Nt (Nr -1) complex additions. So, the total number of complex operations required is given as: [2Nt Nr – Nt] (7) Each complex number of the channel matrix H(k) and the received signal matrix y(k) is first separated to its real part and imaginary part. It is then converted to 32-bit floating point number using the IEEE-754 format. The term floating-point refers to the fact that the decimal point can float, that it is placed anywhere relative to the many digits of the amount. The single precision format is shown in Fig 7. 1 8 23

Fig 11: Representation of single precision Floating point

number. This format consists of 3fields- a sign bit(s), a biased exponent (E) and a mantissa (F).

1-bit sign, S: A value of ‘1’ indicates that the number is negative, and a ‘0’ indicates a positive number.

Bias- 127 exponent, e = E + bias: This gives us an exponent range from Emin = -126 to Emax = 127

Fraction/mantissa: The fractional part of the number significand, which is 1 plus

SIGN

EXPONENT (E)

MANTISSA (F)



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the fractional part. The leading 1 in the significand is implicit.

Single precision floating point numbers have 1 bit sign bit, 8bit exponent and 23 bit mantissa as shown in Fig 7. Single precision can represent 32 bits. The floating point numbers are represented by the equation which is given as follows: X = (-1)^ s*1.F*2^ (E-127) (7)

Fig.12:Flow chart for floating point multiplication Floating point multiplication process can be given in the algorithmic form as follows:

Multiply the significands i.e.(M1*M2) Placing the decimal point in the result. Adding the exponent i.e, (E1+E2-bias). Obtaining the sign, s1 xor s2 Normalizing the result Rounding of the result to fit in an

available bit. D. Floating point Adder/Subtractor Floating –point addition has mainly 3 parts:

1. Adding hidden ‘1’ and Alignment of the mantissas to make exponents equal.

2. Addition of aligned mantissas. 3. Normalization and rounding the result.

The initial mantissa is of 23-bit wide. After adding the hidden ‘1’, it is 24 bit wide. First the exponents are compared by subtracting one from the other and looking at the sign (MSB which is carry) of the result. To equalize the exponents, the mantissa part of the number with lesser exponent is shifted right‘d’ times. Where‘d’ is the absolute value difference between the exponents. The sign of the larger number is anchored. In Normalization, the leading zeroes are detected and shifted so that a leading one comes. Exponent also changes accordingly forming the exponent for the final packed floating point result. The whole process is explained clearly in Fig13.

Fig 13: Architecture for Detection of Symbol by SM-

MIMO Receiver The Receiver of the SM-MIMO system has to iteratively perform multiplication operations of the complex numbers between channel matrix H(k) and received signal matrix y(k) for different antennas. The received signal y(k) is different for different symbols of BPSK and QPSK modulation techniques for different transmit antenna numbers. The complex number matrix multiplication is highly optimized in terms of area, speed and power. It is functionally verified in VHDL language and synthesized. IV. RESULTS

a) MATLAB Simulation Results

For the purpose of simulation, a flat Rayleigh fading channel is assumed with additive white Gaussian noise (AWGN). The receiver is assumed to have full channel knowledge. Random binary data of length 10,00,000 bits was generated. Let us consider first thirty information bits of transmission data.



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Fig14: Sampling index vs magnitude plot of first

30 bits of transmitting data For 3bits transmission using QPSK modulation, the 2nd and 3rd bits used for selection of symbol. Those bits will be mapped to QPSK symbol and 1st bit used for choosing the transmitting antenna. So twenty bits are mapped as ten QPSK symbols having magnitude and phase. These symbols have transmitted from the chosen transmitting antenna. The indices of chosen antennas will be transmitted implicitly.

Fig15: Magnitude and phase plots of QPSK symbols These QPSK symbols are multiplied by respective path gains while transmitting through wireless channel.

Fig16: Magnitude and Phase plots of channel effected

QPSK symbols AWGN noise was added to BPSK symbols and received bits are detected and number of errors is detected. This procedure is repeated by changing SNR in steps of 1dB from 0dB to 10dB. It is having maximum BER equal to 0.08 and falling as SNR increases.

Fig17: SNR VS BER Plot BPSK System Additive white Gaussian Noise is added to QPSK symbols. Now by changing the SNR insteps of 1dB from 0dB to 10dB. Corresponding BER values are calculated. It is having maximum BER equal to 0.15 and falling as SNR increases.

Fig18: SNR Vs BER Plot of QPSK system BER for SM-MIMO was calculated at different SNRs. SNR is changed in steps of 2dB from 0dB to 20dB. MATLAB simulations are repeated for QPSK and BPSK modulation techniques with SM-MIMO and its BER values are plotted.

Fig19: SNR Vs BER Plots for SM-BPSK and SM-QPSK

0 1 2 3 4 5 6 7 8 9 1010-6

10-5

10-4

10-3

10-2

10-1

SNR in dB

BER

BPSK Modulation

0 1 2 3 4 5 6 7 8 910

-5

10-4

10-3

10-2

10-1

100

SNR in dB

BE

R

QPSK Modulation

0 2 4 6 8 10 12 14 16 18 2010

-5

10-4

10-3

10-2

10-1

100

SNR in dB

BE

R

Spatial Modulation

BPSKQPSK



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In SM detection errors occur more because information bits are to be recovered from both transmitted symbol and antenna number. The BER for BPSK is less than that of QPSK modulation.

b) VLSI SIMULATION RESULTS

Fig20: Detection of BPSK symbol +1 at Antenna-1 by Receiver

Fig21: Detection of BPSK symbol -1 at Antenna-1 by Receiver


Fig23: Detection of BPSK symbol -1 at Antenna-2

by Receiver


Fig25: Detection of BPSK symbol -1 at Antenna-3 by Receiver



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Fig27: Detection of BPSK symbol -1 at Antenna-4 by

ReceiveR

Fig28: Detection of QPSK symbol +1+i at Antenna-1

by Receiver

Fig29: Detection of QPSK symbol -1+i at Antenna-1 by

Receiver

Fig30: Detection of QPSK symbol +1-i at Antenna-1 by

Receiver

Fig31: Detection of QPSK symbol -1-i at Antenna-1 by Receiver



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Fig32: Detection of QPSK symbol 1+i at Antenna-2 by

Receiver

Fig33: Detection of QPSK symbol -1+i at Antenna-2 by

Receiver

Fig34: Detection of QPSK symbol 1-i at Antenna-2 by Receiver

Fig35: Detection of QPSK symbol -1-i at Antenna-2 by

Receiver C) RTL Schematics of BPSK/QPSK Transmitter

Fig36: Top module of BPSK Transmitter

Fig37: Internal module of BPSK Transmitter



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Fig38: Technology Schematic of BPSK Transmitter

Fig39: Top module of QPSK Transmitter

Fig40: Internal module of QPSK Transmitter

Fig41: Technology Schematic of QPSK Transmitter D) RTL Schematics of BPSK/QPSK Receiver

Fig42: Top module of QPSK Receiver

Fig43: Total Architecture of QPSK Receiver



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E) Synthesis Report of QPSK/BPSK Receiver

Fig 44: Comparison Table for BPSK/QPSK Receiver

V.CONCLUSION In this paper, we have implemented the hardware design of the Spatial Modulation MIMO Receiver with low complexity using VLSI technology. It employs the Complex number multiplication and Addition operations between channel matrix and received signal matrix. A novel high rate, low complexity MIMO transmission scheme called Spatial Modulation (SM) that utilizes the spatial information in an innovative fashion has been presented. It maps multiple information bits into a single information symbol and into the physical location of the single transmitting antenna. The task of the receiver is to detect the transmitted symbol and to estimate the respective transmitting antenna. Spatial modulation avoids ICI at the receiver input. In addition, only one RF (radio frequency) chain is required at the transmitter because at any given time only one antenna transmits. Hence the energy efficiency is achieved and the cost of the transmitter is significantly reduced. The Receiver of the SM-MIMO system has been deigned, which computes complex number multiplications with less amount of resources and with low complexity and thereby achieved high performance. REFERENCES [1] Caijun Zhong “Capacity and Performance Analysis of Advance Multiple Antenna Communication Systems”, London, March 2010.

[2] R.Mesleh and H.Haas, “ Spatial Modulation-A New Low Complexity Spectral Efficiency Enhancing Technique”, Communication and Networking in China 2006. ChinaCom 06. First International Conference on 25-27, Oct 2006. [3] M. Di Renzo, Member, IEEE, H.Haas, Member, IEEE, Ali Ghrayeb, senior Member, IEEE, and Shinya Sugiura, senior member, IEEE, “Spatial Modulation for generalized MIMO: Challenges, opportunities and implementation. [4] Y.Chau and S-H. Yu, “ Space modulation on Wireless fading Channels,” Proc.IEEE VTC’2001, vol.3, pp. 1668-1671, October 2001. [5] H. Haas, E. Costa, and E. Schulz, “Increasing Spectral Efficiency by Data Multiplexing Using Antenna Arrays”, Proceedings of the International Symposium on personal, Indoor and Mobile Radio Communications (PIMRC 2002), vol. 2, pp.610-613, September 15 – September 18 2002. [6] R.Mesleh, H.Haas, Y.Lee, and S.Yun, “Interchannel Interference Avoidance in MIMO Transmission by Exploitng Spatial Information,” Proceedings of the International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2005,September 11-September 14, 2005 [7] J. Jeganathan, A.Ghrayeb and L.Szczecinski, “Spatial modulation:Optimal detection and performance analysis,” IEEE Commun.Lett.Vol.12, no.8,pp.545-547, July 2009 [8] M.D.Renzo and H.Haas, “Performance analysis of Spatial Modulation,” In Proc. Int. ICST Conf.CHINACOM,Aug.2010,pp.1-7. [9] Pritam Som and A.Chokalingam “A Spatial Modulation and Space shift Keying in Single Carrier Communication”, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications – (PIMRC). [10] Y.Chau and S-H.Yu, “Space modulation on Wireless fading Channels”, Proc.IEEE VTC’2001,vol.3,pp. 1668-1671, October 2001. [11] Apple Inc., http://www.apple.com/ (current July 09, 2008. [12]dspLog-Signal Processing for communication, www.dspLog.com [12] G.Even and P.M. Seidel, “A comparison of three rounding algorithms for IEEE floating-point multiplication”, Technical Report EES 1998-8,EES Dep., Tel-Aviv Univ.,1998. http://www.eng.tau.ac.il/Utils/reportlist/reports /repfram.html [13] IEEE standard for binary floating arithmetic. ANSI/IEEE 754-1985, New York, 1985.

Logic Utilization

QPSK Receiver

BPSK Receiver

Number of Slices

4353

8826

Number of 4 input LUTs

8630

17492

Number of bonded IOBs

897

897

Number of MULT 18X18SIOs

4

4

Number of GCLKs

1

1

Combinational Path delay

143.524ns

93.547ns



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