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A structure of dynamic reconfigurable channelized filter bank is proposed in order to solve the problem that the uniform channelized receiver cannot receive the cross-channel and wideband signal. The dynamic reconfigurable channelized filter bank is divided into two parts-the analysis filter bank and the synthesis filter bank. The function of the analysis filter bank is to divide the received signal into several sub-signals according to the channel division. Then the sub-signals of each channel need to be detected and discriminated. At last, we use the sub-signals to reconstruct the original received signal by the synthesis filter bank. The analysis filter and the synthesis filter bank of the dynamic reconfigurable channelized filter bank are all efficient polyphase structures, so it can save more hardware resources and has extensive applicability. The structure is simulated by MATLAB and the simulation results verify the correctness of this structure.

With the development of software radio, the digital channelized receiver has become a hot spot research in the field of receiver. It has the advantages of digital receiver such as high accuracy, high flexibility, high reliability, low power consumption, and meanwhile the advantages of channelized receiver such as good applicability and strong comprehensiveness. The digital channelized receiver divides the instantaneous bandwidth into several sub-band channels by the digital filter bank. When the receiver receives the instantaneous signal, it can realize the full-probability receive through processing the sub-band signals in parallel.

Reference [

In this paper, we propose a non-maximally decimated dynamic reconfigurable channelized structure based on the modulated filter banks. The received signal firstly goes through the decimation module to reduce the sampling rate, and then is divided into several sub-band signals by the analysis filter bank. Secondly, the sub-band signals go through the detection and discrimination module. Finally, the synthesis filter bank reconstitutes the desired signal by synthesis the sub-band channels with signal. This method can synthesis the channels with sub-band signals, which reduces the consumption of hardware resources.

The M filters evenly divide the entire frequency band into M sub-bands.

the synthesis filter bank is

As Equation (1) can be expressed in matrix form, we define the following column vectors:

Then, the matrix representation of Equation (1) can be written as:

The total z-transfer function of the system can be expressed as:

The desired signal z-transfer function can be expressed as:

The undesired aliasing z-transfer function can be expressed as:

Then we can rewrite Equation (8) as:

Let

So, the aliasing cancellation condition can be expressed as:

By the theory of the modulation filter bank, the aliasing cancellation condition can be expressed as:

In order to achieve the aliasing cancellation condition, Equation (10) is required to be the integer delay of the analysis and synthesis filter bank and the z-transform of the frequency response of the detecting and processing sector

Above all, the desired signal z-transform function can be expressed as [

In order to achieve the desired signal perfect reconstruction condition without the detecting and processing sector, the modulation filter bank must satisfy Equations (15) and (16).

The low-pass structure uniform analysis filter bank [

module and the low-pass filter are in a high sampling rate. If the system processes the signal at a high sampling rate, the hardware requirements will be relatively increased.

In order to solve these problems, we use the efficient polyphase structure of the analysis filter bank to replace this structure. We can infer the efficient polyphase structure of the analysis filter by doing polyphase decomposition to the low-pass structure. Through the theory of IDFT and polyphase filtering, we can get the efficient polyphase band-pass structure of the analysis filter bank as shown in

The z-transform function of the output of the IDFT module

Then the z-transform function of the output of the k-th channel can be expressed as:

Because

Then the output signal can be expressed as:

When we put the decimation module in front of the IDFT module, the signal

The z-transform function of

Because

From the above deduction, we can get the improved efficient polyphase structure as shown in

The low-pass structure of the synthesis filter bank was shown in

Assuming that the input signal occupies P sub-band channels, the number of the channel of the input signal of the synthesis filter bank Q should satisfy:

terpolation K should satisfy the following formula:

From

where

Let

Let

Let

Because K is even, so Equation (29) can be expressed as [

where

From the corollary in Reference [

In order to save the hardware resources further, we should improve this structure by using the dynamic reconstruction method [

When the output of the analysis filter bank occupies

The z-transform function of the output of the k-th synthesis filter

Because

Assuming

The first part of the Equation (35) is desired signal; the second part is undesired aliasing. So, we know that even if the perfect reconstruction condition is met, the output signal cannot be completely synthesized. We defined that

Firstly, we need to design the prototype filter. The pass-band cut-off frequency

of the prototype filter is 60 MHz and its stop-band cut-off frequency is 90 MHz. The order of the prototype filter is 127. The sampling rate is 960 MHz, and the number of channel is 8. The decimation time is 4. We input two signals. One is a chirp complex signal from 80 - 160 MHz and the other is a chirp complex signal from 340 - 400 MHz. The first signal occupies the first and second channels and the second signal occupies the third and the 4^{th} these two channels. From the simulation result we can prove the correctness of this structure. The frequency spectrum of the input signals and the output signals are shown in following Figures 7-8.

This paper aimed to solve the problem that the analysis filter bank of the digital channelized receiver cannot receive the cross-channel signal proposes a dynamic reconstruction channelized structure based on uniform channelization. This structure improves the aliasing problem caused by the analysis filter bank and satisfies the perfect reconstruction condition. Because this structure can reduce the design complexity of the filter, when the hardware resource is limited this structure has more advantages.

This work is supported partly by National Natural Science Foundation of China under Grant No. 61301205 and No. 61571146, National Defense Based Science Research Program under Grant No. JCKY2013604B001. This paper is funded by the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation.

Zhang, W.X., Zhao, W.T., He, J.X. and Shi, F.M. (2017) A Non-Maximally Decimated Dynamic Reconfigurable Channelized Structure Based on Modulated Filter Bank. Int. J. Communications, Network and System Sciences, 10, 88-97. https://doi.org/10.4236/ijcns.2017.108B010