Application of Cognitive Radio in Emergency Communication after Earthquake
Abstract: In order to carry out rescue work immediately after the earthquake, it is essential to restore the communication system as soon as possible. According to the particularity and requirements of emergency communications, based on the analysis of the key technologies of cognitive radio, a communication model based on cognitive radio technology is established, and the solution to the post-earthquake communication line congestion and the improvement of low frequency spectrum utilization rate New ideas. Three methods of spectrum sensing are introduced in detail: matched filter detection, energy detection, and periodic stationary process feature detection. The research of cognitive radio technology provides a new thinking mode and technical prospects for post-earthquake emergency communication construction.
Keywords: cognitive radio, spectrum sensing, matched filter detection, energy detection, periodic stationary process feature detection
1. Foreword The Sichuan Wenchuan earthquake caused huge loss of life and property. The key to saving the loss is how to quickly and effectively restore emergency communications after the earthquake, so as to understand the disaster situation, unified command, and better organization during the 72-hour golden rescue time after the disaster Coordination, so the recovery of emergency communications after a disaster is crucial. When an earthquake occurs, telecommunications companies are faced with two major tests: on the one hand, the communication network has been damaged to varying degrees due to disasters, and the ability to guarantee information and communication services has been greatly reduced; on the other hand, after the disaster, the government and the public are very eager to understand In the disaster situation, the communication business grew in a "blowout style", forming communication congestion. In the face of these two major problems, some people proposed the construction of secondary routes for important lines and the improvement of disaster resistance through the construction of back-up trunk lines; and the establishment of an emergency communication method with a combination of heaven and earth and various modes. However, these are only for prevention from the construction of lines and the diversification of ways. In the face of the huge information flow of emergency communications after disasters, can these lines withstand such a large amount of information? Will it cause communication congestion again? Cognitive radio technology starts from solving the problem of low spectrum utilization rate in high frequency bands, so that wireless communication equipment can access authorized high-frequency idle spectrum and use the spectrum dynamically, which is expected to alleviate the congestion problem of existing communication lines and is used for emergency communication. The construction unfolded another technological prospect.
2. Basic Concepts of Cognitive Radio The concept of cognitive radio was proposed by Joseph Mitola in 1999. Its core idea is to enable wireless communication devices to discover idle spectrum and use spectrum resources reasonably. As we all know, the radio communication spectrum is a precious natural resource, generally authorized by the government. In the hundreds of MHZ-3GHZ wireless frequency bands with very tight frequency requirements, some bands are not used by users for most of the time, while others are only occasionally occupied, and competition for the use of other frequency bands is relatively fierce. Cognitive radio is considered to be the best solution to the current wireless spectrum utilization rate. It is an intelligent wireless communication system with environmental awareness and self-modification of transmission parameters. It can change and adjust its internal state in real time through the understanding of the environment. , To adapt to changes in the external wireless environment, thereby achieving spectrum sharing, dynamically increasing the total number of available spectrum for the network and individual users, providing a possible solution for spectrum allocation.
The cognitive ability of cognitive radio is manifested in its ability to interact with its environment in real time, thereby determining the appropriate communication parameters and adapting to the dynamic wireless environment. This task requires adaptive operation in the open spectrum, as shown in Figure 1, called the cognitive cycle. The cognitive cycle consists of three main steps: spectrum sensing, spectrum analysis, and spectrum decision-making.
3. The emergency communication model of cognitive radio is aimed at the problems of communication systems after an earthquake. Due to the limited channel capacity of common frequency bands, the sudden increase in traffic will cause channel congestion. Figure 2 shows a model of a signal transmission system based on cognitive radio. The design of the model is to perform signal processing on the measured signal space, find the signal from the noise background and extract the information carried by the signal, and formulate a detection estimate. Guidelines, make a report of the presence or absence of authorized users (or spectrum holes), which is the spectrum sensing process of cognitive radio, and then divide the frequency band of spectrum holes into several channels, and modulate the baseband signal to the gap band In fact, the spectrum is moved, and the relatively lower frequency spectrum is moved to a higher frequency spectrum, so that the signal can be transmitted on these high-frequency channels. 
Figure 1 Cognitive cycle
Figure 2 Diagram of signal transmission model based on cognitive radio
Perform signal processing, find the signal from the noise background and extract the information carried by the signal, and formulate detection and estimation criteria, and make a detection report of the existence (or spectrum hole) of authorized users. This is the spectrum sensing process of cognitive radio , And then divide the frequency band of the spectrum hole into several channels, and modulate the baseband signal to the gap frequency band, which is actually the spectrum shift, moving the relatively low frequency spectrum to the higher frequency spectrum, so that the signal can be at these high frequencies The transmission is on the channel.
4. Cognitive Radio Spectrum Sensing Technology Spectrum sensing is the basic function of cognitive radio systems and the premise for spectrum management and spectrum sharing. The so-called "perception" is to continuously perform spectrum detection on the frequency bands allocated to authorized users in the time domain, frequency domain and space domain multi-dimensional space, to detect whether the main users in these frequency bands work, so as to obtain spectrum usage. If the frequency band is not occupied by authorized users, the frequency band is called "spectrum hole", and cognitive users can temporarily use the spectrum hole. Combining with the above model, there are usually three detection schemes of matching detection, energy detection and periodic stationary process feature detection to detect the user source.
4.1 Matching filter detection Matching filter detection is a more commonly used method in signal detection, which can maximize the signal-to-noise ratio of the received signal. The use of matched filters in cognitive radio equipment actually completes the demodulation of the authorized user's signal, so that cognitive radio users must know the information of the authorized user's physical layer and media control layer, use these to achieve The signal is synchronized in the time and frequency domains, thereby demodulating the signal. The advantage of this detection method is that it can complete synchronization in a short time and improve the signal processing gain. The disadvantage is that the user must be aware of the various information of each type of authorized user.
4.2 Energy detection Energy detection is a non-coherent detection method, it only needs to know the energy of the signal in the detected frequency band. In order to measure the energy of the received signal, the output signal of the band-pass filter needs to be squared and integrated within the observation period, and the output of the integrator is compared with a fixed threshold. Because this detection method is limited by the detection threshold, the perception accuracy is not high, and it is usually used in the rough perception stage. The energy detection model is shown in Figure 3.
Figure 3 Energy detection model
When measuring energy detection performance, it is generally assumed that the transmission channel is Gaussian distributed and the noise is Gaussian white noise with zero mean. Suppose that the received signal passes the filter with the bandwidth, the detection time is, and the threshold is K, then the probability of false alarm is:
Is the variance of the received signal and noise.
4.3 Periodic stationary process feature detection The periodic stationary process feature detection can extract the unique characteristics of the modulated signal, such as sinusoidal carrier, symbol rate and modulation type. These characteristics are detected by analyzing the spectral correlation function. The main advantage of the spectral correlation function is that it can distinguish the noise energy from the power of the modulated signal, provided that the noise is an incoherent generalized stationary signal, and the modulated signal is periodic stable and spectrally coherent after the signal period is inserted with redundancy. In the environment of unknown noise, power change noise and strong interference, feature detection of periodic stationary processes has advantages over other detections. The spectrum correlation detection model is shown in Figure 4.
Assuming that the signal is cyclically stable and the power is limited, the cyclic autocorrelation function (CAF) is defined as
The parameter is called the cycle frequency, and each cycle frequency is an integer multiple of the signal duration T. At that time, CAF and CSD were commonly known as autocorrelation functions and power spectral densities. Different signals have different cyclic power spectra. This feature can be used to detect input information. The decision method is
5. Conclusion Starting from the study of the key technologies of cognitive radio, combined with the requirements and particularities of emergency communications, the two can be organically combined. The spectrum sensing technology of cognitive radio technology is used to solve the problem of congestion of intermediate frequency channels in emergency communications and low spectrum utilization in high frequency bands, which maximizes the improvement of post-disaster communication lines. The establishment of emergency communication systems saves disaster relief work This precious time has also provided a new mode of thinking and technological prospects for the development and construction of emergency communication systems.
references:
[1] Zhou Xianwei. Cognitive radio [M]. National Defense Industry Press, 2008
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[3] Tan Xuezhi, Jiang Jing, Sun Hongjian. Research on Spectrum Sensing Technology of Cognitive Radio [J]. Communication Technology, 2007, 3: 61-63
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