1. 1 of 20 Z. Nikolova, V. Poulkov, G. Iliev, G. Stoyanov NARROWBAND INTERFERENCE CANCELLATION IN MULTIBAND OFDM SYSTEMS Dept. of Telecommunications Technical University of Sofia BULGARIA e-mail: zvv@tu-sofia.bg

2. 2 of 20 Technology for short range high data rate communications, combining OFDM and frequency hopping.  Occupies a very wide frequency band and low transmission power;  UWB systems are subject to different types of narrowband interferences, which could deteriorate strongly and even block communications;  NBI suppression is of primary importance for these systems. Multiband OFDM (UWB):

3. 3 of 20 Multiband OFDM

4. 4 of 20  NBI avoidance methods. Based on avoiding the transmission over frequencies with strong narrowband interferers;  Cancellation – suppression methods. Aim at eliminating the effect of NBI on the received UWB signal. NBI mitigation

5. 5 of 20 How? Via adaptive complex filtering using the LMS algorithm to adapt to the central frequency of the NBI. Why is possible? Compared with the desired wideband signal the interference occupies a much narrower frequency band, but with a higher power spectral density; UWB signal has autocorrelation properties quite similar to that of AWGN, so filtering in the frequency domain could be applied. Scheme for the suppression of NBI

6. 6 of 20 Scheme for the suppression of NBI

7. 7 of 20 Variable complex digital filter circuit derivation The composite multiplier, containing  is derived: Second-order real coefficient transfer functions All of them of BP type, describing a complex digital filter section, which is variable with respect to both the BW (by changing of  ) and the central frequency (by changing of  ). First-order complex coefficient transfer function  f  +

8. 8 of 20 Variable complex digital filter circuit derivation Real first-order digital filter section Complex second-order digital filter section

9. 9 of 20 Variable complex second-order filter Magnitude and group-delay responses of variable BP complex second- order filter for different values of the central frequency

10. 10 of 20 Variable complex second-order filter Magnitude, phase and group-delay responses of variable BP complex second-order filter for different values of the bandwidth

11. 11 of 20 For the BP filter we have the following real and imaginary outputs: and - when the input signal is For the BS filter we have - real and imaginary outputs: and ADAPTIVE ALGORITHM x R (n) SECOND-ORDER COMPLEX FILTER + + x I (n) e R (n) y I (n) y R (n) e I (n) The cost-function is the power of BS filter output signal: where The Least Mean Squares (LMS) algorithm is applied to up­date the filter coefficient responsible for the central frequency as follows:   is the step size controlling the speed of the convergence; (*) denotes complex-conjugate; y(n) is the derivative of y(n) with respect to the coefficient subject of adaptation. Block-diagram of a versatile adaptive complex narrowband filter Adaptive complex second-order filter

12. 12 of 20 Performance evaluation of the NBI suppression scheme via simulations relative to baseband: Assuming standard MF-OFDM receiver with 3 subbands (as proposed MB-OFDM in the 3.1 – 4.8 GHz band) and IEEE 802.15 3a Channel Model 1.  The NBI interference is modulated with a random frequency appearing in one subband;  Soft decision 4-bit Viterbi decoding was used, thus recovering some of the lost data due to the frequency domain excision.

13. 13 of 20 Results:  The simulations showed that for one and the same BER such NBI cancellation scheme gives more than 2 dB improvement for signal-to-interference ratios below 8 dB. Drawback of the scheme:  Frequency excision is performed over all OFDM symbols (dehopped over all subbands), nevertheless the fact that the NBI appears only in one.

14. 14 of 20 Better if: Frequency excision is performed not over all symbols but only on those affected by NBI. Proposed solution:  Instead of one complex adaptive filter section a filter bank with corresponding switching capabilities and a number of ACF equal to the number of subbands is implemented.  Corresponding ACF to be switched accordingly with the hopping of the carrier frequencies and will process only the OFDM symbols appearing in one and the same frequency sub-band.

15. 15 of 20 Analysis: Behavior of an ACF, composed of three second-order complex filter sections.  Input interfering signal is composed of three complex sine-signals with frequencies f1=0.25, f2=0.2 and f3=0.15;  Learning curves show that our filter bank is able to detect and to track the input complex sinusoids and can be successfully used for their cancellation.

16. 16 of 20 Learning curves for second-order adaptive complex filter applying different step size Adaptive complex second-order filter

17. 17 of 20 Learning curves of an ACFB consisting of three second-order complex filter sections Adaptive complex second-order filter

18. 18 of 20 Advantages of the ACF:  Low computational complexity;  Fast convergence (less than 100 iterations in the example);  Convenience for implementation with CORDIC processors;  The very low sensitivity of the initial LP section ensures a high tuning accuracy.

19. 19 of 20 Another important advantage: The proposed NBI cancellation scheme is that the adaptive complex notch filter section has also a bandpass output used for monitoring the NBI and switching of the ACF in cases when the NBI vanishes or is reduced to a predetermined level.

20. 20 of 20 THANK YOU!

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