higher level modulation for lte

8/8/2019 Higher Level Modulation for LTE

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Introduction

Telecommunications data rates are as predictable as Moore's Law. Some

telecommunications technologies, like cellular telephony, can be used as

you move around freely. Others, like Wi-Fi, can be used while moving fromplace to place but aren't fully mobile. According to Edholm's Law, the

three telecommunications categories march almost in lock step: their data

rates increase on similar exponential curves, the slower rates trailing the

faster ones by a predictable time lag. At recent conference in New York

City, Hossein Eslambolchi, president of AT and T Labs in Bedminster, N.J.,

made an observation that telecommunications data rates aren't rising just

in a Moore's Law-like way; they're rising at exactly the Moore's Law rate:

doubling every 18 months.

So in order to satisfy the customers needs for higher data rate and

mobility, continuous research work is carried on these topics. One of the

big achievements of research is the Orthogonal Frequency Division

Multiplexing which results in the saving of 50% bandwidth compared to

Frequency Division Multiplexing and results in immunity to Multipath

fading. In OFDM transceivers the main task is the application of the

IFFT/FFT in modulation and demodulation respectively.

In order to successfully implement the Orthogonal Frequency Division

Multiplexing modulation which should be applicable to Long Term

Evolution(LTE), Worldwide Interoperability for Microwave Access (WiMAX)

and Wi-Fi on Digital Signal Processing board that is TMS320C6414 Velocity

architecture having 1GHz speed, Firstly I am going to do is to simulate the

code for the OFDM Modulation and Demodulation with 64 QAM and all

others parameters which are applicable to LTE, WiMAX and Wi-Fi like

number of carriers, IFFT size, guard period type, guard length time, carrier

frequency, symbol duration, guard time, space frequency between two

frequencies, bandwidth and symbol rate. In the Matlab first am going to

generate random data and then convert the random data to the parallel

data i.e. to symbols depending on the number of bits per symbol, binary

data into modulo N integer data where N = 2^bit per symbol.

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After the conversion from serial to parallel the 64 QAM modulations if

performed and after that the frequency domain signal is converted to time

domain signal using the Inverse Fast Fourier Transform (IFFT) which is the

fastest version of Inverse Discrete Fourier Transform (IDFT). As we

considering the idle case in Matlab just for knowledge purpose we are not

considering the channel as idle i.e. what the data is generated at the

transmitter side the same data is applied at the receiver side. After the

IFFT the parallel data is converted to the serial data. At the receiver the

side the same data is applied to the receiver side. The serial data is

converted to the parallel stream and then Fast Fourier Transform is

performed which is the conversion of time domain signal to the frequencydomain. The frequency domain signal is then demodulated using 64 QAM

after the demodulation the same binary stream of data should appeared

across the output of demodulator as at the output of the random data

generator without any bit error. The parallel data is then converted to

serial data stream.

Secondly, after the successful completion of the above task then that isthe time to model OFDM modulation on the DSP board using the Code

Composer Studio. Using one DSP board first we should do modulation and

see the constellation map on the Code Composer Studio or on the Digital

Storage Oscilloscope. After the successful completion of the OFDM

modulation task then using the same board the demodulation should be

done using Costas loop. The output data stream after the Costas loop

should be same as that of the input at the modulator side. If the outputdata stream is not same as that of the input data steam then there should

be some symbol timing recovery error. In order for proper symbol timing

recovery the design of the Costas loop and symbol timing recovery loop

should be accurate.

Thirdly, after the successful implementation of above task then what we

should do is to use two DSP boards one for transmission and other one for

reception. The boards should be connected with wire or wireless. When

the boards are wireless connected then will face several problems like

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multipath delays, fading, inter channel interference, inter symbol

interference and Doppler shifts. In order to compensate for these losses,

we should modify our code to do forward error correction, interleaving and

cyclic prefix. At the reception if due to symbol timing offset the

constellation diagram rotate then we should do something to make it

normal. At the reception if the data received is same as that at the

transmission, then the project will be successful.

Aim

To achieve OFDM Modulation and Demodulation on Digital Signal

Processor applicable to Long Term Evolution (LTE), WiMAX and Wi Fi

Objective

In order to achieve the aim we have to go through various procedures. As

we know it is not an easy task to implement the OFDM modulation and

Demodulation with 64 QAM in real time. So, in order to reach the

destination we have to go step by step through various stages. First we

have to simply implement the OFDM modulation and demodulation with

64 QAM on the Matlab without introducing any channel noise, considering

the channel as Idle. The idea behind this is to understand the concept and

parameters of OFDM modulation and demodulation with 64 QAM. In the

idle case there is no transmission error so the received data at the

receiver should be same as random data generated at the transmitter. The

parameters used for modulation like number of carriers, IFFT size, guard

period type, guard length time, carrier frequency, symbol duration, guard

time, space frequency between two frequencies, bandwidth and symbol

rate should be compatible with LTE, WiMAX and Wi Fi. In the second phase

after the successful completion of the first task now I can do Modulation

and Demodulation on the DSP board. As we know the DSP support the C+

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+ language which can be programmed through Code Composer Studio. In

order to program the DSP board we can either do programming in C++

and we can also convert the MATLAB code to C/C++ code using the

MATLAB Compiler. The translated C/C++ code can then be converted into

a MEX file which can be called from MATLAB.There are three options to

program the DSP board and these are by using Embedded Matlab function

in simulink and Real Time Workshop to target my board, manually

converting all the code to C and port it via CCS and since we have Real-

Time Workshop, you can generate embeddable C code directly from

MATLAB code using Embedded MATLAB. Embedded MATLAB is a subset of

the MATLAB language that supports code generation for real-time

embedded systems. Embedded MATLAB supports C-code generation forembedded algorithms and systems. It consists of more than 300 operators

and functions from MATLAB, 110 functions from Fixed-Point Toolbox, and

40 functions from Signal Processing Toolbox. Thirdly after the successful

completion of the above task we can do the OFDM modulation on one

board and after the completion of the I Q modulation there is no need to

combine these two signals and these two signals are transmitted directly

on the LEFT and Right channels of the DSP board. We have to use otherboard for reception, at the reception the I and Q signals are applied to the

receivers LEFT and Right channel and then we have to use Costas loop

and some symbol timing recovery loop for proper reception of signal. If

the binary data transmitted at the sender side is same as that of the

reception side after hard decision then the project will be successful.

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Literature Review

OFDM technologies typically occupy nomadic, fixed and one-way

transmission standards, ranging from TV transmission to Wi-Fi as well as

fixed Wi-MAX and newer multicast wireless systems like Qualcomms FLO

(Forward Link Only). OFDMA, however, adds true mobility to the mix,

forming the backbone of many of the emerging technologies such as Long

Term Evolution (LTE) and Mobile WiMAX. OFDM is being used in a number

of wireless and wire-line applications including WLAN, Digital Audio and

Video Broadcast, Fixed WiMAX, ADSL, and ADSL2+, Mobile WiMAX and

trials of LTE. The difference is that OFDMA has the ability to dynamically

assign a subset of subcarriers to individual users, making this the multi-

user version of OFDM, using either Time Division Multiple Access (TDMA)

(separate time frames) or Frequency Division Multiple Access (FDMA)

(separate channels) for multiple users. OFDMA refers to simultaneously

supporting multiple users by assigning them specific sub channels for

intervals of time. Point-to-point systems are OFDM and do not support

OFDMA. Point-to-multipoint fixed and mobile systems are the OFDMA form

of OFDM. On the other hand, with an OFDM time domain signal, the

subcarriers magnitudes and phases can easily be detected using a very

simple and well understood signal processing technique based on off-the-

shelf Fast Fourier Transform (FFT) algorithms. Furthermore, OFDM signals

are resistive to multi-path distortion and thus, OFDM receiver does not

require complex equalizer implementation. Instead, multi-path distortion is

completely eliminated just by simply provisioning for a slightly longer

transmission time at the end of each symbol period by repeating a portion

of the transmit signal know as the Cyclic Prefix (CP).

In Mobile WiMAX, the FFT size is scalable from 128 to 2,048. Here, when

the available bandwidth increases, the FFT size is also increased such that

the subcarrier spacing is always 10.94 kHz. This keeps the OFDM symbol

duration, which is the basic resource unit, fixed and therefore makes

scaling have minimal impact on higher layers. A scalable design also

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keeps the costs low. The subcarrier spacing of 10.94 kHz was chosen as a

good balance between satisfying the delay spread and Doppler spread

requirements for operating in mixed fixed and mobile environments. This

subcarrier spacing can support delay-spread values up to 20 sec and

vehicular mobility up to 125 km/h when operating in 3.5GHz. A subcarrier

spacing of 10.94 kHz implies that 128, 512, 1,024, and 2,048 FFT are used

when the channel bandwidth is 1.25MHz, 5MHz, 10MHz, and 20MHz,

respectively. It should, however, be noted that mobile WiMAX may also

include additional bandwidth profiles. For example, a profile compatible

with Wireless Broadband (WiBro) will use an 8.75MHz channel bandwidth

and 1,024 FFT. This obviously will require different subcarrier spacing and

hence will not have the same scalability properties.

The IEEE 802.11a standard specifies an OFDM physical layer (PHY) that

splits an information signal across 52 separate subcarriers to provide

transmission of data at a rate of 6, 9, 12, 18, 24, 36, 48, or 54 Mbps. The

6, 12, and 24 Mbps data rates are mandatory. The primary purpose of the

OFDM PHY is to transmit Media Access Control (MAC) protocol data units

(MPDUs) as directed by the 802.11 MAC layer. The OFDM PHY is dividedinto two elements: the physical layer convergence protocol (PLCP) and the

physical medium dependent (PMD) sub layers. The signal field consists of

216 bits, these 216 bits are the data bits per OFDM symbol but the coded

bits per OFDM symbol are 288, defining data rate and frame length. Coded

bits per subcarrier are 6 for 64 QAM. The 802.11a version of OFDM uses a

combination of binary phase shift keying (BPSK), Quadrature PSK (QPSK),

and Quadrature amplitude modulation (QAM), depending on the chosendata rate. The length field identifies the number of octets in the frame.

The PLCP preamble and signal field are convolutionally encoded and sent

at 54Mbps using 64-QAM no matter what data rate the signal field

indicates, The convolution encoding rate depends on the chosen data rate.

In order for the proper implementation of the OFDM Transceiver on the

DSP board which should be applicable to the Long Term Evolution (LTE),

WiMAX and Wi Fi we have to select the parameters which should be

applicable for LTE, WiMAX and Wi Fi. I am going to consider the maximum

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parameters for the better throughput, for QAM modulation 6 bits per

symbol is enough because if we increase the number of bits per symbol

then during the multipath propagation the scattering of data symbols

would be large because for higher value of M-QAM the mapping of data

symbols on the constellation mapping will be too close and after scattering

inter symbol interference will occur that we called inter symbol

interference. The maximum IFFT/FFT size supported by the DSP board is

1024, so I am going to use 1024-IFFT/FFT for OFDM Modulation and

Demodulation.

OFDM is a special case of multicarrier transmission, where a single data

stream is transmitted over a number of lower-rate subcarriers (SCs). It isworth mentioning here that OFDM can be seen as either a modulation

technique or a multiplexing technique. One of the main reasons to use

OFDM is to increase robustness against frequency-selective fading or

narrowband interference. In a single-carrier system, a single fade or

interferer can cause the entire link to fail, but in a multicarrier system,

only a small percentage of the SCs will be affected. Error-correction coding

can then be used to correct for the few erroneous SCs.

It is possible, however, to arrange the carriers in an OFDM signal so that

the sidebands of the individual carriers overlap and the signals are still

received without adjacent carrier interference. To do this the carriers must

be mathematically orthogonal. The receiver acts as a bank of

demodulators, translating each carrier down to dc, with the resulting

signal integrated over a symbol period to recover the raw data. If the othercarriers all beat down the frequencies that, in the time domain, have a

whole number of cycles in the symbol period T, then the integration

process results in zero contribution from all of these other carriers. Thus,

the carriers are

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linearly independent (i.e., orthogonal) if the carrier spacing is a multiple of

1/T.

In the first part what I am going to do is to just write the code for OFDM

modulation with 64-QAM having 1024-IFFT/FFT size. I am not going to

consider any channel i.e. the constellation map generated after

modulation and the output data after the IFFT is directly applied to the

demodulator side. The constellation mapping at the modulator side after

the 64 QAM is applied to the Inverse Fast Fourier Transform the parallel

data is converted to the serial data and then the serial bit steam is applied

to the receiver serial to parallel as shown in the block

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diagram. The serial data is then converted to the parallel data and thenFast Fourier Transform is done on the data which is then demodulated

using 64 QAM. The parallel data after demodulation is converted back to

the serial data which should be same as the data at the transmission side.

In the second part what I am going to do is to implement the modulation

on the DSP board. In order to implement the modulation on the DSP board

we need code composer studio software which acts as interface between

user PC and DSP kit. The DSP board which we are going to use is

TMS320c6416 by Texas Instruments having 1GHz speed. This board

supports ANSI C language so we have to convert the Matlab program to

code which should be implemented on DSP hardware. In this phase first

we have to implement the OFDM modem on the single board and after the

simulation we will see the constellation mapping. During the modulation

we have to use the separate channels for the in Phase and Quadrature, so

that at the receiver side the proper synchronization is achieved during the

sampling to detect the exact beginning of the sample. The synchronization

should be proper so that data generated at the transmitter should be

same at the output of the receiver.

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64 QAM

Modulation is the process by which information signals, analog or digital,

are transformed into waveforms suitable for transmission across the

channel. Hence, digital modulation is the process by which digital

information is transformed into digital waveforms. After bit interleaving,the data bits are entered serially to the constellation mapper. The data

bits shall be modulated by using 64-QAM modulation; the encoded and

interleaved binary serial input data shall be divided into groups of NBPSC

(6) bits and converted into complex numbers representing 64-QAM

constellation points. The conversion shall be performed according to Gray

coded constellation mappings, as illustrated in the figure.

RF MODULATION

The output of the OFDM modulator generates a base band signal, which

must be mixed up to the required transmission frequency. This can be

implemented using analog techniques as shown in Figure or using a Digital

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up Converter as shown in Figure. Both techniques perform the same

operation, however the performance of the digital modulation will tend to

be more accurate due to improved matching between the processing of

the I and Q channels, and the phase accuracy of the digital IQ modulator.

A transmitted RF signal is always a real signal as it is just a variation in

field intensity. It is however possible to directly generate a real OFDM

signal. This is useful in wired applications, such as ADSL. In these

applications the transmitted signal is generally from just above DC to an

upper limit determined by the required signal bandwidth. The required

transmission signal is a real signal as only a single cable is used. If acomplex signal were used then two wires would be needed, one for the

real signal and one for the imaginary signal.

In the third phase what we should do is to use two boards, one for

transmission and one for reception. As we see in the block diagram we

directly connect the left channel of the one board to the left channel of the

other board and the right channel of one board to the right channel of theother board. Now, main thing which is very important is the design of the

receiver. The design of the receiver may change but at present in order to

understand the concept we are considering Costas loop for symbol timing

recovery. We may use guard interval/cyclic prefix to reduce inter symbol

interference. After the conversion of digital to analog signal we can up

convert the signal by multiplying the In phase signal with Sin and

Quadrature signal by Cosine function the up converted signal is then fedto the Left and Right channel of the receiver. The main purpose of the

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receiver is Synchronization, time and frequency synchronization are

paramount, respectively, to identify the start of the OFDM symbol and to

align the modulators and the demodulators local oscillator frequencies. A

perfect synchronization recovery at the receiver is one of the most

important troubles for a system based on a OFDM modulation scheme.

In the final stage we may connect two boards wirelessly as shown below in

the block diagram. In this case we also have to consider channel as well. If

the channel is wireless then there should be multipath propagation which

results in delay spread, fading and Doppler shifts. During this we may

modify our code to put some forward error correction/channel coding,

interleaving and guard interval/cyclic prefix insertion.

OFDM Synchronisation

Synchronization is a key issue in the design of a robust OFDM receiver.

Time and frequency synchronization are paramount, respectively, to

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identify the start of the OFDM symbol and to align the modulators and the

demodulators local oscillator frequencies. If any of these synchronization

tasks is not performed with sufficient accuracy, then the orthogonality of

the SCs is (partly) lost. That is, ISI and ICI are introduced. A perfect

synchronization recovery at the receiver is one of the most important

troubles for a system based on a OFDM modulation scheme. The

synchronization stadium has to be particularly accurate because it is

possible recovery information in a OFDM symbol only if the orthogonality

property between sub-carriers is restored.

The designed synchronization scheme is subdivided in three main parts:

Frame synchronization

Symbol timing recovery and fractional frequency offset correction

Coarse frequency offset correction.

The algorithm uses some correlation properties between samples

introduced by the cyclic prefix, allows to find the useful part position for

each symbol, and then to extract this part from the symbols sequence.

The extracted symbol samples do not match the orthogonality property

due to an imperfect demodulation so you cannot execute the FFT

operation. Therefore it is indispensable to recover this property estimating

and correcting the fractional frequency offset, the offset part introduced

by oscillators that causes the spectrum misalignment on the frequencies

grid for each symbol. There is also an integer component for the frequency

offset that does not concern with orthogonality between sub carriers but it

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can cause a wrong symbol demodulation: the last step of the designed

algorithm is to estimate and to correct this component too. The frequency

offset determines a sub carriers frequency shift and it is caused by the

phase difference between frequency oscillator in the receiver for down

conversion and the oscillator in the transmitter for RF up conversion. This

term is the first one cause of performance degradation of the entire

system and this loss is much more when the frequency offset value is near

the half of inter-carrier frequency.

Software Implementation

Matlab

MATLAB is a high-level language and interactive environment that

enables you to perform computationally intensive tasks faster than with

traditional programming languages such as C, C++, and FORTRAN. We

can use MATLAB in a wide range of applications, including signal and

image processing, communications, control design, test and

measurement, financial modelling and analysis, and computational

biology. Add-on toolboxes (collections of special-purpose MATLAB

functions, available separately) extend the MATLAB environment to solve

particular classes of problems in these application areas. MATLAB provides

a number of features for documenting and sharing your work. We can

integrate your MATLAB code with other languages and applications, and

distribute your MATLAB algorithms and applications.

Code Composer Studio

Code Composer Studio v4 (CCS v4) is the integrated development

environment for TI's DSPs, microcontrollers and application processors.

Code Composer Studio includes a suite of tools used to develop and debug

embedded applications. It includes compilers for each of TI's device

families, source code editor, project build environment, debugger, profiler,

simulators and many other features. The CCS IDE provides a single user

interface taking you through each step of the application development

flow. Familiar tools and interfaces allow users to get started faster than

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ever before and add functionality to their application thanks to

sophisticated productivity tools.

TMS320C6416 DSP Processor

The TMS320C64x is a 16-bit fixed-point family of packaged DSP processors

from Texas Instruments. Its instruction set is a superset of that of the

TMS320C62x and adds significant SIMD processing capabilities, among

other enhancements. The TMS320C64x family targets high-performance

applications such as wireless base stations, digital subscriber loops, multi-

line modems, ISDN modems, imaging, 3D imaging applications, video

applications, and radar and sonar systems. The fastest TMS320C64x

family members execute at 1 GHz with a 1.2-volt core supply and 3.3-volt

I/O.

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higher level modulation for lte

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