Security Sinusoidal Transform Of Speech Coding For Mobile Communication

Security Sinusoidal Transform Of Speech Coding For Mobile Communication


This project security sinusoidal transform of speech coding for mobile communication centers on the transformation of speech codes used in communication. Speech coding is the efficient representation of speech on digital form. It is one of the key technologies in current and evolving digital cellular and wireless voice communication offerings. The speech coders in existing standards exhibit a level of sophistication and performance unimaginable just 15 years ago. Chapter one tends to look at the introduction of the topic and the characteristics of mobile communications. It also looks at the statement of the problem, why the study is being carried out, significance of the study and the limitations of the study imposed by the wireless channel and by background impairments. Chapter two looks at the literature review of previous researchers on the project topic. Chapter three looks at the presentation of approaches to address their resulting effects by researchers. Chapter four discusses the designing of speech codes. Finally, chapter five summarizes the project topic in a nutshell. It also discusses the conclusion and recommendation made by researchers for future research in speech coding for mobile communication problem


Title page
Certification = = = = = = = = i
Dedication = = = = = = = = ii
Acknowledgment = = = = = = = iii
Abstract = = = = = = = = = iv
Table of content = = = = = = = v
Chapter one
1.1 Back ground of the study == = = = = 1
1.2 Characteristics of mobile communication with respect to speech coders = = 5
1.3 Statement of problem = = = = = 9
1.4 Purpose of the study = = = = = 11
1.5 Significance of the study = = = = 12
1.6 Limitation of the study = = = = 13
1.7 Definition of terms = = = = = 14
Chapter two
Literature review
2.0 Introduction = = = = = = = 16
2.1 source coding and rate distortion theory = = 16
2.2 analysis-by-synthesis speech coding = = = 20
2.3 transform coding = = = = = = 24
2.4 security sinusoidal coding = = = = = = 27
2.5 relative merits and demerits of different coding strategies = = = = = = = = = 29
Chapter three
3.0 research methodology = = = = = 34
3.1 system investigation = = = = = = 34
3.2 method of data collection = = = = = 35
3.3 interview method = = = = = = 35
3.4choosing an appropriate spectral representation= = 37
3.5 preprocessing = = = = = = = 42
35.1 Pre-emphasis = = = = = = = 42
3.5.2 Band width expansion = = = = = 43
3.5.3 High frequency compensation = = = = 44
3.6 vector quantification of LPC parameters = = 45
3.5.1 stochastic vector quantification
3.5.2 techniques exploiting interface correlations selective encoding of sub-vectors
3.6 constrained (suboptimal) vq
3.6.1 the structured vq
3.6.2 classified vq
3.6.3 product code vq
3.6.4 basis vector vq
3.6.5 multi-stage vq
3.6.6 partitioned vq (split vq)
Chapter four
4.0 result presentation and discussion
4.1 multi-stage vq of LPC parameters
4.2 suboptimality of sequential search
4.2.1 optimality conditions for sequential search
4.3 search strategy
4.3.1 search complexity
4.3.2 detailed analysis of the search complexity
4.4 codebook design
4.4.1 controid computation
4.4.2 Outlier weighting
4.5 choices of parameter representation and distance measure
4.6 performance and complexity trade-offs
4.7 robustness issues
4.7.1 Effect of language and input spectral shape
4.7.2 Performance in the presence of channel errors
4.8 Improved codebook designs for multi stage vq
4.8.1 Iterative sequential design
4.8.2 Simultaneous Joint Design
4.9 A Low Rate Spectral Excitation Coder
4.9.1 Recent Development in MSVQ
Chapter five
5.0 Summary, Conclusion and Recommendation
5.1 Summary
5.2 Conclusion
5.3 Recommendation




The introduction of speech coding for mobile communication through security sinusoidal transformation. Speech coding is the application of data compression of digital audio signal containing speech. Speech coding uses speech-specific parameter estimation using audio signal processing techniques to model the speech signal, combined with generic data compression algorithms to represent the resulting modelled parameters in a compact bitstream. The two most important applications of speech coding are mobile telephony and voice over IP.

The techniques employed in speech coding are similar to those used in audio data compression and audio coding where knowledge in psychoacoustics is used to transmit only data that is relevant to the human auditory system. For example, in voice band speech coding, only information in the frequency band 400HZ to 3500Hz is transmitted but the reconstructed signal is still adequate for intelligibility.

Speech coding differs from other forms of audio coding in that speech is a much simpler signal then most other audio signals, and a lot more statistical information is available about the properties of speech. As a result, some auditory information which is relevant in audio coding can be unnecessary in the speech coding context. In speech coding, the most important criterion is preservation of intelligibility and pleasantness of speech, with a constrained amount of transmitted data. The intelligibility of speech includes, the actual literal content, speaker identity, emotions, intonation, timbre etc. In addition, most speech applications require low coding delay, as long as coding delays interfere with speech interaction.

Communication is the exchange of thoughts, messages or information, as by speech, signals, writing or behaviour. It is derived from the latin word.

“Communis”, which means to share. Communication requires a sender, a message and a recipient, although the receiver need not be present or aware of the sender’s intent to communicate at the time of communication, thus communication can occur across vast distances in time and space. Communication requires that the communicating parties share an area of communicative commonality. The communication process is complete once the receiver has understood the message of the once the receiver has understood the message of the sender. Feedback is critical to effective communication between participants. Bandwidth is a key concept in many telephony applications. In radio communications, for example, band width is the frequency range occupied by a modulated carrier wave, whereas in optics, it is the width of an individual spectral line or the entire spectral range.

In many signal processing contexts, bandwidth is a valuable and limited range of frequencies. A government agency may apportion the regionally available bandwidth to broadcast license holders so that their signals do not mutually interfere.

For different applications there are different precise definitions for bandwidth. It could be defined as the range of frequencies beyond which the frequency function is zero. This would correspond to the mathematical notion of the support of a function. Bandwidth can also be referred to as the frequencies where the frequency function is small.

Bandwidth typically refers to base band or as a pass band for communication systems. 


There are a number of additional characteristics of mobile communication, some of which are closely linked with handover.

The most important characteristics includes:

       The initial timing advance is obtained by monitoring the RACH from the mobile which contains only access bursts with a long guard interval of 68.25 bit periods. This ensures that there will not be any overlap problems for a mobile separation from the base station of up to 37Km.

The required timing advance is specified in terms of bit periods by a 6 bit number transmitted on the SACCH. This means that an advance between 0 and 63 bit periods can be requested.

To overcome the problem of long duration fades, the sequence of bursts making up a traffic channel are cyclically assigned to different carrier frequencies defined by the base station. Timing signals are available at the base and mobile to keep transmitters and receivers in synchronism on the defined hoping sequence. An advantage of slow frequency hopping. Is that, C0-channel interference is more evenly spread between all the mobile stations.

This has two advantages which includes:

Discontinues reception may be employed to conserve battery power when a mobile is in the stand by mode. The paging channel on the downlink CCCH is organized in such a way that the mobile needs to listen only to a subset of all paging frames. Hence a mobile can be designed to make the receiver active only when needed.


    When the mobile phone or data device is turned on, it registers with the mobile telephone exchange, or switch, with its unique identifiers, and can then be alerted by mobile when there is an incoming telephone call. The handset constantly listens for the strongest signal being received for the surrounding base stations, and is able to switch seamlessly between sites. As the user moves around the network, the “handoffs” are performed to allow the device to switch sites without interrupting the call.

Cell sites have relatively low-power radio transmitters which broadcast their presence and delay communications between the mobile handsets and the switch. The switch in turn connects the call to another subscriber of the same wireless services provider or to the public telephone network, which includes the networks of other wireless carriers. Many of these sites are camouflaged to blend with the existing environments, particularly in scenic areas.

The dialogue between the handset and the cell site is a stream of digital data that includes digitized audio (except for the first generation analog networks). The technology that achieves this depends on the system which the mobile phone operator has adopted. These technologies are grouped by generation. The first generation systems started in 1979 with Japan, and are all analog and include AMPS and NMT. Second generation systems started in 1991 in Finland, and are all digital and include GSM, CDMA and TDMA.


The objective of this study is to help us know the importance of mobile communication, which facilitates individual subscribers to travel globally with continuous personal communications.

Much of the later work in speech compression was motivated by military research into digital communications for secure military radios, where very low data rates were required to allow effective operation in a hostile radio environment. At the same time, far more processing power was available, in the form of VLSI integrated circuits, than was available for earlier compression techniques. As a result, modern speech compression algorithms could use far more complex techniques than were available in the 1960s to achieve far higher compression ratios.

These techniques were available through the open research literature to be used for civilian applications, allowing the creation of digital mobile phone networks with substantially higher channel capacities than the analog systems that preceded them.

The most common speech coding is Code Excited Linear Prediction (CELP) coding, which is used for example in the GSM standard. In CELP, the modeling is divided into two stages.


       As can be seen, with a 3dB bandwidth of only approximately 4KHZ, code acquisition is futile unless counter measures are taken against possible Doppler offsets.

The most common approach to overcome this obstacle is to sequentially search all code phase over the range of anticipated frequency offsets. This brute force approach is laborious and can lead to large acquisition times. The approach outlined in this project, utiliizes the SPC combined with an FFT techniques, as proposed in, to simultaneously search all possible code Doppler offsets at one time, thus reducing the 2-dimensional search problem to a 1-dimensional search for code phase.


The near-far problem is a condition in which a receiver captures a strong signal and thereby makes it impossible for the receiver to detect a weaker signal.

The near-far problem is particularity difficult in CDMA systems, where transmitters share transmission frequencies and transmission time.

There is a long-standing issue that the dynamic range of one or more stages of a receiver can limit that receiver’s ability to detect a weak signal in the presence of strong signal. The near-far problem usually refers to a specific case of this in which ADC resolution limits the range of signals a receiver can detect in a direct sequence spread spectrum (DSSS) system such as CDMA. The receiver’s ADC must reduce its gain to prevent ADC salutation, which causes the weaker signal to fall into the noise of the ADC. This is different from a condition of one signal interfering with another because if the ADC had sufficient resolution, it would be possible to recover both signals.

DSSS allows multiple transmitters to use the same bandwidth at the same time. One price of such a system is that the dynamic range of the system is limited by the dynamic range of the receiver ADC.


iii)    CCCH      GSM Common Control Channel

vii)   DSSS      Direct Sequence Spread Spectrum System.

viii)   FDMA      Frequency Division Multiple Access.

xii)   NMT        Nordic Mobile Telephone System.

xiii)  RACH       GSM Random Access Channel

xiv)  SACCH      GSM Slow Associated Control Channel

xvi)  TACS       Total Access Communication System

xvii) TDM        Time Division Multiplexing.

xviii) TDMA      Time Division Multiple Access.

xix)  VAD        Voice Activity Detector

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