Mobile communications are rapidly becoming more and more necessary for everyday activities. With so many more users to accommodate, more efficient use of bandwidth is a priority among cellular phone system operators. Equally important is the security and reliability of these calls. One solution that has been offered is a code division multiple access system. The research in this field has been enormous in the past few years. One of the problems associated with this type of system is detecting and demodulating a desired user. When asynchronism and non-orthogonality are introduced into the system, this problem can become overwhelming. The idea behind this project is to develop simulation tools which allow generation of a realistic system and the testing of different fixed and adaptive linear detectors.
Code Division Multiple Access(CDMA) is one method for implementing a multiple access communication system. A multiple access system has a design which allows multiple users to transmit information over the same channel, or frequency bandwidth, to a receiver. In a cellular communication system, this corresponds to the multitude of mobile units all transmitting to a single base station. Figure 1.1 depicts such a situation.
Since there are
multiple users transmitting over the same channel, a method must be
established so that individual users will not disrupt one another.
There are essentially three ways in which to do this, Frequency
Division Multiple Access(FDMA), Time Division Multiple Access(TDMA), and Code
Division Multiple Access(CDMA). The idea behind FDMA, is to split up
the available channel into non-overlapping frequency bins and each
active user will be assigned an individual band. In this case, the
receiver can tune to the specified band and demodulate the
information. In a TDMA system, the channel is divided into time
segments and a time segment is assigned to each active user. In
these systems, each users is essentially orthogonal in either time or
frequency, which makes detection and demodulation a relatively easy
task. However, these systems can not take advantage of the properties
of the transmitted data. Voice data tends to be very bursty in
nature, so much of the time no data is being sent over the
channel. This inefficiency tends to limit the capacity of the system.
In a CDMA system the users are spread across both frequency and time
in the same channel. The capacity of this system depends on the amount of
interference from the other users. If all the users are transmitting
at the same rate and the system is synchronous, we find that the
capacity of the CDMA system is equal to that of the FDMA and TDMA
systems. 
It is shown in
[4] that if the users transmit at different rates,
synchronous CDMA can achieve greater capacity than the FDMA and TDMA systems.
CDMA is a system which is based on spread spectrum technology. A spread spectrum signal is characterized by a bandwidth which is used to decrease the transmitting power and eliminate interference from other users as well as interference from the same user. The pseudo-random codes, or pseudo-noise sequences (pn sequences), used to increase the bandwidth are essential for providing security and decreasing eavesdropping detectability. Two different CDMA technologies are based upon the use of pn sequences. R-CDMA, or Random-CDMA, utilizes extremely long pseudo-noise codes which span millions of bits. This type of system is relatively unsuited for linear detectors which utilize each users unique spreading code. The long codes are used to make multiple access interference (MAI) appear as white Gaussian noise, the affects of which are overcome by powerful error control coding. DS-CDMA, or Direct Sequence-CDMA, makes use of short, bit-length pn sequences. The low cross correlation properties these codes exhibit are exploited in linear interference cancellation and detection. Each code essentially provides each user with its own subspace, allowing the linear detector to remove MAI. Most linear receivers for DS-CDMA utilize knowledge of these spreading codes to remove interference from the received signals. The extent to which the knowledge of the codes and message and channel statistics are utilized distinguishes the performance and structure of these receivers.
The remainder of this report addresses the development of different fixed and adaptive linear detectors and includes documentation of the software created to test the linear detectors. In chapter 2 a system model for a DS-CDMA system including channel ISI and asynchronism is developed. The following chapter includes descriptions and derivations of the different linear detectors implemented in the software. Chapter 4 describes the design process for developing the software package and includes documentation of the software. Finally, various simulation results are provided in chapter 5.