Signal Processing Fundamentals
There are a few important principles that are essential to the comprehension of signal processing in wireless systems. This chapter describes each of these concepts in detail. It is important for network designers to have a good understanding of these principles to be able to properly dimension network resources.
4.1 Digitizing Analog Signals
Analog signals carry a lot of redundancy and are hard to retrieve from noise whereas digital data conveys information as a stream of ones and zeros, which can be more easily recovered. Digital information can represent numbers, codes, images, text or even analog signals. To do so, analog signals have to be digitized and the fundaments to do it are established by the sampling theorem.
Digital data is generally grouped into packets; each packet carrying data and a source and destination address, IP (Internet Protocol) being a typical example of this.
To digitize and analog a signal two questions have to be answered: can a continuous analog signal be fully represented by discrete samples? And, if so, how many of them are required?
Many authors have contributed to this topic, but two papers are considered fundamental. In 1928, Harry Nyquist published a paper entitled “Certain topics in telegraph transmission theory”, where he demonstrated that 2*B independent pulse samples can be sent through a system with a bandwidth B. Then, in 1949, Claude Shannon in his paper, “Communications on presence of noise” ...