Pulse or digital communications – Spread spectrum – Direct sequence
Reexamination Certificate
1997-12-31
2001-04-10
Vo, Don N. (Department: 2631)
Pulse or digital communications
Spread spectrum
Direct sequence
C375S141000, C375S147000
Reexamination Certificate
active
06215813
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to spread spectrum communications systems. More particularly, this invention relates to the encoding, modulation, demodulation, and decoding of communication signals in a spread spectrum communications system.
BACKGROUND OF THE INVENTION
A typical prior art communication system comprises a transmitting station and a receiving station, and a connecting medium called a channel. Two-way communication requires each station to have both a transmitter and a receiver.
FIG. 1
is a functional block diagram of a prior art communication system. The transmitting subsystem
102
of this communication system
100
accepts either digital or analog signals as inputs. An analog-to-digital converter
104
is coupled to receive an analog input signal
106
and to periodically sample the analog input waveform. The digital signal
108
, comprising discrete voltage levels, output from the analog-to-digital converter is coupled to be received by a source encoder
110
. The general purpose of the source encoder
110
is to convert effectively each discrete symbol into a suitable digital representation, often binary.
In some systems where no channel encoding function
112
is present, the source encoder
110
output is converted directly to a suitable waveform within the modulation function for transmission over the channel. Noise and interference added to the waveform cause the receiver's demodulation operation to make errors in its effort to recover, or determine, the correct digital representation used in the transmitter. By including the channel encoding
112
function in the typical communication system, the effects of channel-caused errors can be reduced. The channel encoder
112
makes this reduction possible by adding controlled redundancy to the source encoder's
110
digital representation in a known manner such that errors may be reduced. The channel encoded signal is coupled to be received by the modulator
114
. The modulator
114
converts the binary symbols of the source information into a suitable waveform for transmission over the channel
116
using a signal with a particular carrier frequency.
The functions performed in the receiving subsystem
118
typically reflect the inverse operations of those in the transmitting subsystem
102
. The demodulator
120
recovers the best possible version of the output that was produced by the channel encoder
112
at the transmitter subsystem
102
. The channel decoder
122
reconstructs, to the best extent possible, the output that was generated by the source encoder
110
at the transmitter subsystem
102
. It is here that the controlled redundancy inserted by the channel encoder
112
may be used to identify and correct some channel-caused errors in the demodulator's
120
output. The source decoder
124
performs the exact inverse of the source encoding
110
function.
As previously discussed, the purpose of the channel encoder is to convert the source code to a form that will allow the receiver to reduce the number of errors that occur in its output due to channel noise. As such, the channel encoder adds redundancy to the source code by inserting extra code digits in a controlled manner so that the receiver can possibly detect and correct channel-caused errors. One class of encoding process uses a coding method and apparatus that produces convolutional codes.
Convolutional codes involve memory implemented in the form of binary shift registers having K cascaded registers, each with k stages. The sequence of source digits is shifted into and along the overall register, k bits at a time. Appropriate taps from the various register stages are connected to n modulo-2 adders. The output code becomes the sequence of n digits at the output of these adders generated once for every input shift of k source digits. The ratio k
is called the code rate, and K is called the constraint length. Therefore, each n-bit output codeword depends on the most recent k source bits stored in the first k-stage shift register as well as K−1 earlier blocks of k source bits that are stored in the other registers.
Tree diagrams, trellis diagrams, and state diagrams may be used to describe a convolutional code. The number of branches in a tree diagram doubles each time a new input digit occurs. For a long sequence of input digits to be encoded, the usefulness of the tree diagram is limited. A better approach uses a trellis diagram because the trellis diagram, while carrying the same information as a tree diagram, makes use of the fact that the tree is periodic in the steady state condition and involves only a finite number of states. The typical convolutional encoder of rate k
and constraint length K will have 2
k
branches leaving each state node making the number of possible states 2
k(K−1)
.
In the receiver subsystem, the demodulator will estimate what sequence of binary digits is being received over the channel. The purpose of the channel decoder is to accept the erroneous sequence of demodulator output digits and produce the most accurate replica possible of the source sequence that was input to the channel encoder of the transmitter subsystem.
For convolutional codes, the optimum decoding process amounts to finding the single path through the code trellis that most nearly represents the demodulated bit sequence. The transmitted code digits correspond to a specific path through the trellis. However, the receiver has no knowledge of the exact path and it can only use the received sequence, which possibly has errors, to find the most likely path that corresponds to the received sequence. This most likely path is then used to specify the decoded data sequence that would have generated the path. This procedure is called maximum-likelihood decoding. The Viterbi algorithm is a maximum-likelihood decoding procedure based on finding the trellis path with the smallest distance between its digit sequence and the received sequence. Typically, the distance used is the Hamming distance wherein the Hamming distance between two codewords of the same length is defined as the number of digits that differ in the two sequences. For example, the sequence “011010111” differs from the sequence “111001101 in digits 1, 5, 6, and 8, so the Hamming distance is 4.
Over the last several years, the development and use of wireless communications has, been significant. In the 1980's, numerous analog cellular networks were implemented, many of which quickly reached capacity limits, especially in the large service areas of metropolitan cities. The wireless telecommunications industry, in anticipation of these limitations, introduced several digital technologies to increase spectral efficiency and enhance wireless communications. The enhancements included the addition of features and services such as facsimile and data transmission and various call handling features. Thus, wireless communication technology has evolved from simple first-generation analog systems for business applications to second-generation digital systems with features and services for residential and business environments. Currently, the third-generation systems are being developed, known as personal communications systems (PCS). These PCS systems will enable the wireless network to deliver telecommunication services, including voice, data, and video, without restrictions on the portable terminal, location in the world, point of access to the network, access technology, or transport methods.
In the digital technologies associated with wireless communications, there are two basic strategies whereby a fixed spectrum resource can be allocated to different users: narrowband channelized systems and wideband systems. Two narrowband systems are the frequency-division multiple access (FDMA) systems and the time-division multiple access (TDMA) systems. In terms of improved capacity, the wideband systems are the better alternative because the entire system bandwidth is made available to each user and is many times larger than the bandwidth required to transmit
Jones William W.
Kenney Thomas J.
Blakely , Sokoloff, Taylor & Zafman LLP
Sony Corporation
Vo Don N.
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