Compression Method Of Spectrum Status Information Based On Adaptive Differential

Due to the development of the wireless communication technology, the number of the users and business is getting bigger and bigger, which leads to the fact that the amount of the spectrum resources is getting smaller and smaller. So, people begin to focus on improving the utilization of the spectrum and a good way to solve this problem is using cognitive radio. This technology can find the spectrum holes by sensing the surrounding environment and then makes good use of them, which in turn leads to the improvement of the utilization of the spectrum.Because the spectrum sensing technology needs sensing the surrounding environment accurately, so it will get a lot of spectrum status information. If we do not do data preprocessing and just transmit them directly to the management center or other users, this will put great pressure on the cognitive communication system and this will also take a long time to transmit and occupy a larger bandwidth. So, to solve this problem, this article discusses some data processing methods to reduce the huge amounts of data on the basis of meeting the requirement of the cognitive system.There are many existing methods which can reduce the amount of the spectrum status information, such as sentence processing, compressed sensing, methods based on data compression(e.g. Huffman coding) and so on. But each of them has some disadvantages. For example, the threshold of sentence processing is difficult to set, which will leads to the loss of data. Compressed sensing requires that the signal should be sparse but not all of the signals meet that requirement. Methods based on data compression, such as Huffman coding, its disadvantage is that the compression performance is relevant to the probability distribution of the data: when the probability distribution is overbalanced, the compression performance is the best; when it is balanced, the performance is the worst.To solve the problem properly, this article puts forward a good method for spectrum status information compression. First, convert the difference between spectrum data into binary sequence by adaptive delta encoding. Then, transfer the compressed data to the management center. In this way, each of the original data can be represented in only 1 bit information. So, the compression performance is very good. When the management center is ready to restore the original sensed data, it can adaptively adjust the difference between the original data according to the internal relation between the compressed data. And add this difference to get the value of the data on the basis of the value of the previous data. Then, all of the original data can be restored. By using this method, only a small amount of data needs to be transmitted, which achieves the purpose of data compression. Not only will this method deduce the transmission time, but also save the spectrum resources and reduce the network load.At last, this article accomplishes the spectrum sensing function and the methods for spectrum status information compression. In addition, this article also analyzes and compares these methods' performance.