J. Bibb Cain

Error-Correction Coding for Digital Communications

1. Fundamental Concepts of Coding.- 2. Group Codes.- 3. Simple Nonalgebraic Decoding Techniques for Group Codes.- 4. Soft Decision Decoding of Block Codes.- 5. Algebraic Techniques for Multiple Error Correction.- 6. Convolutional Code Structure and Viterbi Decoding.- 7. Other Convolutional Decoding Techniques.- 8. System Applications.- Appendix A. Code Generators for BCH Codes.- Appendix B. Code Generators for Convolutional Codes.- B.1. Viterbi Decoding.- B.2. Table Look-up Decoding.- B.3. Threshold Decoding.- B.4. Sequential Decoding.- References.

A "Near-Optimum" Multiple Path Routing Algorithm for Space-Based SDI Networks

This paper presents an adaptive routing algorithm for a mid-course, space-based SDI architecture. The goals include rapid recovery from both predictable and unpredictable outages as well as load balancing. Robust operation is critical. The routing table update algorithm is distributed, and it produces loop-free routes from periodic topology update information. In addition, multiple routes are found from source to destination nodes. This allows load splitting among these routes to achieve more effective load balancing. A heuristic is used to distribute the load among these routes. The basic algorithm also provides a mechanism to provide path diversity for added survivability. Recovery from failures detected locally occurs immediately through the use of alternate routes and an event-driven failure recovery algorithm. Simulation results are presented to demonstrate the algorithm behavior.

Convolutional Code Structure and Viterbi Decoding

The codes and decoding techniques presented in the previous chapters apply only to block codes. With these codes the information sequence is segmented into blocks which are encoded independently. Thus, the coded sequence becomes a sequence of fixed-length independent code words. This is not done with convolutional codes. Instead, redundant symbols are generated as a function of a span of preceding information symbols. The transmitted sequence is actually a single “semi-infinite” code word.

Modeling Architecture for DTDMA Channel Access Protocol for Mobile Network Nodes using Directional Antennas

This paper discusses the combination of a Directional Time Division Multiple Access (DTDMA) scheme implemented in a tactical radio with a directional antenna environment modeled within an OPNET simulated network to increase the throughput for network communications in a wireless environment. A technique of allowing multiple communiations pairs to transmit simultaneous during a single timeslot is a key component of the High-band Network Waveform (HNW). We have implemented a high-fidelity data link layer and physical layer model of this implementation. Along with the DTDMA and directional antenna techniques, the model allows node communication pairs to dynamically adjust their data rates based on signal quality to provide the maximum throughput efficiency along a data link. This waveform model also allows allocation of link capacity as needed on each link to provide bandwidth on demand (BOD). The discussion covers the expected benefits and the implementation as modeled in OPNET.

QoS Architecture for a Mobile Ad Hoc Network

Dynamic allocation of network resources in packet-based mobile ad hoc networks requires the operation of autonomous mechanisms that can provide assurance that the user or host application can reasonably expect a satisfactory quality-of-service (QoS). In general, a combination of mechanisms is required to operate concurrently and in real-time to meet this objective. This paper discusses an architectural framework for a mobile ad hoc node, where the functionality required to achieve QoS is achieved by a combination offunctional layers and cross-layer control methods. The framework enables functionalities to support QoS at the application, transport, network, MAC, and physical levels by adaptation to application traffic loads, network conditions, topology, and radio linkperformance. The QoS framework described provides a basis for many possible implementations. Examples of its application that illustrate key functionalities are discussed. These include: adaptation of physical layer attributes to enhance network fabric capacity, source to destination path selection to enhance end-to-end performance, and admission control to facilitate operation.

Challenges in the Verification of Mobile Ad Hoc Networking Systems

Mobile Ad Hoc Network (MANET) techniques are critical to the success of emerging modern warfare concepts and are required to support communications for mobile military platforms, including ships, aircrafts, and ground vehicles operating in a highly dynamic and mobile tactical communications network without fixed infrastructure. Research in Mobile Ad Hoc Networking has increased dramatically over the last few years with significant work in hardware architectures, media access and routing protocols. Until now, most of the work has been in simulation and small-scale laboratory demonstrations due to the significant resources required to implement an actual network with sufficient nodes to fully exercise the capabilities of both the hardware and software. There is significant need to develop testbeds to fully understand the behavior of ad hoc networks, performance under real-world application scenarios. This paper describes a testbed for a real system application exercised in an outdoor environment which approximates very closely the physical operational environment. The ad hoc network performance results include throughput and delay under conditions of mobility and foliage.

Fundamental Concepts of Coding

When digital data are transmitted over a noisy channel, there is always a chance that the received data will contain errors. The user generally establishes an error rate above which the received data are not usable. If the received data will not meet the error rate requirement, error-correction coding can often be used to reduce errors to a level at which they can be tolerated. In recent years the use of error-correction coding for solving this type of problem has become widespread.

Optimizing Performance On Unreliable, Dynamic Networks

This paper discusses link-assignment and adaptive routing algorithms that have been developed for networks consisting of a large number of mobile nodes having directive links. We focus on the special case where data rates are large (tens of Mbits/sec) and the propagation delay between nodes may be large compared to packet transmission delay. In such circumstances, queue sizes at store-and-forward nodes can become extravagant if retransmissions are required because of lost or damaged packets. The algorithms employ techniques that provide a high probability of successful message delivery on the first transmission attempt in the unreliable network. The link-assignment algorithm builds and maintains a link topology that provides multiple node-disjoint paths between each source and destination. Decisions regarding topology changes are also based on link permanency and ability to carry the anticipated traffic load. The adaptive routing algorithm establishes routing tables for multiple independent paths that are maximally node-disjoint between all sources and destinations. Load splitting techniques are used to achieve better load balancing and also to provide a mechanism for rapid adaptation around failed links. All algorithms are distributed in the sense that each node makes independent decisions. Heuristic optimization techniques are used to reduce computation time to within affordable limits. The routing algorithm also responds well to transients in traffic loading.

Soft Decision Decoding of Block Codes

The use of soft decisions with block codes provides the engineer with another degree of freedom when designing a communication system. The additional information provided by the soft decisions in most instances can provide about 2 dB of additional coding gain and can, therefore, significantly increase the usefulness of a particular code. Soft decision decoding is particularly effective when used with moderate length block codes and provides substantial performance benefits over a broad range of signal-to-noise ratios. It is also effective in concatenation schemes (see Chapter 8) which utilize two or more levels of encoding and decoding. In this case the use of soft decisions is restricted to the innermost coder/decoder, and it is necessary for the soft decision decoding method to provide near optimum performance at word error rates in the range of 10−2 to 10−3. This is in contrast to the usual system requirement that the decoding scheme be effective at error rates less than 10−5.

Simple Nonalgebraic Decoding Techniques for Group Codes

Decoding techniques for group codes can be divided into two general categories, algebraic and nonalgebraic. The algebraic techniques basically involve the simultaneous solution of sets of equations for the location and values of the errors. The nonalgebraic techniques, while accomplishing the same goal, are based upon simple structural aspects of the codes which permit one to determine the error patterns in a more direct fashion. In this chapter three nonalgebraic techniques will be discussed. These are Meggitt decoders,(12) first introduced by Meggitt in 1961 for the correction of burst errors, threshold decoders(13) introduced by Massey in 1963, and information set decoding,(14) which was first introduced by Prange in 1962. The discussion will concern only binary codes except when it is specifically noted that the results apply to nonbinary codes as well.