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Text for "Detection of Decodable Packet Signals in the Presence of Noise and Interference Impairments"

IP.com Disclosure Number: IPCOM000021263D
Original Publication Date: 2004-Jan-08
Included in the Prior Art Database: 2004-Jan-08

Publishing Venue

Motorola

Related People

Patrick D. Smith: AUTHOR [+2]

Abstract

In many multiple-access communication systems, noise and interference corrupt transmitted signals, causing them to be received and decoded with errors. Examples of corruption sources are AWGN, burst noise, spurious narrowband signals, and in the multiple-access case, signals transmitted from other sources. Shared channels such as DOCSIS have a fundamental limit to scalability, due to the growth in number of entry points for sources of corruption.

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Text for “Detection of Decodable Packet Signals in the Presence of Noise and Interference Impairments”

Patrick D. Smith

Patrick Maurer

Abstract:

In many multiple-access communication systems, noise and interference corrupt transmitted signals, causing them to be received and decoded with errors. Examples of corruption sources are AWGN, burst noise, spurious narrowband signals, and in the multiple-access case, signals transmitted from other sources. Shared channels such as DOCSIS have a fundamental limit to scalability, due to the growth in number of entry points for sources of corruption. A solution to this problem is to partition the shared channel into multiple branches, each with fewer nodes, and perform full demodulation and decoding at the merge point. This can require costly signal processors to perform the demodulation and decoding. At certain nodes of such a system, it may be simpler and cheaper to detect the presence of valid signals without actually decoding them, and to pass only energy determined to be valid signal. In this way, noise in a system can be trapped and blocked, rather than allowed to disrupt the entire system. A good detector for this purpose will be based on qualities of valid signals not present in noise or corrupted signals. Notably, detectors that search for the presence of information (entropy detectors) and for signals with a specific amplitude and duration (envelope detectors) are useful. For certain classes of signal, the presence of information can be verified through a signal’s transformation from the time domain into the amplitude vs. frequency domain. The statistical variance of a signal’s amplitude vs. frequency domain representation can then be used to judge whether modulation and therefore information is present on the signal. This approach requires no timing recovery or demodulation of the original signal and can therefore be considered computationally simple and modulation unbiased. Additionally, signals corrupted by packet collisions or burst noise can be filtered out without demodulation and decoding by comparing possible signals against an energy profile for valid signals.

Body:

One of the advantages of a scalable node managed communications network is the ability to add and subtract subscribers and hardware resources at many different points within the system while minimizing unique communication link paths and therefore maximizing network utilization at the lowest cost. A compromise of this scalability comes in the form of further and further communication traffic concentration as the subscriber’s signal moves further and further up the physical signaling link. This can be represented as a system whose subscribers each have a dedicated physical communication connection that aggregates its traffic at intermediate points within the signaling chain. Figure 1: Bi-Directional Communication System with Multiple Aggregation Nodes is a generic example of such a system where two levels of subscr...