Figure 1. Block diagram for Chanel Estimation
This paper presents a comparative study of HHT and DWT Based MIMO-OFDM for BPSK, QPSK and QAM modulation schemes in AWGN and Raleigh Fading Channel. Angular diversity is used in radars to mitigate the impairment caused by rapid fluctuations in Radar Cross Section (RCS) of the target. The antennas are placed in separate locations so that the target is seen from different angles. Such systems are called Statistical Multiple Input Multiple Output (MIMO) or MIMO radars with distributed antennas. This statistical MIMO radar exploits angular diversity to mitigate the impacts of RCS fluctuations. The channel capacity in AWGN channel is better when compared to the Rayleigh fading noise channel, since the SNR is high with low BER for any signal in any type of modulation technique. So that AWGN channel gives good results. Wavelet based OFDM has a lot of advantages compared to the FFT based OFDM. There is no need for cyclic prefix, flexibility and gives an optimal resolution. HHT based MIMO-OFDM gives better SNR and low BER compared to the FFT and DWT based MIMO-OFDM. In DWT MIMO OFDM, wavelets are applicable in almost all the areas of communications schemes with OFDM, which is a durable applicant for next peers of wireless schemes. Comparing different types of modulation schemes such as BPSK,QPSK and QAM, BPSK gives good results. So, finally HHT based MIMO OFDM in AWGN channel by using BPSK modulation technique gives better results compared to the DWT based MIMO OFDM.
Multiple Input Multiple Output (MIMO) wireless technology in combination with Orthogonal Frequency Division Multiplexing (OFDM) is an attractive air interface solution for next generation Wireless Local Area Networks(WLANs), Wireless Metropolitan Area Networks (WMANs), and fourth generation mobile cellular wireless systems. Wireless channels have losses due to following reasons. These factors significantly reduce the channel bandwidth and minimize the data flow. The problems listed below lead to multiple copies of signals floating called diversity and can be divided into three areas [1- 4].
The phenomena of having multiple copies of signal at one time are called multipath propagation. The result of multiple signals can be constructive thus increasing the amplitude and phase, or it can be destructive resulting in low amplitude and phase cancellation. The multipath delay causes the information symbols represented in an 802.11 signal to overlap, which confuses the receiver. This is often referred to as Inter Symbol Interference (ISI). Because the shape of the signal conveys the information being transmitted, the receiver makes mistakes when demodulating the signal's information. If the delays are great enough, bit errors in the packet will occur. The receiver will not be able to distinguish the symbols and interpret the corresponding bits correctly. Summarizing, the effects of multipath distortion are summarized below.
It occurs when multipath is so severe that the receiver is unable to detect the transmitted information.
It occurs when the reflected waves arrive exactly out of phase with the main signal and cancel the main signal completely.
It occurs when the reflected waves arrive in phase with the main signal and adds on to the main signal thereby increasing the signal strength.
It occurs when the reflected waves arrive out of phase to some extent with the main signal thereby reducing the signal amplitude.
MIMO-OFDM has become an important wireless communication technique because it can obtain increasing data throughputs from limited wireless spectrum. It provides high spectral efficiency over a wide range of radio channel conditions. This is important as customers demand high throughput for bandwidth hungry applications.
Orthogonal Frequency Division Multiplexing (OFDM) refers to a communication technique where a data stream is sent over a large number of closely packed subcarriers. All subcarriers are modulated at a baud rate below but close to the subcarrier spacing, typically using Quadrature Amplitude Modulation (QAM). The subcarrier spacing for the two prominent broadband wireless access standards today are 15 kHz for LTE and 312.5 kHz for 802.11ac.
Normally OFDM is supplemented with a guard interval, interleaver and forward error correction. The combination allows the OFDM demodulator to provide tolerance to radio links with multipath. The frequency selective fading caused by multipath may introduce deep nulls into a received signal. With coded OFDM, subcarriers with a good receive Signal to Noise Ratio (SNR) can protect the subcarriers with poor receive SNR in the vicinity of the nulls. Multiple Input and Multiple Output (MIMO) refers to the RF propagation channel. The multiple inputs are the two or more transmit antennas radiating signals into the RF channel, and the multiple outputs are the two or more receive antennas collecting signals from the RF channel. MIMO systems offer diversity gain, interference mitigation and spatial multiplexing gain. Diversity gain arises at both the transmitter and the receiver due to de-correlated fading between different TX and RX antenna pairs, diversity gain reduces the fade margin required to sustain a given link availability in a fading channel [9].
The challenges in making wireless broadband connectivity work are mostly environmental. For radio channels commonly used for broadband wireless, best link performance is typically obtained from Line Of Sight (LOS) channels having no reflections. In contrast, Non-Line of Sight (NLOS) links are perturbed by obstructions and reflections. While LOS-only operation relaxes the demands on the radio, it adds cost to the system by restricting antenna placement. The overall cost of a wireless link may be significantly reduced by relaxing the requirements to tolerate some level of NLOS operation while still providing the users required data throughput and availability. This reduces the constraints of the antennas, which gives link planners more options.
The development of MIMO-OFDM has greatly assisted in the successful deployment of wireless networks in challenging environments. Interference mitigation may be provided by using MIMO to perform beam forming and beam nulling to avoid the interfering sources. Spatial multiplexing gain results from the channel supporting more than one spatial stream.
The techniques of MIMO and OFDM form a particularly compelling combination for broadband wireless. Together, these maximize the throughputs and availability achievable in a wide range of RF channel conditions ranging from deep NLOS with high levels of multi-path to benign radio links capable of supporting high rate modulation modes
The need for more than one antenna with MIMO does not necessarily result in a significant increase in the antenna profile. With 2×2 MIMO, a popular configuration is to use dual polarization antennas occupying the same aperture. This gives the benefits of dual stream operation for most channel conditions and some diversity gain when the channel only supports single stream modes [10].
The general structure of MIMO-OFDM system is shown in Figure 1. The proposed system consists of two transmit and two receive antennae. The OFDM signal for each antenna is obtained by applying the Inverse Hilbert–Huang transform (IHHT) and can be detected using Hilbert–Huang transform (HHT) [5,6]. A pilot sequence is inserted and used for the channel estimation. Also, a cyclic prefix is inserted in front of the OFDM symbol at the last step of OFDM modulation block. The time length of the cyclic prefix should be greater than the maximum delay spread of the channel. The main function of the cyclic prefix is to guard the OFDM symbol against Inter Symbol Interference (ISI), hence, this cyclic prefix is called the guard interval of the OFDM symbols [7,8]. The MIMO coding can use several encoders such as STBC, VBLAST and Golden coding. In this paper, the conventional MIMO-OFDM system is implemented using Altamonte STBC with two transmits and two receive antennas.
Figure 1. Block diagram for Chanel Estimation
The Hilbert Huang Transform (HHT) is an empirically based data-analysis method. Its basis of expansion is adaptive, so that it can produce physically meaningful representations of data from nonlinear and non-stationary processes. The advantage of being adaptive has a price: the difficulty of laying a firm theoretical foundation. This section gives an introduction to the basic method, which is followed by brief descriptions of the recent developments relating to the normalized Hilbert transform, a confidence limit for the Hilbert spectrum, and a statistical significance test for the Intrinsic Mode Function (IMF). The mathematical problems associated with the HHT are (i) the general method of adaptive data-analysis, (ii) the identification methods of non linear systems, (iii) the prediction problems in non stationary processes, which is intimately related to the end effects in the Empirical Mode Decomposition (EMD), (iv) the spline problems, which center on finding the best spline implementation for the HHT, the convergence of EMD, and two-dimensional EMD, (v) the optimization problem or the best IMF selection and the uniqueness of the EMD decomposition, (vi) the approximation problems involving the fidelity of the Hilbert transform and the true quadrature of the data, and (vii) a list of miscellaneous mathematical questions concerning the HHT [6]. HHT based MIMO-OFDM system is shown in Figure 2. Compared to FFT and DWT based MIMO-OFDM ,HHT gives better SNR and low BER.
Figure 2. Block diagram representation of HHT based MIMO-OFDM
MATLAB 2013a was used for the work. The signal spectrum of BPSK, QPSK and QAM are plotted in Figures 3, 4 and 5. Signal Spectrum is the signal coverage area under that particular modulation scheme. Based on the above simulation, results under BPSK modulation signal spectrum was better compared to QAM and QPSK modulation schemes.
Figure 3. Signal Spectrum of BPSK
Figure 4. Signal Spectrum of QPSK
Figure 5. Signal Spectrum of QAM
Based on different types of modulation schemes like QAM (Quadrature Amplitude Modulation), BPSK (Binary Phase Shift Keying), QPSK (Quadrature Phase Shift Keying) Constellation and Signal Spectrums, we conclude that the BPSK (Binary Phase Shift Keying) was the best modulation technique for MIMO (Multiple Input and Multiple Output) OFDM(Orthogonal Frequency Division Modulation).
Based on Figure 6, the channel capacity in AWGN (Additive White Gaussian Noise) channel is better when compared to the Rayleigh Fading noise channel which gives the better SNR (Signal to Noise Ratio) and low BER (Bit Error Rate) for any signal in any modulation techniques. Therefore AWGN noise channel is used to get good results.
Figure 6. Channel Capacity of AWGN channel vs Rayleigh Fading channel
Based on the Simulation Results of different MIMO OFDM (FFT, DWT, HHT) techniques in different modulation techniques like QAM, QPSK, BPSK as shown in Figures 7, 8, 9, 10 and,11 gives the simulation results of Signal to Noise Ratio (SNR) and Bit Error Rate (BER) average values listed in Table 1.
Figure 7. Comparison of DWT and FFT based MIMO OFDM's in BPSK
Figure 8. Comparison of FFT and DWT based MIMO OFDM in QPSK
Figure 9. HHT based MIMO OFDM in BPSK modulation
Figure 10. HHT based MIMO OFDM in QPSK
Figure 11. Comparison of FFT DWT HHT based MIMO OFDM's in QAM modulation
Table 1. Comparison of FFT, DWT and HHT based MIMO OFDM in various modulation schemes
By comparing the simulation results of SNR and BER of FFT, DWT, HHT in different types of modulation schemes like QAM, QPSK, BPSK, the best technique is BPSK modulation technique in AWGN channel using HHT, as it gives the best results of high SNR at low BER.
From Table 1, the average SNR for FFT based MIMO OFDM in QAM, QPSK and BPSK are 6.4dB, 6.55dB, and 6.8dB respectively. The SNR increases by 0.4dB and BER decreases by 0.005 dB using BPSK compared to QAM.
An average increase of SNR for DWT based MIMO OFDM using BPSK is 0.45dB compared to QAM. Similarly an average decrease of BER for DWT based MIMO OFDM using BPSK is 0.05dB when compared to QAM.
The average increase in SNR for HHT based MIMO OFDM using BPSK is 0.5dB compared to QAM and average decrease in BER for DWT based MIMO OFDM using BPSK is 0.07dB compared to QAM.
Finally HHT based MIMO OFDM gives better results than FFT and DWT based MIMO OFDM. The average increase in SNR is 0.22 dB and average BER is 0.03 using BPSK modulation compared to FFT based MIMO OFDM.
The simulation results of HHT based MIMO OFDM is best which is based upon the probability of Bit Error Rate and transmission capacity. It gives the low Bit Error Rate (BER), and high SNR compared to the DWT and FFT based MIMO OFDM. As there is no need for cyclic prefix, that is, periodic extension, in which last part of OFDM data is appended to the first part of OFDM data. The linear convolution is converted into circular convolution. To achieve higher data rates, the HHT based MIMO OFDM is better than the DWT, FFT based MIMO OFDM. DWT based MIMO OFDM is an important technique in modern wireless communication system for achieving high data rates with low BER. Later a certain side by side of the transmit antennas, there is no greater development, that is why HHT based MIMO OFDM is given more importance than DWT and FFT based MIMO OFDM techniques in BPSK modulation through the AWGN noise channel. The BER presentation of communication schemes with Binary Phase Shift Keying (BPSK) is superior to Quadrature amplitude modulation and QPSK. By comparing the simulation results HHT is better than FFT and DWT based MIMO OFDM techniques, and BPSK is better than the QPSK and QAM modulation technique in AWGN channel compared to Rayleigh fading noise channel.