Many methods of digital communication rely on representing binary data with what is inherently an analog signal, an electromagnetic wave. At a transmitter, digital signals originally take the form of a series of squared-off dips and pulses. During transmission of the signal, characteristics of the communication channel over which the signal is sent distort the pulses. On receipt of such a signal, before using the data in the transmission, the receiver must first decipher from the incoming wave what data the sender intended to transmit. Thus, transmitters send symbols encoded as analog signal waveforms, and receivers convert the waveforms back into symbols. An analog-to-digital (A/D) converter in the receiver samples the waveform and outputs a series of binary numbers representing the waveform as a discretized time series. This digital representation is then amenable to signal processing by a digital computer.
Sampling with more bits of resolution preserves more of the information in the received waveform and therefore enables more accurate decoding of its information content by the receiver, but consumes more power and silicon “real estate” in the A/D converter. In general, a higher-resolution digital representation also requires a larger and more powerful digital computer.
Receiving systems have employed two types of A/D converters to guess the intended values of components of incoming signal. In both cases, the converters average the value of the signal over a predetermined period of time. One class of converters compares the magnitude of that average to a threshold. If the magnitude of the averaged sample exceeds the threshold, the converter assumes that the transmitter intended to send a bit representing a one. If the magnitude fails to cross the threshold, the A/D converter assumes that the transmitter intended to send a zero. Basing a guess on a fixed threshold is vulnerable to inaccuracy due to noise and other forms of signal interference. Merely because a sample value falls below, for example, the midpoint between voltage levels corresponding to zero and one does not guarantee that a zero was in fact transmitted.
The second type of A/D converter incorporates the information that can be gleaned from the exact magnitude of a sampled signal. This magnitude is stored as a series of bits (CD players use 10 bits, for example). With this series of bits, the system can use decoding algorithms and digital logic operations representing probabilistic functions to guess the intended value of a received bit with more accuracy than could be done with a thresholding system. Implementing this second approach, however, typically requires the use of thousands of transistors and a relatively large amount of power.
In order to more accurately guess the intended values of a received signal component at a given time point, a receiving system ordinarily synchronizes itself with the incoming data stream. Synchronization prevents the receiving system from attempting to guess the intended value of a signal component over a time in which the intended value of that signal is in transition.
Synchronization has been achieved by the receiver using phase lock loops (PLLs) or by the sender transmitting a synchronization signal along with data. PLLs are typically power-hungry while sending a synchronization signal wastes bandwidth. Accordingly, the power necessary to operate the value guessing and synchronization logic in traditional communications systems tends to require the use of large batteries, frequent recharges, or both.