International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
STTC-OFDM Downlink Baseband Receiver for Mobile WMAN
Amaravathi Potla1 Eluri Venkata Narayana2
1
PG Student (M.Tech), Dept. Of ECE, KKR & KSR Institute of Technology & Sciences, Guntur
2
Assistant Professor, Dept. Of ECE, KKR & KSR Institute of Technology & Sciences, Guntur
____________________________________________________________________________________
Abstract— This paper proposed a STTC-OFDM system which is based on IEEE 802.16e OFDMA specification and supports
the distributed subcarrier allocation of partial usage of sub channels (PUSC) for downlink (DL) transmission. The fast Fourier
transforms (FFT) size 1048. The length of cyclic prefix (CP) is 128 sampling periods. The modulation schemes of quadrature
phase shift keying (QPSK) and 16quadrature amplitude modulation (16QAM) are supported for data subcarriers, while binary
phase shift keying (BPSK) is adopted for pilot subcarriers and preamble symbols. A DL sub-frame is composed of one
preamble symbol and 40 OFDM data symbols. The system design target is to support carry frequency offset (CFO) up to
14 ppm and is optimized to enable the vehicle speed up to 120 km/hr. The proposed baseband receiver applied in the system
with two transmit antennas and one receive antenna aims to provide high performance in outdoor mobile environments. Space
Time Block Code OFDM is designed for MIMO receivers in mobility .as the receiver is in velocity there will be a oscillator
frequency mismatch in the synchronization of the transmitter and receiver so to overcome the synchronization an carrier offset
methodology is implemented which consists of
Fractional carrier frequency Offset(FCFO) and integer carrier
offset(ICFO).block code is to estimate the signal accurately .as the blocks may get distorted due to noise they are replaced with
Trelli’s code which has error correcting capability
Keywords— Space time block code – orthogonal frequency division multiplexing (STBC-OFDM) system, STTC,
Trelli’s Coding, synchronizer, fast Fourier transforms (FFT), Modulation, Base band receiver.
I. INTRODUCTION
Most first generations systems were introduced in
the mid 1980’s, and can be characterized by the use of
analog transmission techniques and the use of simple
multiple access techniques such as Frequency Division
Multiple
Access
(FDMA).
First
generation
telecommunications systems such as Advanced Mobile
Phone Service (AMPS) only provided voice
communications. They also suffered from a low user
capacity, and security problems due to the simple radio
interface used. Second generation systems were
introduced in the early 1990’s, and all use digital
technology. This provided an increase in the user
capacity of around three times. This was achieved by
compressing the voice waveforms before transmission.
Third generation systems are an extension on the
complexity of second-generation systems and are
expected to be introduced after the year 2000. The
system capacity is expected to be increased to over ten
times original first generation systems. This is going to
be achieved by using complex multiple access
techniques such as Code Division Multiple Access
ISSN: 2231-5381
(CDMA), or an extension of TDMA, and by improving
flexibility of services available.
The telecommunications industry faces the problem
of providing telephone services to rural areas, where the
customer base is small, but the cost of installing a wired
phone network is very high. One method of reducing the
high infrastructure cost of a wired system is to use a
fixed wireless radio network. The problem with this is
that for rural and urban areas, large cell sizes are
required to get sufficient coverage.
Fig.1 shows the evolution of current services and
networks to the aim of combining them into a unified
third generation network. Many currently separate
systems and services such as radio paging, cordless
telephony, satellite phones and private radio systems for
companies etc will be combined so that all these services
will be provided by third generation telecommunications
systems.
Initial proposals for OFDM were made in the 60s
and the 70s. It has taken more than a quarter of a century
for this technology to move from the research domain to
the industry. The concept of OFDM is quite simple but
the practicality of implementing it has many
complexities. So, it is a fully software project. OFDM
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
depends on Orthogonality principle. Orthogonality
means, it allows the sub carriers, which are orthogonal
to each other, meaning that cross talk between cochannels is eliminated and inter-carrier guard bands are
not required. This greatly simplifies the design of both
the transmitter and receiver, unlike conventional FDM; a
separate filter for each sub channel is not required.
This paper investigates the OFDM scheme, and
realizes a fully functional system in software and
analysing how it is reducing the inter-symbol
interference caused by the multipath fading channels and
different effects and estimating, evaluating the
performance of it.
II. SPACE-TIME BLOCK CODING
Multiple-input multiple-output (MIMO) system
is known to exploit the antenna diversity to develop the
performances of wireless communication systems using
multiple antenna elements at the transmitter and receiver
ends. The main objective of MIMO technology is to
improve bit error rate (BER) or the data rate of the
Fig: 1 Evolution of current networks to the next
generation of wireless networks.
Orthogonal Frequency Division Multiplexing
(OFDM) is a digital multi carrier modulation scheme,
which uses a large number of closely spaced orthogonal
sub-carriers.
A single stream of data is split into parallel streams
each of which is coded and modulated on to a subcarrier,
a term commonly used in OFDM systems.
In OFDM, subcarriers overlap. They are orthogonal
because the peak of one subcarrier occurs when other
subcarriers are at zero. This is achieved by realizing all
the subcarriers together using Inverse Fast Fourier
Transform (IFFT). The demodulator at the receiver
parallel channels from an FFT block. Note that each
subcarrier can still be modulated independently.
Since Orthogonality is important for OFDM
systems, synchronization in frequency and time must be
extremely good. Once Orthogonality is lost we
experience inter-carrier interference (ICI). This is the
interference from one subcarrier to another. There is
another reason for ICI. Adding the guard time with no
transmission causes problems for IFFT and FFT, which
results in ICI. A delayed version of one subcarrier can
interfere with another subcarrier in the next symbol
period. This is avoided by extending the symbol into the
guard period that precedes it. This is known as a cyclic
prefix. It ensures that delayed symbols will have integer
number of cycles within the FFT integration interval.
This removes ICI so long as the delay spread is less than
the guard period.
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communication
by
applying
signal
processing
techniques at each side of the system. The capacity
increases linearly with the number of antennas while
using MIMO however it gradually saturates. MIMO can
obtain both multiplexing gain and diversity gain and can
help significantly increase the system capacity. The
earliest studies considering MIMO channels were
carried out by Foschini [3] and Telatar. MIMO can be
divided into two main classes, spatial multiplexing (SM)
and STC.
In a wireless communication system the mobile
transceiver has a limited power and also the device is so
small in size that placing multiple antennas on it would
lead to correlatıon at the antennas due to small
separation between them. To avoid this, the better thing
to do is to use multiple transmit antennas on the base
station and the mobile will have only one. This scenario
is known as Multiple Input Single Output (MISO)
transmit-diversity. A system with two transmit and one
receive antenna is a special case and is known as
Alamouti STBC. The Alamouti scheme is well known
since it provides full transmit diversity. For coherent
detection it is assumed that perfect channel state
information is available at the receiver. However, when
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
there is high mobility and the channel conditions are
rate is defined as R=k/p (where k is the number of
fluctuating rapidly it may be difficult to obtain perfect or
modulated symbols the encoder takes as input and p is
close to perfect estimates for the channel. To alleviate
the number of transmit antennas) for the Alamouti
this problem another space-time block coding techniques
STBC the rate equals 1.
known as DSTBC has been proposed in [4]. In this
Alamouti STBC Decoding with One Receive Antenna
technique, two serial transmitted symbols are encoded
A block diagram of Alamouti STBC decoder is
into phase differences and the receiver recovers the
illustrated in Fig. 5. At the receiver antenna, the signals
transmitted information by comparing the phase of the
r1 and r2 received over two consecutive symbol periods
current symbol with the previously received symbol.
can be written as follows:
Alamouti Code: Alamouti system is one of the first
space time coding schemes developed for the MIMO
systems which take advantage out of the added diversity
of the space direction. Therefore we do not need extra
In order to estimate the transmitted symbols
bandwidth or much time. We can use this diversity to
(two in this case) the decoder needs to obtain the
get a better bit error rate. At the transmitter side, a block
channel state information (in this work we assume we
of two symbols is taken from the source data and sent to
have perfect CSI) and also use a signal combiner as
the modulator. Afterwards, the Alamouti space-time
could be seen from Fig 3.
encoder takes the two modulated symbols, in this case
x1 and x2 and creates an encoding matrix x where the
symbol x1 and x2 are planned to be transmitted over two
transmit antennas in two consecutive transmit time slots.
The Alamouti encoding matrix is as follows:
A block diagram of the Alamouti ST encoder is shown
in Figure 2
Fig 3 Alamouti Space-Time decoder.
The channel estimates together with the outputs
from the combiner are then passed on to the Maximum
Likelihood decoder (ML) to obtain the estimates of the
transmitted
symbols.
Considering
that
all
the
constellation points are equiprobable, the decoder will
Fig 2 Alamouti Space-Time Encoder.
The Alamouti
STBC scheme which has 2
transmit and Nr receive antennas can deliver a diversity
choose among all pairs of signals ( x1,x2 ) one that
would minimize the distance metric shown below
order of 2 Nr [6]. Also, since for space time codes the
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
By substituting the above equation in below equation,
the maximum likelihood decoding can be written as
Accurate Two-Stage Channel Estimation
Two major categories of pilot-aided channel estimation
methods are interpolation-based channel estimation
methods [4] and DFT-based channel estimation methods
[7]. Interpolation-based method estimates channel
frequency response (CFR) by interpolating the received
Where, C is all probable modulated symbol pairs
pilot subcarriers. This method is not suitable for outdoor
( x1,x2 ) .x1 and x2 are formed by combining the
fast fading channels.
received signals r1 and r2 with channel state information
known at the receiver. The combined signals are given
by:
Substituting r1 and r2 from above equations, the
combined signals can be written as,
Fig. 4 Two stage Channel Estimator
A two-stage channel estimation method is used
to realize a successful STBC-OFDM system in outdoor
h1 and h2 are a channel realization, the combined
signals xi i =1,2, depends only on , i =1,2. It is possible
to split the maximum likelihood decoding rule into two
independent decoding rules for x1 and x2 as shown
below:
mobile channels. The multipath fading channel is
characterized by CIR consisting of a few significant
paths. The delays of these paths usually vary slowly in
time, but the path gains may vary relatively fast.
Therefore, in the initialization stage, the significant
paths are identified during the preamble symbol time. In
the tracking stage, the path gain variations in the
identified path positions will be tracked in the following
Since for M-PSK modulated symbols (| h1| +|h2 | 1) |
2 | , i = 1, 2 is constant for all signal points
equation (4.7) can further be simplified as:
data symbol transmission .Fig. 4 shows the architecture
of the two-stage channel estimator.
1) Initialization Stage: The operation blocks in this stage
are a preamble match, an IFFT, a straight multipath
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
interference cancellation (SMPIC)-based decorrelator,
due to subtraction, and more hardware effort is required
and an FFT. The preamble match correlates the received
for sign extension. Therefore, if the signed calculation is
signal with the frequency domain preamble symbol to
avoided, the hardware and power will be further saved.
get the preliminary CFRs of different antenna pairs.
In the proposed method, both the real and imaginary
Then, the CIR can be obtained
parts of the received sample are quantized into . The
The proposed match filter applied with the ICFO-
quantization loss is less than 0.8 dB in SNR, and it can
compensated coefficients can reduce the CFO effect and
be compensated by increasing the matching length ,
provide the precise symbol boundary detection, and the
which costs only a little hardware overhead When the
ICFO
simultaneously.
total numbers of 0’s and 1’sstored in tap registers,
• The proposed ping-pong algorithm using the estimated
denoted as and , are known, the number of -1 can also be
FCFO value can refine the ICFO value and improve the
obtained at the same time. Therefore, the matching result
accuracy.
can be calculated as
value
can
be
detected
• The proposed two-stage channel estimation can highly
improve the performance in outdoor mobile channels as
compared with the interpolation-based methods that are
According to the simulation results at the vehicle
frequently adopted in the baseband implementation.• In
speed of120 km/hr, the matching length of 300 is chosen
the initialization stage, the proposed SMPIC-based
in this case so that the symbol miss error probability
decorrelator uses a straightforward method to identify
approaches the lowest boundary. A monitor circuit is
significant paths and cancel the multipath interference,
used to count after each data updating. The tap results
which can highly reduce the implementation cost.• In the
are generated by the logical circuits and are accumulated
tracking stage, the matrix inverse computation is
to obtain by a carry save adder (CSA) tree. A logical
efficiently avoided by employing the strongly diagonal
circuit can be simplified to use only NAND gate and
property, which can highly save the computation
NOR gates. In the proposed symbol boundary detection,
complexity.
the coefficient sequence is pre-shifted with the possible
The decision of signal word lengths affects the
values of ICFO, so the ICFO can be detected
system performance and hardware complexity. The
simultaneously. The coefficient sequence is stored in
output SNR at the STBC decoder is used as a
ROM. In order to accumulate the matching results twice
performance criterion to determine the appropriate word
for ICFO detection, an additional circuit is necessary to
lengths of each building block.
store the previous matching results as shown in Fig. 6. If
Synchronizer
the control signal is positive, the registers will
In the match filter, each tap performs complex
respectively store the current matching results of the
multiplication of the coefficient and the received sample.
possible ICFO values. On the contrary, if a control
If the coefficients are quantized into, the tap operation
signal is negative, the chain of the registers works as the
can be simplified to add or subtract the received sample.
shift-registers for accumulating the matching results.
It avoids the multiplier usage and reduces the register
requirement. However, the sign calculation is necessary
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III.
The four possible states of the encoder are
PROPOSED STTC METHOD
Space Time Trellis Code Encoder:
depicted as four rows of horizontal dots. There is one
In this encoder, data bits are provided at a rate
column of four dots for the initial state of the encoder
of k bits per second. Channel symbols are output at a
and one for each time instant during the message. For a
rate of n = 2k symbols per second. The input bit is stable
15- bit message with two encoder memory flushing bits,
during the encoder cycle. The encoder cycle starts when
there are 17 time instants in addition to t = 0,
an input clock edge occurs. When the input clock edge
which represents the initial condition of the encoder.
occurs, the output of the left-hand flip-flop is clocked
The solid lines connecting dots in the diagram
into the right-hand flip-flop, the previous input bit is
represent state transitions when the input bit is a one.
clocked into the left-hand flip-flop, and a new input bit
The dotted lines represent state transitions when the
becomes available. Then the outputs of the upper and
input bit is a zero. Notice the correspondence between
lower modulo-two adders become stable. The output
the arrows in the trellis diagram and the state
selector (SEL A/B block) cycles through two states-in
transition table discussed above. Also notice that since
the first state, it selects and outputs the output of the
the initial condition of the encoder is State 002, and the
upper modulo-two adder; in the second state, it selects
two memory flushing bits are zeroes, the arrows start out
and outputs the output of the lower modulo-two adder.
at State 002 and end up at the same state.
The following diagram shows the states of the
trellis that are actually reached during the encoding of
our example 15-bit message
Fig .5 STTC Encoder
Decoding Scheme for Trellis Decoder:
The Space time trellis decoder itself is the
primary focus of this tutorial. Perhaps the single most
Fig .7 An Example of States for the trellis Code
The encoder input bits and output symbols are
important concept to aid in understanding the Space time
trellis algorithm is the trellis diagram. The figure below
shown
at
the
bottom
of
the
diagram.
Notice
shows the trellis diagram for our example rate 1/2 K = 3
the correspondence between the encoder output symbols
convolutional encoder, for a 15-bit message:
and the output table discussed above. Let's look at that in
more detail, using the expanded version of the transition
between one time instant to the next shown below:
Fig.6 The trellis diagram for our example rate 1/2 K
= 3 convolutional encoder, for a 15-bit message
Fig .8 State Transition for the trellis Code
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
The two-bit numbers labelling the lines are the
corresponding
convolutional
encoder
and 112. The metric we're going to use for now is the
channel
Hamming distance between the received channel symbol
symbol outputs. Remember that dotted lines represent
pair and the possible channel symbol pairs. The
cases where the encoder input is a zero, and solid
Hamming distance is computed by simply counting
lines represent cases where the encoder input is a one.
how many bits are different between the received
(In the figure above, the two-bit binary numbers
channel symbol pair and the possible channel symbol
labelling dotted lines are on the left, and the two-bit
pairs. The results can only be zero, one, or two. The
binary numbers labelling solid lines are on the
Hamming distance (or other metric) values we compute
right.) OK, now let's start looking at how the Space time
at each time instant for the paths between the states at
trellis decoding algorithm actually works. For our
the previous time instant and the states at the
example, we're going to use hard-decision symbol inputs
current time instant are called branch metrics. For the
to keep things simple. (The example source code uses
first time instant, we're going to save these results
soft decision inputs to achieve better performance.)
as "accumulated error metric" values, associated with
Suppose we receive the above encoded message with
states.
a couple of bit errors:
accumulated error metrics will be computed by adding
For
the
second
time
instant
on,
the
the previous accumulated error metrics to the current
branch metrics.
Proposed Architecture:
In this paper, an STTC-OFDM downlink
baseband receiver for mobile WMAN is proposed and
implemented. First, a novel match filter is proposed to
precisely detect symbol boundary. Moreover, a pingFig .9 Error Recovery using Trellis Code
pong algorithm is presented to improve the performance
of carrier frequency synchronization. Then, we propose
Each time we receive a pair of channel symbols,
we're
going
to
compute a
metric to
measure
the "distance" between what we received and all of the
possible channel symbol pairs we could have received.
Going from t = 0 to t = 1, there are only two possible
channel symbol pairs we could have received: 002, and
112. That's because we know the convolutional encoder
was initialized to the all-zeroes state, and given one
input bit = one or zero, there are only two states we
could transition to and two possible outputs of the
encoder. These possible outputs of the encoder are 00 2
a two-stage channel estimator to accurately estimate CSI
over fast fading channels [6]. The initialization stage
uses discrete Fourier transform (DFT)-based channel
estimation with the multipath interference cancellation
(MPIC)-based decorrelation to identify significant
channel paths. The proposed baseband receiver designed
in90-nm CMOS technology can support up to 27.32
Mbps downlink(uncoded) data transmission under 10
MHz channel bandwidth.
• Provision of a STTC-OFDM downlink baseband
receiver architecture that is capable of high-speed
transmission at high mobility;
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
• Integration of a simple and robust synchronizer and an
accurate but hardware affordable channel estimator to
overcome the challenge of outdoor fast fading channel;•
implementation of a successful STTC-OFDM downlink
baseband receiver for mobile WMAN.
Fig.9 Bit error rate for the signal to noise ratio
Fig. 10 Proposed block diagram of STTC Method.
The above graph is the matlab implemented
result for the ofdm architecture by increasing the fading
noise between the transmitter and reciever .the graphs
determines the linear decrease in the error rate by
increasing signal to noise ratio.
Fig. 11 Proposed OFDM system with two
transmitters and one receiver.
IV.
RESULTS AND CONCLUSIONS
The proposed baseband receiver with two transmitting
antennas and one receiver antenna is simulated on Xilinx
13.2i and then they were implemented FPGA system.
The proposed receiver effectively improves the design
complexity with acceptable hardware cost while keeping
the high performance in multipath fading channels. The
Simulation results for the proposed system are shown in
the below figures.
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Fig.10 Bit error rate with respect to the mobility of
WMAN
The above graph plotted by the matlab
determines the speed of the lan in motion .even though
the speed increases upto certain rage BER stays in the
constant by our proposed method.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
Fig.14 Simulation of STTC Encoder
Fig.11 Bit error rate with respect to noise ratio for
different antenna number
Fig.15 Simulation of STTC Decoder
Fig.12 Top module Simulation of Transmitter
The above simulation shows the input of the
transmitter and the output of the stbc ofdm transmitter.
The number of transmit antennas are two.
The proposed downlink baseband receiver for mobile
WMAN that is applied in the STTC-OFDM system with
two transmitter antennas and one receiver antenna. A
simple symbol boundary detector, a carrier frequency
recovery loop modified by the ping-pong algorithm, and
an accurate two-stage channel estimator are effectively
implemented. Although the two-stage channel estimator
requires higher hardware cost as compared with the
interpolation-based channel estimators, it has significant
performance improvement for successfully realizing the
STBC-OFDM system in outdoor mobile environments.
From the simulation results, we have shown that the
proposed receiver improves about 8.5 dB of the
normalized MSE for 16QAM modulation as compared
with that adopting the 2-D interpolation methods in
multipath fading channels. Moreover, under the vehicle
speed of 120 km/hr, the convolutional coded BER for
16QAM modulation can achieve less than 10^6 with
coded rate of 1/2.
Fig.13 Simulation of STBC Encoder Decoder
The above simulation is to find the conjugate of
the input and encoded using almouti scheme .almouti
scheme is discussed in the chapter 3 .the format of the
input is paved in the 2 transmit antenna
Fig.16 Comparison for the Existing and proposed
Method
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number1- Dec 2014
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ISSN: 2231-5381
AMARAVATHI POTLA is pursuing
her Master degree M.Tech in VERY
LARGE SCALE INTEGRATION (VLSI)
SYSTEMS in KKR & KSR Institute of
Technology & Science. She has
completed her B.Tech in ECE from Madhira institute of
technology and sciences.
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E.V.NARAYANA is working as
Assistant Professor in KKR & KSR
Institute of Technology & Science.
He has completed his Master Degree in
Vignan’s University, Guntur .
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