Chapter 3 Analysis and Methods
3.8 The Proposed Algorithm of I/Q Estimation with CW Jamming
The proposed algorithm can be summarized as follows:
1) Detect whether CW jamming exist or not. If not, execute the FD-IQME algorithm described in section 3.1; otherwise, go to 2).
2) Use smooth filter to improve the estimation of a rough CFR.
3) Execute the averaging method (TD-AVM) described in section 3.7.
4) After FFT, perform the FD-IQME algorithm and then the peak-avoidance
method (PEAM) described in section 3.5.
Figure 3-12 shows the proposed algorithm structure in the receiver; Figure 3-13 shows the flow char of the proposed algorithm.
Figure 3-12 The proposed algorithm structure in Rx.
Figure 3-13 The flow chart of the proposed algorithm.
Chapter 4
Simulation Results and Performance
4.1 Simulation Results of Only I/Q-Mismatch
A typical MIMO-OFDM system with FD-IQME algorithm is simulated to evaluate and compare the performance. The length of OFDM symbol is 64 samples and cyclic prefix is 16 samples. The parameters used in the simulation are as follows:
4X4 MIMO-OFDM systems in 20 MHz.
PSDU is 1024 bytes
1000 packets
Multipath Mode: TGn E.
Modulation:64 QAM, coding rate:2/3
SJR=-10dB each receiver
I/Q Mismatch :
gain error :1dB, phase error:20° in receiver one gain error :2dB, phase error:13° in receiver two gain error :2dB, phase error:18° in receiver three gain error :1dB, phase error:19° in receiver four
Figure 4-1 shows that the performance of FD-IQME algorithm is acceptable.
Without CW jamming, packet error rate (PER) converges to 0.01 as signal-to-noise
IQ w/o jamming, IQ compensated IQ with jamming, IQ compensated
(a)
IQ w/o jamming, IQ compensated IQ with jamming, IQ compensated
(b)
Figure 4-1 The Compensation Result.
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4.2 Performance Index
The aim of this paper is to estimate IQM coefficients correctly under the attack of CW jamming. Accurate IQM coefficients, which are obtained from FD-IQME once, can be used to compute CFR again and compensate data. Due to huge simulation time, the system performance is based on the image rejection ratio (IRR). The image rejection ratio as a function of the mismatch is denoted as [22]:
10
Figure 4-2 IRR values corresponding to different phases and gains.
4.3 Simulation Results of I/Q-Mismatch with CW Jamming
For convenience of representation, the abbreviation is used for the proposed methods as below.
FD-IQME : I/Q-Mismatch Estimation in Frequency Domain.
SF : Smooth filter.
SP-LP : Short preamble subtracted from long preamble.
PEAM : Peak-Avoidance Method.
TD-AVM : Averaging Method in Time Domain.
The estimated IQM coefficients on Receiver one is taken to analyze the performance of each method. Because PER and BER converge on SNR=20dB, SNR will be fixed on 20dB when these proposed methods above are discussed. And SJR=-10dB.
4.3.1 Evaluate FD-IQME
While FD-IQME is used to estimate IQM coefficients without dealing with CW jamming, IRR approximates 12 dB from Table 4-1. However, IRR approximates 36 dB when there is no CW jamming. The gap is about 24 dB, which means that CW jamming must be considered when estimating IQM coefficients; this result can correspond to Figure 4-1.
Actually, the IRR value, which is calculated, is only a point. However, it is convenient to observe so that the point is expanded to one plane; the yellow plane is expanded form the point of 35.96 dB and the green plane is expanded form the point of 11.93 dB, as can be seen from Figure 4-3.
40
Figure 4-3 IRR, comparison of FD-IQME w/o jamming and FD-IQME with CW jamming.
Table 4-1 IRR, comparison of FD-IQME w/o jamming and FD-IQME with CW jamming.
FD_IQME ∆εεεε(dB) ∆θθθθ(degree) IRR (dB)
w/o jamming 0.032 0.798 35.96
With jamming 1.046 22.972 11.93
4.3.2 Evaluate SF & SP-LP
From Figure 4-4, using smooth filter, which makes IRR reduced to 9 dB, is worse than using no smooth filter. The result shows that this method SF is not robust enough. The main reason is that smooth filter does not assure that the estimated CFR can approximate the real CFR but rather that the two peak which are caused by CW jamming can be suppressed. Nevertheless, the estimated CFR, which is adjusted by the smooth filter, is still not available, even worse.
Figure 4-4 IRR, comparison of FD-IQME w/o jamming, FD-IQME with CW jamming, and FD-IQME+SF with jamming.
When SP-LP is evaluated, the ideal CFR is assumed. From Figure 4-5, using the
42
changing rate (CR). Two adjacent CW jammings are always different, which makes SP-LP fail to eliminate CW jamming.
Figure 4-5 IRR, comparison of FD-IQME w/o jamming, FD-IQME with CW jamming, and FD-IQME+SP-LP with jamming.
4.3.3 Evaluate PEAM & TD-AVM
Because I/Q-Mismatch estimation needs the information of CFR to calculate IQM coefficients, those simulations in this section are based on knowing the ideal CFR, which is not corrupted by CW jamming. The simulation results are based on 1000 packets. From Figure 4-6 and Table 4-2, some observations are obtained. Using PEAM and FD-IQME can get 19.16dB of IRR, which is better than 11.96dB while using only FD-IQME. If TD-AVM, PEAM and FD-IQME are used for estimating IQM coefficients, IRR will increase into 22.25dB. This justifies that the power of CW jamming is reduced mostly. Figure 4-6 clearly shows that the mean value of IRR moves from 11.96dB to 22.25dB.
0 5 10 15 20 25 30 35
44
Table 4-2 IRR, comparison of FD-IQME, PEAM+ FD-IQME, and TD-AVM+PEAM+ FD-IQME.
with jamming ∆εεεε(dB) ∆θθθθ(degree) IRR (dB)
TD-AVM + PEAM + FD-IQME
0.130 6.575 22.25
PEAM + FD-IQME
0.203 9.321 19.16
FD-IQME 1.046 22.972 11.93
4.3.4 Brief Summary
From Figure 4-7 and Table 4-3, by using the proposed methods, FD-IQME, PEAM, the performance can increase to 19.16dB; by using the proposed methods, FD-IQME, PEAM and TD-AVM, the performance can increase to 22.25dB.
Compared with using only FD-IQME, about 10 dB of improvement is obtained. In the future, some digital signal processing (DSP) techniques such as linear regression can be used to reach higher IRR .
Figure 4-7 IRR, comparison of FD-IQME w/o jamming, FD-IQME with jamming, PEAM+ FD-IQME with jamming, and TD-AVM+PEAM+ FD-IQME with jamming.
Table 4-3 IRR, comparison of FD-IQME w/o jamming, FD-IQME with jamming, PEAM+ FD-IQME with jamming, and TD-AVM+PEAM+ FD-IQME with jamming.
Methods FD-IQME PEAM TD-AVM IRR (dB)
w/o CW Jamming
ˇˇˇ
ˇ 35.96
ˇˇˇ
ˇ 11.93
Chapter 5
Conclusions and Future Work
5.1 Conclusions
The currently existing methods which are evaluated seem to provide some resistance to CW jamming. However, a robust method for solving CW jamming is needed. Therefore, time-domain estimator for IQ mismatch with CW jamming is considered to evaluate. As mentioned in the Section 3, while the power of CW jamming is reduced once, the IRR will improve significantly. The proposed methods and the simulation results demonstrate this idea. This concept also can be applied to the time-domain estimator.
The main contribution for this paper is as follows. First, by making use of STF, one shot calculated algorithm is proposed to estimate IQM coefficients without too complicated computations. Second, by defining image-rejection-ratio (IRR), the simulation time can be effectively reduced to obtain estimated IQM coefficients.
5.2 Future Work
In this section, three works are suggested to solve in the future. First, a I/Q mismatch estimation in time domain is proposed to resist CW jamming. Second, a
accurate channel-estimation is needed. Finally, the hardware implementation is continued.
5.2.1 I/Q Mismatch Estimation in Time Domain
From time domain view, the amplitude of CW jamming covers the one of desired signal due to SJR equal to -10 dB. By reducing the power of CW jamming, the performance of estimating IQ mismatch will improve greatly. Some property of STF can be used to reduce the power of CW jamming. For many positions of STF are null subcarriers in the frequency domain. If CW jamming corrupted the signal, the values of these positions will become nonzero. However, these values are forced to set to ZERO and that will not destroy the original signal because the values of these positions do not include the values of the original transmitted signal. And then the results are transformed from frequency domain to time domain by IFFT. After that, the power of CW jamming is reduced mostly and makes little effects on the signal.
But this method needs a time-domain estimator for I/Q mismatch.
5.2.2 Channel Estimation
Although a smooth filter is used to resist CW jamming, the performance of IRR is not good enough. For I/Q estimation in frequency domain, the estimation of channel frequency response (CFR) also affects the estimation of IQM coefficients. If a rough value of estimated CFR cannot be compensated, IRR is always very low.
Therefore, an anti-jamming channel-estimation is needed.
5.2.3 Hardware Implementation
The FD-IQME algorithm of 4X4 MIMO-OFDM system will be performed by verilog and then tap out. Therefore, RTL coed, gate-level verification, and layout need
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