Transmit Filter and Multi Secrecy Aided Optimization with DFE for Duplex Systems

The following example essay on “Transmit Filter and Multi Secrecy Aided Optimization with DFE for Duplex Systems” on the problem of secure transmission in wireless communication, especially in the physical layer.

The interconnectivity of devices in Cyber-Physical systems under wireless environments facilitates information exchange but challenges network security. In order to proliferate secrecy, with the assumption of channel reciprocity, the legitimate users share the same channel which is independent of the channels between the legitimate users and the eavesdropper.

It is because of the broadcast nature of the wireless medium makes it vulnerable to two types of major attacks denial of service, and information leakage.

Here the security may decrease due to the correlation between the generated secret bits. To address these challenges, this framework includes two multi-antenna legitimate parties and a multi-antenna eavesdropper node. In order to maximize the secrecy rate, interleaver along with jointly optimized transmit filter and multi secrecy techniques are used at transmitting section.

Optimum receive filter and Equalization technique are used at the receiver section.

At last, the problem is implemented for both duplex systems. So combining with them is a kind of key technology in future physical layer wireless communication. The impact of channel estimation errors and self-interference are taken into account.

Introduction

Wireless technologies are emerging very fast, as the latest technologies allow users to access information and services via electronic media. As wireless networks are becoming more sophisticated and offering more applications, most important compelling issue is the security issues. Hence there is a need to deal with various security issues.

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Confidentiality in transmission will lost due to broadcast nature, mobility, channel instability and dynamic topology of wireless networks. Attackers with a transceiver can be able to hinder wireless transmission[1]. In this paper, secrecy rate is attained by the joint optimization of transmit filter and multi secrecy techniques. This optimization will improve secrecy better than existing methods.

This paper is divided into six sections, first section is the introduction. Section II introduce the existing system . A new technology MIMO-OFDM system is presented section III. Proposed duplex systems are evaluated in section IV. Simulation results and conclusions are given in sections V and VI, respectively

Existing system

The security techniques in physical layer of communication system aim to harden the secrecy characteristics, thereby decreasing the signal quality of a prospective eavesdropper. A joint transmit filter and an artificial noise optimization framework is introduced, for the wireless duplex communication systems. ZF and optimum filter is compared at receiver filter and evaluate their performance.

However with eavesdroppers overhearing capacity goes increases and as mobilty of devices increases this artificial noise based security technique is not enough secure.

MIMO – OFDM System

Multiple-input multiple-output (MIMO) technology in combination with orthogonal frequency division multiplexing (MIMO-OFDM) is an advanced air-interface solution for next-generation wireless systems[2]. MIMO technology, which multiplies capacity by transmitting different signals over multiple antennas, and orthogonal frequency-division multiplexing (OFDM), which divides a radio channel into a large number of closely spaced subchannels to provide more reliable communications at high speeds and spectral efficiency. MIMO incorporated OFDM system is a promising technique for higher capacity for multi hop networks.

MIMO System

The MIMO system multiplies the capacity of radio link by transmitting multiple signals over multiple, co-located antennas. It is accomplished without need for additional power or bandwidth. In MIMO system, the user data is broken down into several chunks and transmitted over the antennas by using same frequency Fc. For a given subcarrier, QPSK symbols are transmitted on several antennas (MIMO). And an antenna can transmit several subcarriers (OFDM).

Orthogonal Frequency Division Multiplexing

In general, Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation technique in which FDM modulation technique for transferring huge amount of data over a radio wave preserving bandwidth efficiency. As its name implies it is orthogonal FDM i.e carrier centers are put on orthogonal frequencies. Peak of each signal coincides with zero crossing of other signal. While the symbol transmitting through channel, past symbols interfere with present symbols create ISI. Equalization is a technique to avoid ISI. Another technique to remove ISI more efficiently is OFDM.

System Model

There is often transmission modes are used for delivery of data between communication devices. In communication networks there are commonly two modes of communication. ie, simplex and duplex. Here OFDM technique is applied to both duplex systems.

The complete block diagram of OFDM induced multi secrecy technique is illustrated here. Packet transmission is carried out at the physical Layer. The binary bits to analog signal transformation is conducted and waveform is send over a communication channel.

The transmission section contains interleaver, channel encoder, modulator, transmit filter cum artificial and phase noise, IFFT and cyclic prefix. The basic idea behind use of interleaved codes is to scatter input symbol sequence at transmitter. It leads to alter sequence at receiver also. At the receiver, deinterleaver will alter the received sequence to get back the original unaltered sequence at transmitter.

The information bits are encoded by convolution encoder, converts serial data into parallel data. Check bits are interleaved with data. Thus it helps to correct error in whole blocks.Data is now modulated by a 16-QAM modulator mapping onto the sub carrier amplitude and phase. In communications systems Quadrature Amplitude Modulation (QAM) is implemented utilizing both amplitude and phase variations.

Multi secrecy techniques merely contain two techniques which intensify existing secure communication. In this approach there includes artificial noise and phase noise signals for improving physical layer secrecy. Thus the confidentiality of the data transmission can be improved. Power invested in both of them is calculated.

With the newly emerging concept of phase jamming, phase of the information signal is changed, with the complete knowledge of legitimate receiver for information security. The main idea is to change the phase of the transmitted signal, which prevents the unauthorized user to receive the signal in correct phase .In physics, the term phase is used to point out a particular portion of a periodic signal.

The transmit filter at transmission section reduces the noise generated by base station. Thus it provide pulse shaping and optimize power consumption. It also eliminates the wideband noise created by transmission system.

Inverse Fast Fourier Transform (IFFT) and Fast Fourier Transform (FFT) operation ensures that subcarriers do not interfere with each other. i.e OFDM is spectrally efficient. It perform operation (I+jQ) exp (jct). Input bits are mapped on the I and Q components of the QAM symbols and arranging in a proper length as the number of subcarriers in the OFDM symbol. To transmit them, the signal must be represented in time domain

In order to avoid intercarrier interference(ICI), each OFDM symbol is preceded by a copy of end part of that same symbol. It provides a guard interval between OFDM symbols. Thus preserves the orthogonality between subcarriers.

As there are multiple antennas at receiver section, high data rate and reliability is preserve. The binary data obtained is an estimate of the transmitted binary information.

Consider Zero Forcing filter and an Optimum filter and comparison is performed to obtain a better solution. The name Zero Forcing corresponds to bringing down the interference of data to zero at received signal. The optimal linear receive filter is obtained for acquiring a best estimate of desired signal from noisy measurement. It is done by minimizing the MSE.

As it is known that use of a cyclic prefix is standard within OFDM and it enables the performance to be maintained even under conditions when levels of reflections and multipath propagation are severe. The Fast Fourier Transform (FFT) converts the time domain samples back into a frequency domain representation. Actually demodulator is an electronic circuit in which the information content is recovered from the modulated carrier wave. The QAM demodulator is the reverse of the QAM modulator. Finally, the parallel to serial block converts this parallel data into a serial stream to recover the original input data is decoded by viterbi algorithm.

Intersymbol interference (ISI) is an unwanted phenomenon of the form of a distorted signal in which one symbol interferes with subsequent symbols. Distortion on a current pulse as it was caused by previous pulses is subtracted. The decision feedback equalizer (DFE) will estimate current symbol from previous symbols by predicting the noise level of channel through noise predictor. Then predicted noise is subtracted from the input signal by using a feedback filter(FB) to reduce the noise level of the channel [7,8,9]. In other words, DFE is actually a filter that uses feedback of detected symbols to produce an estimate of the channel output.

The legitimate nodes A and B send information signal along with multi secrecy components. As it is full duplex system, the eavesdropper node gets affected by the interference due to simultaneous transmission along with the artificial noise and phase noise components[10]. All analysis in full duplex is similar to half duplex, except here there is dual communication occurs at same time.

Simulation Result

In this section performance of duplex systems is treated by MATLAB programming.  As large 1/sigma2 means strong overhearing ability of eavesdropper, while smaller the value means weak overhearing ability. FD system with optimum filter yields smaller power.

As it is clear that due to simultaneous transmission ,in FD systems cause interference than HD. So as interference increase, SNR value reduce in FD systems and in HD systems vicevesa.

As the residual self interference coefficient increases, total power of system also got increase. So to reduce power consumption, inference value got reduced. In FD systems, efficient self interference cancelation schemes are to be properly working, to minimize interference problems.

Conclusion

Over the years, there has been a tremendous growth in digital communications especially in the fields of multimedia, teleprocessing, graphic design, cellular, satellite, and computer communication. Hence, information security has become a key challenge, attain confidentiality in existing communication techniques, physical layer security is an alternative paradigm to protect wireless transmission against eve’s attacks. Here a joint transmit filter and multi security optimization scheme is devised, to minimize error rate and attain a target secrecy level. This joint optimization framework is well suited for making physical layer security in wireless transmission systems.

References

1. O. Cepheli, G. Dartmannz, G.K.Kurt and G.Ascheid, A Joint Optimization Scheme for Artificial Noise and Transmit Filter for Half and Full Duplex Wireless Cyber Physical Systems IEEETransactions on Sustainable Computing, 2017
2. H. B?lcskei, E. Zurich “MIMO – OFDM wireless systems: basics, perspectives, and challenges.” IEEE Wireless Communications  August 2006.
3. J. Kaur, S. Kaur and Sandhu”Comparison of BER for various Constraint Lengths of Convolution Coding in OFDM System” IJARECE Volume 5, Issue 5, May 2016
4. CSE 545: Coding Theory
5. M.I.Khan and M.Riaz comparison of different types of physical layer security techniques in wireless communication systems: a reviewEuropean Journal of Engineering and Technology Vol. 5 No. 1, 2017.
6. S. Goel and R. Negi, Guaranteeing secrecy using artificial noise, IEEE Transactions on Wireless Communications, vol. 7, no. 6, pp. 2180-2189, 2008.
7. Ahsan Aziz “Decision Feedback Equalizer for StarCore®-Based DSPs” Freescale Semiconductor, 2007.
8. Heyi Sun, AnantSahai, Ed, John Wawrzynek, Ed.Spectrum Access System: Design and Implementation of the Decision-Feedback Equalizer in Software
9. /2017/EECS-2017-83.pdf may 2017
10. M. Moshfegh, Al. Rahmati and A.Hajisami Optimized Decision Feedback Equalizer and Comparison with MLSE Algorithm for GSM Channel IEEE International Conference on Modelling and Simulation, May 2011.
11. P. Lioliou, M. Viberg, M. Coldrey, and F. Athley, Self-interference suppression in full-duplex MIMO relays, in 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, Nov 2010, pp. 658-662.