In Chapter 19 we apply methods developed in the previous chapters (namely the weak converse and the random/maximal coding achievability) to compute the channel capacity. This latter notion quantifies the maximal amount of (data) bits that can be reliably communicated per single channel use in the limit of using the channel many times. Formalizing the latter statement will require introducing the concept of a communication channel. Then for special kinds of channels (the memoryless and the information-stable ones) we will show that computing the channel capacity reduces to maximizing the (sequence of the) mutual information. This result, known as Shannon’s noisy channel coding theorem, is very special as it relates the value of a (discrete, combinatorial) optimization problem over codebooks to that of a (convex) optimization problem over information measures. It builds a bridge between the abstraction of information measures (Part I) and practical engineering problems.

The fundamentals of analog and digital modulation techniques are presented in Chapter 6. The theoretical underpinnings of the world's most popular amplitude modulations, frequency modulations, and phase modulations are presented. The impact of pulse shape and filtering on bit error rate of a mobile communication system is demonstrated, where Doppler spread creates an irreducible bit error rate no matter how good the signal-to-noise ratio, yet is below the noise created by other aspects of the radio system. This led Europe to select GMSK for the pan-European 2G digital cellular standard, whereas the US selected a pi/4 PSK modulation method originated in Japan that allows both coherent and non-coherent demodulation and a graceful upgrade path for existing operators to adopt the new digital modulation with gradual base station changeouts over time.Capacity and Shannon's limit are defined and explained through numerous examples.

In this chapter, differences between magnetic communication and electromagnetic wave-based communication are summarized and major advantages of magnetic communication are discussed, which provides a big picture of the applicable scenarios of magnetic communication. In addition, the physical circuit for magnetic communications is introduced. The fundamental performance metrics, such as path loss, bandwidth, capacity, and connectivity are discussed.

The performance analysis for ambient backscatter communication systems is fundamentally different from that of traditional communication systems. The carrier signal of backscatter communication is opportunistically exploited from the existing active radio-frequency communication systems. As it is vulnerable to channel variations, different detection and encoding mechanisms have been proposed and analyzed to improve the system throughput or ergodic capacity. In this chapter, we have focused on the analysis of signal detection and bit-error rate (BER) performance for backscatter communication. We have reviewed the different system models for backscatter communication systems and various signal detection approaches under different resource and physical constraints.