ABSTRACT
Due to the substantial increase in the number of devices in 5G networks, traditional multiple-access techniques cannot utilize the time frequency space sufficiently to satisfy demand. One way to increase utilization of the available time frequency space is to apply non-orthogonal multiple access (NOMA) techniques coupled with complex message-passing algorithms at the receiver which allows user capacity in 5G networks to be increased. In the NOMA system, users at any given time occupy the same resource element, while different interference cancellation procedures are used to separate users. For instance, in NOMA multi-user shared access (MUSA) techniques that use short-spreading codes, interference cancellation (IC) is needed because of their short length, and the codes are not fully orthogonal. In the other NOMA version, pattern division multiple access (PDMA) sequences depict patterns whose elements are allocated the same resource elements. Other multiple-access techniques like Interleaved multiple access are also possible. In this chapter, we first define a system for algebraic construction of short quasi-orthogonal PDMA patterns that fit perfectly in NOMA PDMA. These patterns are characterized by superb separation properties and their huge number within the family. By family we mean a set of patterns of identical length and weight. Characteristics of polynomials over finite fields are used to create patterns. Creating patterns with different weights within each family is also explained as one of the possibilities. We then extend the construction to complex sequences and show that the sequences can also be used in MUSA. We use pseudorandom noise (PN) sequences to compare the performances we achieve with our sequences. Performances of our sequences are obtained using link-level simulations. A performance comparison is also performed with the corresponding sequences from different PDMA and MUSA systems-related literature. The advantage of the proposed ways of constructing our sequences applied in IoT systems in relation to random sequences is reflected in improved system performance.
