The notion of perceptual coding, which is based on the concept of distortion masking by the signal being compressed, is developed. Progress in this field as a result of advances in classical coding theory, modeling of human perception, and digital signal processing, is described. It is proposed that fundamental limits in the science can be expressed by the semiquantitative concepts of perceptual entropy and the perceptual distortion-rate function, and current compression technology is examined in that framework. Problems and future research directions are summarized. >

Signal compression based on models of human perception

A description of technology targets in signal compression and a nonexhaustive account of research directions that may lead toward these targets are presented. Opportunities for integrating source coding and channel coding technologies are also pointed out. Such integration, which has hitherto been an informal exercise, will become increasingly essential as communication capabilities are stretched with capacity-limited channels such as wireless media. In parallel, as greater sophistication is sought in the integration of speech and data with broadband signals such as CD-audio and high-resolution video, there will be increased interaction of signal compression technology with the field of communication networking. >

Signal compression: technology targets and research directions

Algorithms for solving for the cell loss rates in an asynchronous transfer mode (ATM) network using cell loss priorities are presented. With the loss priority scheme, cells of low-priority classes are accepted only if the instantaneous buffer queue length at the cell arrival epoch is below a given threshold. The input is modeled by Markov-modulated Bernoulli processes. The effect of the loss priority scheme on data, voice, and video traffic is investigated. >

An efficient solution method for Markov models of ATM links with loss priorities

Some methods of supporting voice in broadband ISDN, (B-ISDN) asynchronous transfer mode (ATM), including voice compression, are examined. Techniques for voice compression with variable-length packet format at DS1 transmission rate, e.g., wideband packet technology (WPT), have been successfully implemented utilizing embedded adaptive differential pulse code modulation (ADPCM) coding, digital speech interpolation (DSI), and block-dropping schemes. For supporting voice in B-ISDN, voice compression techniques are considered that are similar to those used in WPT but with different packetization and congestion control methods designed for the fixed-length ATM protocol at high speeds. Possible approaches for packetization and implementation of variable-bit-rate voice coding schemes are described. ADPCM and DSI for voice coding and compression and cell discarding (CD) for congestion control are considered. The advantages of voice compression and CD in broadband ATM networks are demonstrated in terms of transmission bandwidth savings and resiliency of the network during congestion. >

Voice packetization and compression in broadband ATM networks

ATM is a broadband fast-packet technology, but its modern technological base should make it less expensive than existing circuit switching systems once economies of scale are reached. The article examines the use of ATM to address the growth of emerging narrowband services such as frame relay. ATM's flexibility in supporting variable rates and levels of service make it an ideal network technology to carry multiple services. While B-ISDN services promise many benefits to users, major issues must be addressed before such services can be available on a large scale. Utilizing ATM as a backbone technology to support the growing capacity needs of emerging narrowband services could facilitate more rapid introduction of ATM into the network infrastructure and speed delivery of future BISDN services. >

ATM for narrowband services

A type of speech coding for asynchronous transfer mode (ATM) is described. Cell processing, which improves service quality, is taken into account. Missing-cell recovery methods are discussed, and the distinctive features of missing-cell recovery methods used with low-bit-rate coding are examined. An example of the speech quality obtained using speech coding techniques in the ATM networks is described. The performance levels for increasing cell loss are compared for various speech coding methods, in combination with methods for dividing coded speech signals into cells and discarding cells. Representative feasible network applications of coding technologies are considered. >

M. Taka

Papers

Speech coding technology for ATM networks