Research Plan Taufiq Syobri V4 -2

8/11/2019 Research Plan Taufiq Syobri V4 -2

1/19

Spatial Coupling in Structured

Relaying for Wireless Data

ExchangeResearch Plan

Taufiq Syobri


2/19

Abstract ......................................................................................................................................................... 2

1. Background ........................................................................................................................................... 3

2. Problem Statement ............................................................................................................................... 4

3. Objective of The Research .................................................................................................................... 4

4. Related Work ........................................................................................................................................ 4

5. State of The Art ..................................................................................................................................... 5

5.1. Taxonomy of Paper ....................................................................................................................... 5

5.2. Research Position .......................................................................................................................... 9

5.3. Contribution ................................................................................................................................ 11

6. Background Theory ............................................................................................................................. 12

6.1. Relay Communication System Network...................................................................................... 12

6.2. Spatial Coupling .......................................................................................................................... 14

6.3. Network Coding .......................................................................................................................... 15

7. Research Time Schedule ..................................................................................................................... 16

8. Expected Result ................................................................................................................................... 16

9. Conclusion ........................................................................................................................................... 17

10. Biography ........................................................................................................................................ 17

11. Reference ........................................................................................................................................ 18


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Abstract

In this proposal, new decoding scheme will be studied in this research. The new decoding scheme will

be implemented on spatial coupling in structured relaying for wireless data exchange in central network

node. Basic network topology in this research is Star Structured network. Star structured network is

formed by one central network and more than 2 users that access the relay system. Data exchange will

be divided into 2 phases such as multiple access channel (MAC) phase and broadcast channel (BC)

phase. Data that flow in network will have finite length code. The new decoding scheme has property

such as adaptive decoding process, using one encoder and decoder, and low complexity of decoding

algorithm. Adaptive decoding process from this decoding scheme will make implementation of this

decoding in any condition of spatial coupling that without error free so it can be implemented in the

application in real world. The adaptive decoding process is also expected to increase spectral efficiency

with better performance. This decoding scheme that uses one encoder and decoder makes simple

communication network. The low complexity of decoding algorithm can reduce latency in

communication network so it will increase data rate and channel capacity. Because of advantage of

decoding scheme in this research , it has potential application for future communication technology.

Keyword: Relay System, Spatial Coupling, Adaptive decoding scheme , Spectral efficiency, Finite length

code,Star structured network .


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1. Background

Development of telecommunications in nowadays is focused on a mobile device. Advanced

development in telecommunications technology leads everyone in the world connected with each other

very well. One of the most important in mobile communication is about interconnection of mobile

equipment that be able to be covered by a BTS. interconnection of mobile equipment that be able to be

covered by a BTS can have bad performance if users are outside of the coverage of BTS. Relay system is

a system that can increase a coverage BTS. Relay system that connected each other can make

information flow from one node to another node with large coverage. The information flow that flown

in a big relay system network continuously can form a very big information coding if it is seen from far

distance. This communication scheme is expected to be future communication system in the world.

There are several issue in relay communication such as complexity of network, efficiency of

communication network compared with point to point communication, and spatial coupling without

error free. Because relay communication has good prospect in communication network and there are

several issue in relay communication, Research that will be done focuses on relay communication

network in order to solve the issues.

The research will focus on spatial coupling in structured relaying for wireless data exchange. Basic

topology model in this research is Star structured network topologies with a central relay. Spatial

coupling that happened in each node that connected each other, star network, and finite block length

code will be main components for this research. New network decoding strategies that studied in this

research. The new decoding scheme has property such as adaptive decoding process, using one encoder

and decoder, and low complexity of decoding algorithm. Adaptive decoding process from this decoding

scheme will make implementation of this decoding in any condition of spatial coupling that without

error free so it can be implemented in the application in real world. The adaptive decoding process is

also expected to increase spectral efficiency with better performance. This decoding scheme that uses

one encoder and decoder makes simple communication network. The low complexity of decoding

algorithm can reduce latency in communication network so it will increase data rate and channel

capacity.


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2. Problem Statement

Problem statement in this research as follows:

1)

How is performance of adaptive decoding scheme in any condition of coupling that without

error ?

2)

How is to reduce complexity of decoding algorithm in order to reduce latency in decoding

process ?

3)

How is to increase performance of decoding scheme with one encoder and decoder ?

3. Objective of The Research

Objective of this research as follows :

1)

Determine performance of adaptive decoding scheme in any condition of coupling that without

error

2)

Determine the way about reducing complexity of decoding algorithm in order to reduce latency

in decoding process.

3)

Determine the way about increase performance of decoding scheme with one encoder and

decoder.

4.

Related WorkResearch to be conducted is intended to support the project star code "Structure Relaying for Global

Wireless Data Exchange". Project star code has several issues include the following spatially correlated

signal, effect of finite block length, and further that strategy related to the level of communication such

as coding and scheduling field. Objective of this research is for increasing spectral efficiency in any

condition of spatial coupling that without error free, low complexity of decoding algorithm in order to

reduce latency of decoding process, and reducing complexity of relay communication network.


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5. State of The Art

5.1. Taxonomy of Paper

Title : Three-way Relaying Systems Using Iterative Spatial DemappingAuthor : K.Anwar and T.Matsumoto

Main

discussion

: The research in this paper studies about iterative spatial demapping scheme. The

scheme is proposed for simultaneous data exchange in three way relaying systems

where each user does not have direct links to the other users. The proposed structure

uses two-state memory 1 convolutional code for each user.The performances are

evaluated by computer simulations in AWGN and two cascaded frequency-flat block

Rayleigh fading channel. Bit-error-rate (BER) performance results show that clear turbo

cliff can be achieved, with a transmit power close enough to the theoretical limit, for

each user in AWGN channel. The result of research is the ISM demapper can distinguish

simultaneously the transmitted information, which allows the three users to exchange

information simultaneously within only two transmission phases [1] .

Scope of

research

: Structure of iterative spatial demapping and decoding so that the data

exchange is made possible only in with two transmission phases such as

multiple Access Channel ( MAC) and Broadcast Channel (BC)

Focus in single carrier transmission

The relay amplify-and forwards (AF) the message from each user and broadcast

the composite signal to all users during BC Phase

BPSK modulation and no pre-processing before transmission

Transmit power is same for all user

The variance of AWGN with each user is also assumed to be 1.

Each user can subtract-off their own symbols that reduces the computation of

symbol detections

Further

Work

: Because the channels in three-way relaying systems can be seen as a

concatenation of MAC and BC channels, the degradation in average BER and SER

compared with that in P2P communications are unavoidable in the exchange of

benefiting the simultaneous data exchange within only two transmission phases. It

is challenge to improve decoding strategy so degradation BER and SER is avoidable

[1] .

When difference phase of two channels are 0 or the number of users increase, it is

difficult to extract the information from received symbol. So it is challenge to

extract symbol when difference phase of two channels are 0 or the number of

users increase [1] .


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Title : Joint Compute and Forward for the Two Way Relay Channel with Spatially Coupled

LDPC Codes

Author : Brett Hern and Krishna Narayanan

Main

discussion

: The research in this paper studies about design and analysis of coding scheme for

binary input two way relay channel with erasure noise. The research in this paper

proposes a decoding paradigm called joint compute and forward. The paradigm isimplemented in spatially coupled LDPC ensembles, This paradigm can achieve better

decoding performance than decode forward paradigm and compute forward paradigm

with single encoder and single decoder. The result in this research also shows that the

class of punctured spatially coupled LDPC codes can be used to obtain a rate of max

(RDF;RCF) over the entire range of channel parameters, i.e., which it is not required to

use different degree distributions of LDPC codes for the different rates and channel

parameters. It suffices to use a single spatially coupled LDPC code and puncture this

code until the rate is close to max (RDF;RCF) for given channel parameters [2] .

Scope of

research

: The decoding paradigm in this research is Joint Compute and Forward (JCF)

Reliable physical layer network coding in which relay performs perfect error

correction prior to forwarding message

Binary input two way relay with erasure noise

Focus of the research is specifically on the achievable computation rates of

Low Density Parity Check (LDPC) code ensembles and message passing

decoding

The research proposes a class of two-way erasure multiple access channels

(TWEMAC) for which it can exactly analyze the performance of the JCF

message passing decoder. TWEMAC

The state of the channel is assumed to be known to the relay but unknown at

nodes A and B

Further

Work

: It is challenge for The universality of spatially coupled codes allows a single

encoder and decoder to achieve any currently known equal exchange rate [2] .

Title : Finite-length performance of spatially-coupled LDPC codes under TEP decoding

Author : Pablo M. Olmos, Fernando Perez-Cruz, Luis Salamanca, Juan Jose Murillo-Fuentes

Main

discussion

: The research in this paper studies about Spatially-coupled LDPC code. Spatially-coupled

(SC) LDPC codes are constructed from a set of L regular sparse codes of length M. In

the asymptotic limit of these parameters, SC codes present an excellent decoding

threshold under belief propagation (BP) decoding, close to the maximum a posteriori

(MAP) threshold of the underlying regular code, but In the finite-length regime, it

needs both dimensions, L and M, to be sufficiently large, yielding a very large code

length and decoding latency. The research shows that the finite-length performance of

SC codes is improved if it considers the tree-structured expectation propagation (TEP)

algorithm in the decoding stage. When TEP algorithm is applied to the decoding of SC

LDPC codes, it allows using shorter codes to achieve similar error rates. The Research

also proposes a window-sliding scheme for the TEP decoder to reduce the decoding

latency [3].

Scope of

research

: Binary Erasure Channel

Finite length LDPC codes


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TEP Decoder

Sliding Window TEP Decoder

LDPCC is used for a representative example of spatially-coupled codes

Further

Work

: Gain for LDPCC code, a representative example of spatially-coupled codes , is still

needs much longer code therefore it can be exploited either to improve the Word

Error Rate (WER) or the latency by reducing the code length [3] .

Title : Spatially Coupled LDPC Codes for Two-User Decode-and-Forward Relaying

Author : Stefan Schwandtery, Alexandre Graell i Amatx, and Gerald Matzy

Main

discussion

: The research in this paper studies about decode-and-forward transmission scheme that

is based on spatially coupled LDPC codes and applies to a network consisting of two

sources, one relay, and one destination. The scheme has been proved in this research

analytically that the proposed scheme achieves the Shannon limit on the binary

erasure relay channel for symmetric channel conditions. Using density evolution in this

research, the scheme approaches capacity also for asymmetric channel conditions [4] .

Scope ofresearch

:

Binary Erasure Channel TDMA Relay Channel

Decode and Forward Relaying Scheme

Using Spatially Coupled LDPC code (SC-LDPC Code)

Design of research model is bilayer SC-LDPC codes for a half duplex DF relaying

system with two sources, one relay, and one destination

Asymmetric and symmetric channel condition

Further

Work

: It challenge to develop a scheme in asymmetric channel condition for different

channel model like AWGN or fading channel that achieves the Shannon limit

Capacity using same model in this research [4] .

Title : On the Block Error Probability of Finite-Length Codes in Decentralized Wireless

Networks

Author : Cecilia G. Galarza, Pablo Piantanida, and Marios Kountouris

Main

discussion

: The research in this paper studies about block error probability of large decentralized

wireless networks for given code length and rate. The network model in this research

consists of a large number of nodes,distributed according to a homogeneous Poisson

point process. The transmitted signals are attenuated due to both path loss and fading

emitting their messages independently from the others. The research in this paper

shows that when the code length is long enough (asymptotic regime) and users

communicate with Gaussian codebooks, the error probability between any pair of

nodes in the network behaves as the well-known probability of outage and in the non-asymptotic regime, it bounds the block error probability as a function of the code

length and the rate [5] .

Scope of

research

: Decentralized network

Fixed code length

signal attenuation occurs due to path loss and fading

Observe outage probability for asymptotic regime and non-asymptotic regime

Error probability as a function of code length and rate


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Planar network model

Messages are uniformly distributed

Analysis in the research is performed during a single time slot considering a

snapshot of the network

Research is also focused about the interaction between the block length and

the spatial densityFurther

Work

: The further work in this research is to explore in the context of large spatial

networks [5] .

Title : Robust error correction for real-valued signals via message-passing decoding and

spatial coupling

Author : Lenka Zdeborova, Pan Zhang, Jean Barbier and Florent Krzakala

Main

discussion

: The research in this paper studies about error correction scheme of real-valued signals

when the codeword is corrupted by gross errors on a fraction of entries and a small

noise on all the entries. Combining the recent developments of approximate message

passing and the spatially-coupled measurement matrix in compressed sensing, theresult of research shows that the error correction and its robustness towards noise can

be enhanced considerably. Scheme of research is to combine a Bayesian AMP

(Approximate Message Passing) reconstruction and spatially coupled decoding

matrices. The scheme shows that the scheme is robust to non-sparse small noise.

Research in this paper computes the phase diagram in the limit of large signal sizes and

showed numerically that the probability of failure decreases exponentially in the signal

size [6] .

Scope of

research

: Error correction scheme of real-valued signals when the codeword is corrupted

by gross errors on a fraction of entries and a small noise on all the entries.

Scheme of research replaces the convex-relaxation decoding by the Bayesian

Approximate Message-Passing (AMP) decoder that uses the available priorinformation about the error vector.

Scheme of research considers a quasi-sparse channel where, in addition to the

gross errors on a fraction of elements, there is a small additive random white

noise, and in the lines of show that the performance of AMP decoder is stable

under this additional noise.

Scheme of research use spatially-coupled measurement matrices in the

decoding.

Research of this paper relies on the development of the Bayesian AMP

algorithm, whose behavior for large signal sizes can be studied rigorously using

the state evolution technique; on the development of spatially coupled error

correcting codes on binary variables

Further

Work

: Enhancement of error correction scheme uses spatially-coupled measurement

matrices decoding up to its information theoretical limit in the case of strictly

sparse noise [6].

Improvement AMP decoder in order to decrease execution time [6].

Joint source and channel coding is studied when signal is itself compressible

[6].


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5.2.

Research Position

No Title of Paper

Focus of Research

Spectral

Efficiency

Error

CorrectionScheme

Channel

Capacity

Decoding

Scheme

1 Three-way Relaying Systems Using

Iterative Spatial Demapping

V V

2 Joint Compute and Forward for the

Two Way Relay Channel with Spatially

Coupled LDPC Codes

V

3 Finite-length performance of spatially-

coupled LDPC codes under TEP

decoding

V

4 Spatially Coupled LDPC Codes for Two-

User Decode-and-Forward Relaying

V V

5 On the Block Error Probability of Finite-

Length Codes in Decentralized Wireless

Networks

V

6 Robust error correction for real-valued

signals via message-passing decoding

and spatial coupling

V

7 My Research V V V


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No Title of Paper

Scheme of Research

Single Carrier

Transmission

Multi Carrier

Transmission

Finite

Length

Code

Relay

Scheme

1 Three-way Relaying Systems Using

Iterative Spatial Demapping

V V


Two Way Relay Channel with

Spatially Coupled LDPC Codes

V

3 Finite-length performance of

spatially-coupled LDPC codes under

TEP decoding

V

4 Spatially Coupled LDPC Codes for

Two-User Decode-and-Forward

Relaying

V V

5 On the Block Error Probability of

Finite-Length Codes in

Decentralized Wireless Networks

V V

6 Robust error correction for real-

valued signals via message-passing

decoding and spatial coupling

V

7 My Research V V V

No Title of Paper

Relay Scheme of Research

Amplify

and

forward

Decode

and

forward

Compute

and Forward

Joint Compute

and Forward

1 Three-way Relaying Systems UsingIterative Spatial Demapping

V


Two Way Relay Channel with Spatially

Coupled LDPC Codes

V V

3 Finite-length performance of spatially-

coupled LDPC codes under TEP

decoding

4 Spatially Coupled LDPC Codes for

Two-User Decode-and-Forward

Relaying

V

5 On the Block Error Probability ofFinite-Length Codes in Decentralized

Wireless Networks

6 Robust error correction for real-

valued signals via message-passing

decoding and spatial coupling

V

7 My Research V


12/19


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6. Background Theory

6.1. Relay Communication System Network

Relays that receive and retransmit the signals between base stations and mobiles can be used to

increase throughput extend coverage of cellular networks. Infrastructure relays do not need wired

connection to network thereby offering savings in operators backhaul costs. Mobile relays can be used

to build local area networks between mobile users under the umbrella of the wide area cellular

networks [7] .

Figure 3. Relay Communication System [7]

Amplify-and-forward (AF) relays retransmit the signal without decoding while decodeand-forward (DF)

relays decode the received signal, encode the signal again, and transmit. Furthermore, relays can

operate in half-duplex mode, i.e. they do not transmit and receive simultaneously in the same band, or

in full-duplex mode. The latter operation requires a spatial separation between transmit and receive

antennas to reduce loop-back interference from the transmit antennas to the receive antennas [7].

From signal processing point of view AF relays offer interesting challenges, especially when the AF relay

operates in full-duplex mode: Adaptive algorithms are required for loop-back interference cancellation.

Furthermore, the effect of interference must be incorporated into analytical performance studies.

Spectral shaping of the transmitted signal requires advanced techniques for digital filter design. The

research benchmarks AF relays with DF relays taking into account the aforementioned issues. We

cooperate with High-frequency and microwave engineering group to gain understanding of the actual

propagation environment and loop-back interference with full-duplex relays [7]


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Basic information theory on relays results date back to 1970s. The capacity of the setup below, where

the destination is able to hear both source and relay remains unsolved in general case. Several upper

and lower bounds have been presented for the general case, and capacity has been solved in some

special cases, e.g. on degraded relay channel [7].

Figure 4. Basic Diagram of Relay Communication System [7]

In recent years cooperative relay techniques have received a lot of interest.. A typical link-level setup is

depicted below, in which a group of relays help the communication between source and destination.

The relays can then use a space-time code or the most reliable relay can be chosen to transmit the signal

while the other relays suspend transmission [7].

Figure 5. Relay Coperative Diagram [7]

Practical issues of cooperative schemes like signaling between relays and different propagation delays

due to different locations of relays are often overlooked. If the difference in time of arrival between

the direct path from source to destination and the paths source-relay-destination is constrained then

relays must locate inside the ellipsoid as depicted below. Thus, in practice, such a cooperative system

should be a narrow band one, or guard interval between transmitted symbols should be used to avoid

inter symbol interference due to relays [7].


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6.2.

Spatial Coupling

Spatial coupling is a technique introduced by Kudekar et. al. to explain the performance of convolutional

LDPC codes. In this article we only consider transmission over a binary erasure channel using (l,r) regular

LDPC codes as the base ensemble. The MAP threshold of the ensemble can be computed from the BP

GEXIT curve using the area theorem. It is known that the MAP threshold of the (l,r) ensemble

approaches the channel capacity with increasing l. Spatial coupling allows us to construct ensembles

from the base ensemble, whose BP and MAP thresholds are close to the MAP threshold of the

underlying ensemble. This phenomenon is called threshold saturation. So spatially coupled codes can be

used to transmit information at rates arbitrarily close to capacity for the BEC. Threshold saturation has

also been observed for more general channels. In figures below are different between uncoupled code

and coupled code chain for LDPC code [8].

Figure 6. Uncoupled Code Chain [8]

Figure 7. Coupled Code Chain [8]

Density evolution analysis of spatially coupled codes typically assumes that the chain-length L is kept

fixed while the lifting factor M tends to infinity. In practice, we are interested in optimizing the

performance for finite L and M. To first order, one might wonder for which scaling L=f(M) we optimize

the asymptotic performance. Empirical observations indicate that the threshold saturation phenomenon


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happens even when the number of sections grows considerably faster than M, which suggests that the

threshold saturation phenomenon is very robust [8].

6.3. Network Coding

Network coding technology was proposed in year 2000 by R.Ahlswede, and it is an information exchange

technology which combines coding and routing. The message sent from the source through the

intermediate nodes does not perform any processing just simply be stored and then forwarded to the

sink node in conventional computer communication network, but network coding technology encodes

the transmitted message by using the intermediate nodes rather than only at the store-and-forward,

which can realize maximum transmission capacity in theory and improve the utilization of the link

bandwidth. In bellow figure is example of network coding [9].

Figure 8. Butterfly Network Coding [9]

Figure shows the butterfly network model as an example of network coding, the capacity of each link is

1, S is the source node, X and Y are the sink nodes, V,M,W and Z are the intermediate nodes. According

to the Max-Flow Min-Cut bound, X and Y can receive information a and b sent from S at the same time

in theory. The traditional routing method is on the left image, which needs to use the link between M

and V twice if X and Y all both receive information a and b. X and Y receive a total of three bits of

information, so the rate is 1.5 bit/unit time. M perform XOR operation to the information on the right

image, X can achieve b through a(b a), let the rate reaches to 2 bit/unit time, so the broadband

utilization increased by 33% [9].


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Network coding can make use of other network links except the multi-cast tree to disperse network flow

and balance network load to extend network lifetime. Simultaneously network coding can ensure the

security of the data from a certain extent, since people can only achieve original data by knowing how to

decode [9].

Applying network coding to the wireless sensor network, the liner network encoding is sufficient to

acquire network capacity, but liner network coding can be applied to the actual when it only uses

random coefficients]. Chou proposes a coding scheme which uses random coefficients generated by the

intermediate nodes to multiplies the same number of packets and form a new packet, but it will bring

heavy burden since the nodes will consume too much power for transmitting data which is equivalent to

the number of nodes. From another perspective, this in turn provides an opportunity for the

combination of network coding and compressed sensing. In addition, network coding have the

probability of decoding failure [9].

7. Research Time Schedule

Table 1. Research time schedule

1st

Year 2nd

Year 3rd

Year

Paper Minimal 1paper

Minimal same as 1

st

year but I hope Icould produce more than before

Minimal same as 2

nd

year but I hope Icould produce more than before

Journal 1 Journal Minimal same as 1st

year but I hope I

could produce more than before

Minimal same as 2nd

year but I hope I

could produce more than before

8. Expected Result

Research that will be done focuses on relay node with the input finite length code. The research will

studied about decoding scheme in relay node for relay communication. The new decoding scheme has

property such as adaptive decoding process, using one encoder and decoder, and low complexity of

decoding algorithm. Adaptive decoding process from this decoding scheme will make implementation of

this decoding in any condition of spatial coupling that without error free so it can be implemented in the

application in real world. The adaptive decoding process is also expected to increase spectral efficiency


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with better performance. This decoding scheme that uses one encoder and decoder makes simple

communication network. The low complexity of decoding algorithm can reduce latency in

communication network so it will increase data rate and channel capacity.

9. Conclusion

The new decoding scheme that implemented on spatial coupling in structured relaying for wireless data

exchange will be developed in this research. The new decoding scheme has property such as adaptive

decoding process, using one encoder and decoder, and low complexity of decoding algorithm. This new

decoding scheme will increase spectral efficiency, reduce latency decoding process, simplify relay

communication network, and increase channel capacity. By reducing latency decoding process with

reducing code length and low complexity decoding algorithm, it will increase data rate so it impacts on

increasing channel capacity and spectral efficiency. By using single encoder and decoder in relay node,

relay communication system will be simple. Because it has advantage on spectral efficiency, capacity

channel, simple relay communication network and low latency, it has potential to be future

communication system in the world.

10. Biography

My name is Taufiq Syobri. I was born at August 11, 1989 in Medan. I obtained my

Bachelor Degree at ITB on July 2011 with major Telecommunication Engineering and

obtained my master degree on July 2012 with Cum Laude Predicate with major

Electrical Engineering option Telecommunication Engineering. My Interest research are

Signal Processing, Wireless Communication. Radar and Navigation, and Antenna

Propagation.


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11. Reference

1.

K.Anwar and T.Matsumoto, Three-Way Relaying Systems Using Iterative Spatial Demapping,

In 7th

International Symposium on Turbo Codes and Iterative Information Processing ,ISTC 2012.

2.

B.Hern and K.Narayanan, Joint Compute and Forward for the Two Way Relay Channel with

Spatially Coupled LDPC Codes,Department of Electrical and Computer Engineering Texas A&M

University College Station TX 77843, U.S.A, 26 May 2012.

3.

P. M. Olmos, F. P.Cruz, L. Salamanca, and J. J. M. Fuentes, Finite-length performance of

spatially-coupled LDPC codes under TEP decoding , IEEE Information Theory Workshop, 2012.

4.

S. Schwandtery, A.G.i Amatx, and G. Matzy, Spatially Coupled LDPC Codes for Two-User

Decode-and-Forward Relaying , 7th International Symposium on Turbo Code and Iterative

Information Processing (ISTC), 2012.

5.

C.G.Galarza, P.Piantanida, and M. Kountouris, On the Block Error Probability of Finite-Length

Codes in Decentralized Wireless Networks, Forty-Ninth Annual Allerton Conference Allerton

House, UIUC, Illinois, USA, September 28 - 30, 2011.

6.

L. Zdeborova, P. Zhang, J. Barbier and F. Krzakala, Robust error correction for real-valued

signals via message-passing decoding and spatial coupling , http://arXiv.org /pdf/1304.6599,

24 April 2013.

7.

https://sites.google.com/site/tkksigresearch/Home/research/relays, accessed on 12 June 2013

at 12.41 Indonesia Time.

8.

http://ita.ucsd.edu/wiki/index.php/Spatially_coupled_codes,accessed on 12 June 2013 at 12.49

Indonesia Time

9. J.Xiong, J.Zhao, and L. Xuan,Research On The Combining Of Compressed Sensing and Network

Coding In Wireless Sensor Network , Journal of Theoretical and Applied Information

Technology, 31st

January 2013. Vol. 47 No.3.
http://ita.ucsd.edu/wiki/index.php/Spatially_coupled_codeshttp://ita.ucsd.edu/wiki/index.php/Spatially_coupled_codeshttp://ita.ucsd.edu/wiki/index.php/Spatially_coupled_codes

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Research Plan Taufiq Syobri V4 -2