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07-06-2010, 12:14 AM



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So far transmission errors have been described as evil entity in communication literature. Introducing error intentionally can save power and reduce interference. This has been proved by scientists Jik Dong Kim (South Korea), Sang Wu Kim (USA) and Young Gil Kim (South Korea). It is about combined power and error control in multicarrier DS-CDMA systems which are most popular in various indoor and mobile communication systems. This paper explains new scheme devised by them along with performance comparison with older systems to prove it is better than existing systems. This work originally appeared in IEEE transactions on communications in August 2004.


A combined power control and error control coding in multicarrier direct- sequence code-division multiple-access (DS-CDMA) systems is explained in this paper. The transmission power is controlled in such a way that channel fading in each subchannel is compensated for only when the channel gains in all subchannels are above a prescribed cutoff fade depth 0; otherwise, no power is allocated for the corresponding symbols (i.e., power truncation), and erasures are generated at the receiver. The motivation for this technique is that the symbols with low channel gain is likely to be error and yet, if transmitted, consumes the energy resources and generate interference to the other users. Truncating the power for those symbols has the effect of reducing the interference to other users and allocating more power on symbols with high channel gain (there by reducing the error probability). Since block codes can correct twice as many erasures as errors, the coded performance can be improved by properly combining the power control with the error-control coding.


We consider a multicarrier DS-CDMA system with K active transmitters communicating with a common receiver (base station). The block diagrams of the transmitter and receiver are shown in Fig. below. Each packet of data is encoded by an (n, k) extended Reed-Solomon (RS) code over GF (Q), where n is equal to Q and is a power of two. In order to randomize error bursts, an ideal interleaver/deinterleaver is assumed. A code symbol (Q-ary) is converted into M (= log2 Q) parallel bits, and each bit is spread by a random sequence pk(t). The substreams are modulated on M subcarriers with a carrier spacing that provides nonoverlapping subbands. The subchannels are assumed to experience an independent flat fading. This assumption can be justified by choosing the number of subcarriers and the bandwidth of each subband, such that the carrier spacing between adjacent subcarriers, f, is greater than the coherence bandwidth, Bc, and the delay spread is less than the chip duration of each subchannel.
Let k,i be the channel power gain in the ith subchannel for transmitter k. We assume that {k, i} are independent and identically distributed (i.i.d) random variables with probability density function (pdf) given by
Where = E [k, i] for all i and k. We also assume that = k,1, k,2¦ k,M can be estimated perfectly at the receiver, and fed back to the transmitter k through a reliable feedback channel for power control. The channel state changes at a rate slow enough (slow fading) for the delay on the feedback channel to be negligible. However, the side-information error may occur if the receiver fails to identify the correct gain (due to the low SNR of pilot) or the feedback channel is not reliable.
The receiver signal r (t) at the base station can be expressed as
Where Pi( ) is the transmission power, dk,i(t) and pk(t) are the data and random spreading waveforms, respectively, fi is the carrier frequency, tk is the propagation delay and k,i is the carrier phase, all for transmitter k at the ith subchannel. We will assume a raised-cosine chip waveform with rolloff factor a, n(t) represents the thermal noise and is modeled by a zero mean white Gaussian noise with two-sided power spectral density N0/2.
If the channel power gains of all M subchannels are greater than a threshold 0 (i.e., k,i = 0, for all i), then the corresponding Q-ary code symbol is transmitted with a power Pi( ),i = 1, 2,¦.,M. Otherwise, it is not transmitted (i.e.,



Pi( ),i = 0, for all i), and an erasure is generated for the corresponding Q-ary code symbol at the receiver. Thus the probability of symbol erasure is given by

The erasure probability is also the activity factor; each user turns off its power with probability . Thus, the power truncation will reduce the average number of interfering users from K-1 to (K-1) , thereby reducing the symbol-error probability (SEP). Notice that the conventional power control corresponds to a special case of 0 being equal to zero.


Because an (n, k) RS code can correct any set of s erasures and t errors provided s+2t = n-k, the probability of incorrect decoding PE is given by
Where per and pc are the symbol (Q-ary) erasure probability and the correct symbol (Q-ary) probability, respectively. Below, we will derive the correct symbol probability pc for two types of power control.
A. Power Truncation Only (Scheme B)
In this subsection, we consider the following power control:
for some constant P. The required feedback information for this type of power control is one bit indicating whether the channel power gains of all M subchannels are greater than a threshold o (i.e., k,i = o, for all i). The special case of 0 = 0 corresponds to the conventional errors-only decoding without power control. The coherent correlation receiver calculates a decision statistic Zk,i
where T is the bit duration, and dk,i is the channel bit in the ith subchannel. The first term in (6) is the desired signal term. The second term
represents multiuser interference, where f is a random variable uniformly distributed over [0, 2p). According to the central limit theorem, the distribution of IM is approximately Gaussian with mean zero and variance
where is a constant that depends on the chip waveform, N Ë T/Tc is the processing gain, and Tc is the chip duration of each subchannel. For the rectangular chip waveform and raised-cosine chip waveform with a rolloff factor a, is 1/3 and (1- a /4)/2, respectively. The third term in (6) represents the background white Gaussian noise with mean zero and variance N0/2. Thus, Zk,i is a Gaussian random variable with
Therefore, the conditional probability pc( ) of correct symbol (Q-ary) is
In (12), we assumed that the Q-ary code symbol is correct only when all log2Q bits constituting the code symbol are correct, i.e., if atleast one bit constituting the code symbol is in error, the probability of correct symbol pc is given by (14)-(15).
In deriving (14), we assumed that the k,i™s for i=1,2,¦.,M are i.i.d. It follows from (5) and the assumption that the k,i™s for i=1,2,¦.,M are i.i.d. that the average transmission power per channel bit is
Therefore, the average received energy per information bit is
Where r=k/n is the code rate.

B. Truncated Channel Inversion (Scheme A)

In this subsection, we consider the following power control:
for some constant PR. This type of power control makes the fading channel appear as a time-variant additive white Gaussian noise (AWGN) channel during nontruncation periods. The required feedback information for this type of power control is the channel gains of all subchannels (k,1, k,2,¦¦,k,M), which is much more than what power truncation only (scheme B) requires. The special case of 0=0 corresponds to the conventional errors-only decoding with channel inversion.
It follows from (8) and (20) that the variance of the multiple access interference is
The equivalent noise spectral density Ne/2 can be then obtained form (11) and (21). Therefore, the probability of the correct symbol (Q-ary) is given by (22).
It follows form (16) and (20) that the average channel bit power PT is
The average received energy per information bit can be obtained from (18) and (23).


Fig. 1 is a plot of the probability of incorrect decoding PE versus the normalized cutoff threshold /¯. We find that there exists an optimum threshold that minimizes PE , and the optimum choice of for scheme A can reduce PE by almost two orders of magnitude, when compared with the conventional errors-only decoding with channel inversion (0 = 0). Also, scheme A provides a better performance than scheme B. This can be explained as follows.

Scheme A (per-carrier adaptation) makes the channel appear as an AWGN channel during nontruncation periods, and thus, provides a better performance over scheme B. However, if the available energy resources is limited (i.e., very low Eb/N0), then the truncation period for scheme A may be too long (i.e., too many erasures to correct), so that its decoding-error probability may become higher than scheme B.
Fig. 2 is a plot of the probability of incorrect decoding PE versus Eb/N0 with several erasure-generation methods, where the simulation results for the proposed scheme are included for the validation of the analysis. We find that the combined power control and error-control coding scheme (A and B) provide a much lower PE over the conventional error-control coding without power control (C, D, and E), particularly at high Eb/No. This is because the proposed scheme suppresses the multiuser interference

Fig. 4. Probability of incorrect decoding PE versus Eb/No: (512,170) RS code, N=64, K=30, M=9, a=0.25, A=truncated channel inversion, B= power truncation only, C= convolutional code of rate with an optimum distance profile of the generator polynomial (4 564 754) in octal number and constraint length of seven. and saves the energy resources by truncating the transmission power during unfavorable channels, and allocates the saved energy on symbols on high channel gain. shows that the combined power control and error-control coding provides a significant capacity gain over conventional schemes.shows the characteristic steep slope of the RS code versus the graceful degradation of the convolutional code.

We also find that the convolutional-coded system provides a lower PE than the RS-coded system in the low SNR region, but exhibits an error floor and provides a higher PE in the high SNR region(interference-limited region).


We explained that the probability of incorrect coding can be significantly reduced by combining the power control with the error-control coding. It is also seen that power can be saved and interference can be reduced.
How much power can be saved
In reference 4 it has been explained that for a large communication network every one dB saving in power will result in savings of many millions of dollars annually.
Will Reliance India mobile which uses CDMA technology save crores of rupees by implementing this technique
These two questions will be answered when we meet in ERODE SENGUNTHAR Engg college on 22nd & 23rd of September 2005.


2. Dr. KAMILO FEHER Wireless Digital Communications, PHI 2002
3. WILLIAM C.Y.LEE, Mobile communications engineering, 2¬¬¬nd edition MC Graw-Hill.
4. K.SAM SHANMUGAM, digital and analog communication systems, John Wiley.
Use Search at http://topicideas.net/search.php wisely To Get Information About Project Topic and Seminar ideas with report/source code along pdf and ppt presenaion
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26-10-2010, 05:00 PM

.pdf   MohitGargDDPThesis-ppt.pdf (Size: 914.8 KB / Downloads: 89)

Multi-user Signal Processing Techniques for DS-CDMA Communication

Mohit Garg (00D07015)
Guide: Prof. U. B. Desai

Multi-user signal processing techniques can be classified into two broad
• Multi-user Detection
 Receiver based schemes
 Can be used on the uplink channel
 Maximum Likelihood Multi-user Detector formulated by Verd´u (1986)
• Multi-user Transmission
 Transmitter based schemes so as to reduce complexity at the receiver
 Can be used on the downlink channel
 – Need channel knowledge at the transmitter
• The focus of this work has been towards reducing the computational burden
at the receiver. We have proposed
 + A modification to two existing multi-user detection algorithms
 + Two new multi-user transmission algorithms
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29-10-2010, 10:54 AM

[b]Design of Secure Mobile Communication using Fingerprint[/b]

Seifedine Kadry
Aziz Barbar
American University of Science and Technology
Department of Computer Science



Mobile handheld device is a popular device that provides secure, private, authentic,
and accurate communication and exchange of confidential information. In this paper we
propose a technique to solve the authenticity problem in mobile communication. This
technique is mainly based on the usage of the Fingerprint to identify both the speaker and
the sender. This technique is simple, requires less calculation than other public/private key
techniques, assures more authenticity than digital signature, and eliminates the need for a
third party. Moreover, when applied to mobile phones, this technique resists any forge
imposed by another party.

1. Introduction

A recent survey carried by Interactive Statistics Corporation (IDC) shows that around 90% of mobile
users use messaging as their main communication tool disregarding the safety level of such a
communication system; if phones are lost or shared, anyone can access the data on the phone. This is
known as the AUTHENTICITY in cryptography science. That is why, scientists should come up with a
concept that minimizes the risk associated with losing or sharing a phone, thus offering a safe
environment for communication.
This paper presents a solution for the above mentioned problem. “Fingerprint Identification
Technique” is the most effective technique for solving such a problem. This technique works on the
Fingerprint basis whereby the phone can be accessed when it identifies the Fingerprint of the user(s).
This paper is organized as follows: In section 2, we provide an overview of the secure
communication in mobile handheld device. Then, section 3 describes the digital signature scheme and
the related algorithm RSA [3]. In section 4, we write the code of the RSA algorithm in JAVA for the
performance purpose. Section 5 gives a literature review of fingerprint matching technique. Next in
section 6, we describe the proposed design which is based on the fingerprint to authenticate the caller,
the performance of our design is given in section 7 and finally section 8 concludes the paper with
future work.

for more ::->

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02-05-2011, 12:41 PM

Submitted By :
Sunil Phour

.ppt   Cellular Communication.ppt (Size: 283.5 KB / Downloads: 48)
Cellular Communication
Cellular Phone System
The cellular phone service area is divided into smaller geographical areas called cells.
Cellular phone system
Each cell has a base station with a tower which receives and transmits signals.
All the base stations are connected by phone lines to mobile telephone switching office (MTSO).
How does it work?
A caller communicates via radio channel to its base station, which sends the signal to MTSO.
If the called number is land based, MTSO sends the signal through central telephone office like any other phone call.
If the called number is mobile, MTSO sends the signal to the base station of the cell where the called number is. The base station transmits the signal to the called number using the available radio channel.
As the caller moves from one cell to another, MTSO automatically switches the user to an available channel in the new cell.
Cell Phones
Cell phones communicate in the high frequency range: 806-890 MHz and 1850-1990 MHz for the newly allocated ‘PCS’ range.
Cells are spaced 1-2 miles apart.
The concept of cells is the key behind the success of cell phones because by spacing many cells fairly close to each other, the cell phones may broadcast at very low power levels (typically 200mW-1W, depending on system).
Since the cell phones may broadcast at low power levels, they use small transmitters and small batteries.
Reuse frequencies at cells that are not adjacent.
Encoding and Multiplexing
With thousands of cellular phone calls going on at any given time, everyone cannot talk on the same channel at once.
Therefore, several different techniques were developed by cell phone manufacturers to split up the available bandwidth into many channels each capable of supporting one conversation.
Analog cellular systems use a 3 kHz audio signal to frequency modulate a carrier with transmission bandwidth 30 kHz.
FDMA (Frequency Division Multiple Access)
It is used on analog cellular systems.
When a FDMA cell phone establishes a call, it reserves the frequency channel for the entire duration of the call.
The voice data is modulated into this channel’s frequency band (using FM) and sent over the airwaves.
At the receiver, the information is recovered using a band-pass filter.
FDMA systems are the least efficient cellular system since each analog channel can only be used by one user at a time.
These channels are larger than necessary given modern digital voice compression and are also wasted whenever there is silence during the cell phone conversation.
Analog signals are also especially susceptible to noise.
Given the nature of the signal, analog cell phones must use higher power (between 1 and 3 watts) to get acceptable call quality.
TDMA (Time Division Multiple Access):

TDMA builds on FDMA by dividing conversations by frequency and time.
Digital compression allows voice to be sent at well under 10 kilobits per second (equivalent to 10 kHz).
TDMA shares the same channel with multiple sessions.
While TDMA is a good digital system, it is still somewhat inefficient since it has no flexibility for varying digital data rates (high quality voice, low quality voice, pager traffic) .
In other words, once a call is initiated, the channel/timeslot pair belongs to the phone for the duration of the call.
TDMA also requires strict signaling and timeslot synchronization.
Due to the digital signal, TDMA phones need only broadcast at 600 mW.
CDMA (Code Division Multiple Access):

CDMA uses ‘spread spectrum’ techniques.
CDMA has been likened to a party: When everyone talks at once, no one can be understood, however, if everyone speaks a different language, then they can be understood.
CDMA systems have no channels, but instead encodes each call as a coded sequence across the entire frequency spectrum.
Each conversation is modulated, in the digital domain, with a unique code (called a pseudo-noise code) that makes it distinguishable from the other calls in the frequency spectrum. Using a correlation calculation and the code the call was encoded with, the digital audio signal can be extracted from the other signals being broadcast by other phones on the network.  
Since CDMA offers far greater capacity and variable data rates depending on the audio activity, many more users can be fit into a given frequency spectrum and higher audio quality can be provide.
The current CDMA systems boast at least three times the capacity of TDMA systems.
CDMA technology also allows lower cell phone power levels (200 miliwatts) since the modulation techniques expect to deal with noise and are well suited to weaker signals.
The downside to CDMA is the complexity of deciphering and extracting the received signals.
Spread Spectrum

CDMA is a form of Direct Sequence Spread Spectrum communications. In general, Spread Spectrum communications is distinguished by three key elements:
1. The signal occupies a bandwidth much greater than that which is necessary to send the information. This results in immunity to interference and jamming and multi-user access.
2. The bandwidth is spread by means of a code which is independent of the data. The independence of the code distinguishes this from standard modulation schemes.
3. The receiver synchronizes to the code to recover the data. The use of an independent code and synchronous reception allows multiple users to access the same frequency band at the same time.
In order to protect the signal, the code used is pseudo-random. This pseudo-random code is also called pseudo-noise (PN).
Direct Sequence Spread Spectrum (DS/SS)
CDMA is a DS/SS system.
Signal transmission consists of the following steps:
A pseudo-random code is generated, different for each channel and each successive connection.
The Information data modulates the pseudo-random code (the Information data is “spread”).
The resulting signal modulates a carrier.
The modulated carrier is amplified and broadcast.
Signal reception consists of the following steps:
The carrier is received and amplified.
The received signal is mixed with a local carrier to recover the spread digital signal.
A pseudo-random code is generated, matching the anticipated signal.
The receiver acquires the received code and phase locks its own code to it.
The received signal is correlated with the generated code, extracting the Information data.
Spread Spectrum Generation
Pseudo-Noise Spreading
Bit rate of PN is much higher. (chip rate)
Spectrum of DS/SS
SS modulation is applied on top of a conventional modulation.
One can demonstrate that all other signals not receiving the SS code will stay as they are, unspread.
Properties of DS/SS
Secure Communication
The signal can be detected by authorized persons who know the PN code.
The signal power is small due to spreading (hide signal inside the noise)
Difficult to jam since it is wideband
Multiple Access
Individual users have independent, uncorrelated spreading codes
Advantages of CDMA over TDMA and FDMA
Greater capacity
TDMA and FDMA have a fixed number of slots
Frequencies can be reused in all the cells in CDMA.
No hard limit to the number of users.
Resistance to multipath fading.
Other Applications of Spread Spectrum
GPS (Global Positioning System)
Determine time, location and velocity of a person
Consists of 24 satellites to measure the exact location
Each satellite uses the same frequency band with DS/SS.
Military Applications
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02-05-2011, 02:32 PM

.ppt   ABHI.ppt (Size: 378.5 KB / Downloads: 52)
Cellular Technology
MOBILE PHONE…most popular device
Cellular Evolution
Concept first tested in Chicago in 1978
First operational in Sweden in 1981
In the US, became operational in 1983
Introduced in Canada in 1986
Until 1991, all systems were analogue
1994, PCS were introduced
Frequency Bands
Operate in the UHF range, either in:
450 MHz: Analogue
800 MHz: Analogue & Digital
900 MHz: Analogue & Digital
1400 MHz: Digital (Japan only)
1800 MHz: Digital PCN
1900 MHz: Digital PCS
What does this tell you?
how is …EXAT MODEL?
Cellular System - Why
Limited Spectrum
The cellular concept solved the problem by replacing a single, high power transmitter (large cell) with many low power transmitters (small cells). Each providing coverage to only a small portion of the service area.
Fundamental Concepts
The fundamental idea behind cellular communications is Frequency Reuse.
Question: Is this TDMA? CDMA?….
Answer: SDMA (space division multiple access)
frequencies used in one area can be reused in another area located some sufficient distance away (to avoid co-channel interference)
Geographic Layout
Theoretical 7-cell cluster arrangement
Real World Cell Shape
Each cell has a coverage area which is ~circular
(exact shape is subject to distortions from obstacles and ground topology).
Cell Frequency Distribution
Each subset of frequency pairs are then reused according to a pattern
WHAT depends on cell size?
Changing the Cell Size
Why sectorize?
Results in lower interference due to an increase in D/R ratio (means more freq in a cell)
How it works
4 Channels between BS & MS
Where am I
Every live cell phone always knows the location area via the location area identity code (transmitted from BS)
position is entered in the Home Location Register, and if roaming, in the Visitor Location Register of network
BS continually monitors signal strength of all Mobile Stations (MS) in its area.
If strength falls below a specified level, cell phone tells the Mobile Switching Centre (via the nearest Base Station), and a new BS is selected
Current generation
mobile user monitors signal strength of various cells and updates BS of strongest - much faster handoff
Goal: seamless connectivity from cell to cell without dropping or disrupting calls in progress
If required - info is exchanged via FCC & RCC
During the handoff, conversation is interrupted for less than 400 ms (not noticeable to the voice user)
Two Types of Handoffs:
Hard Handoffs
new frequency allocated (FDMA & TDMA systems)
Soft Handoffs
same frequency is retained (CDMA systems)
Whatever………is was basic!!!
Applications in……
3.GSM……[2G , 3G ,4G….]

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