UWA Communication using MIMO OFDM transmission rate then it's called MIMO-OFDM. MIMO-OFDM is the efficient

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  • www.ijemr.net ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962

    346 Copyright © 2017. Vandana Publications. All Rights Reserved.

    Volume-7, Issue-3, May-June 2017

    International Journal of Engineering and Management Research

    Page Number: 346-452

    UWA Communication using MIMO OFDM

    Sanjay K. Sharma 1 , Utkarsha Sharma

    2

    1 Assistant Professor,

    2 Dual Degree Scholar,

    1 Department of Electronics & Communication Engineering UIT, RGPV, INDIA

    2 Department of Electronics & Communication Engineering UIT, RGPV, INDIA

    ABSTRACT Various researches has been carried out to explore the

    effective ways of communication inside the water between the

    submarines or to collect information from sensors inside the

    water. A methodology proposed in this paper uses combination

    of Multiple Input Multiple Output (MIMO) and Orthogonal

    Frequency Division Multiplexing (OFDM) along with QAM and

    BPSK Modulation Schemes and LDPC Coding which increases

    the reliability of UWAC. Both Radio and Under Water

    Communication are almost similar. The difference lies in

    Density and Speed of Water. Transmission Speed of water is

    generally 1500 m/sec and its density is high.

    Keywords-- Shallow Water Communication, LDPC, MIMO-

    OFDM, QAM and BPSK

    I. INTRODUCTION

    The ability to communicate effectively underwater

    has various applications for marine researchers and industrial

    operators, oceanographers, and different organizations.

    Electromagnetic waves cannot propagate over long distances

    in sea water, therefore acoustic waver are preferred for

    communication in under water. Underwater acoustic (UWA)

    communications has been a troublesome problem because of

    unique channel characteristics like the fading, extended

    multipath and also the refractive characteristics of the sound

    channel [1, 2].

    In this work we introduce a combination of multiple

    input multiple output (MIMO) and orthogonal frequency

    division multiplexing (OFDM) with low complex

    modulation techniques and also less complex coding

    techniques to communicate our signal in shallow water

    acoustic communication. We analyzed various modulation

    technique on the basis of two parameters, BER and FER. The

    Binary phase shift key (BPSK) technique is less complex in

    comparison with other modulation techniques as we know

    that in underwater the bandwidth is very less which is 5 khz

    that‟s why BPSK consume low bit error rate (BER) as well

    as low signal to noise ratio (SNR). The proposed technique

    will be simulated with the help of MATLAB R2013b.

    Since OFDM provides support

    of additional antennas and larger bandwidths as it

    simplifies equalization in MIMO systems, combination of

    MIMO-OFDM is very advantageous for communication. By

    conjointly using Multiple-Input Multiple-Output (MIMO)

    and Orthogonal Frequency-Division Multiplexing (OFDM)

    technologies, data rates up to hundreds of M bits/s could be

    reached by indoor wireless systems and they can also

    attain spectral efficiencies of several tens of

    bits/Hz/s, that are undoable for typical single-input single-

    output systems. This enhancements of data rate and

    spectral efficiency is due to the fact that MIMO and OFDM

    schemes are so parallel transmission technologies in

    the space and frequency domains, respectively.

    When OFDM signal is transmitted through variety of

    antennas in order to attain diversity or to achieve higher

    transmission rate then it's called MIMO-OFDM.

    MIMO-OFDM is the efficient solution for

    transmitting and receiving the data over the long distance.

    The sub-carrier frequency has been chosen in our proposed

    OFDM transceivers so that cross-talk between the sub-

    channels are eliminated, hence the inter carrier guard bands

    are not required and we have also used such type of guard

    band for eliminating the cross-talk between channels. This

    greatly simplifies the design of both the transmitter and the

    receiver; unlike conventional FDM, a separate filter for each

    sub-channel is not required.

    FER= 1- (1-BER) 4

    1.1 (in this case)

    FER=

    1.2

    Correlation between Es /No and Eb /No (SNR)

    Es /No = Eb /No (dB) +10log10(k) 1.3 Where k is the number of information per symbol

    Es/No =ratio of symbol energy to noise power spectral density

    Eb/No = ratio of bit energy to spectral power density

  • www.ijemr.net ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962

    347 Copyright © 2017. Vandana Publications. All Rights Reserved.

    II. PROPOSED METHODOLOGY

    In the upcoming years MIMO has drifted enormous

    amount of attention of researchers in the field of wireless

    communication. Multipath fading is main factor in increasing

    the data rate and reliability of transfer of information over

    wireless channel. To improve reliability, channel coding

    techniques which are used to meet the requirements of

    today‟s multimedia communications is insufficient.

    Figure 1: Block diagram of the proposed shallow water communication system

    Increased spectral potency for a given total transmit

    power is obtained through wireless communication using

    multiple-input multiple-output (MIMO) systems. That

    enhanced the capacity that's achieved by introducing further

    spatial channels which are attained by using space-time

    coding. The environmental factors have an effect on MIMO

    capacity. Those factors embrace channel complexity,

    interference, and channel estimation error. If multiple

    antennas are used at transmitter or receiver, it will improve

    data rate and reliability.

    In Fig.1 the block diagram of the proposed approach

    is provided. Modulation of data using BPSK and QAM

    followed by Serial to parallel conversion of modulated signal

    are the major blocks. Before transmission of signal cyclic

    prefix are added, the signal has been coded with LPDC and

    modulated by Orthogonal Frequency Division Multiplexing

    (OFDM). FER means the combination or group of bits

    referred to as frames.

    During transmission through channel, signal reaches

    the receiver end before encountering with the various noises.

    AWGN is generally a basic noise model to imitate the effect

    of many random processes that take place in nature. On the

    receiver the reverse method of transmitter is taken place and

    the data will be taken out.

    The above described block diagram of the proposed

    methodology is then implemented on simulation tool. The

    execution of the simulation algorithm is explained step by

    step as follows:

    i. Start simulation

    ii. Create simulation environment using variable

    initialization

    iii. Generate random data for transmission over system

    iv. Modulate data with BPSK and QPSK Modulation

    v. Convert signal from serial to parallel

    vi. Code signal with LDPC coding

    vii. Perform OFDM Modulation i.e. IFFT

    viii. Add cyclic prefix ix. Transmit channel and add noises x. Remove cyclic prefix xi. Perform OFDM demodulation that is FFT xii. Decoding with LDPC coding xiii. Convert parallel data to serial xiv. Demodulate data with BPSK/QAM modulation xv. Calculate Error Rate xvi. Compare and display results xvii. End of Simulation

    III. MATHEMATICAL MODDELING

    During the simulation, we have taken the equivalent

    model with parallel flat-fading sub channels. Ignoring

    intercarrier interference (ICI), the signal in the k-th sub

    channels can be represented as

        . 1,2......k k pZ H k d k v k k   3.1

    Where d[k] is the data symbol to be transmitted

    over k-th subcarrier, kp is the number of subcarrier and H[k]

    is the channel frequency response of the k-th subcarrier, vk is

    the additive noise.

    On the SWA multipath channel the coefficient H[k]

    can be related to discrete time base-band channel

    parameterized by Lp+1 complex value coefficients

    {* + } through

      2

    0

    p p

    j pk

    L k

    pp H k e

     

     

    3.2

    BPSK / QAM

    Modulation

    Serial To

    Parallel

    Conversion

    LDPC Coding OFDM

    Modulation

    (IFFT)

    Adding Cyclic

    Prefix

    Remove Cyclic

    Prefix

    OFDM

    Demodulation

    (FFT)

    LDPC

    Decoding

    Parallel to

    Serial

    Conversion

    Demodulation

    Data

    Input

    Data

    Output

    Channel with

    Noises

  • www.ijemr.net ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962

    348 Copyright © 2017. Vandana Publications. All Rights Reserved.

    As long as kp≥ Lp+1, we can rewrite as

    ⌋=⌊

    ⌋ [