Distributed Fair Channel Access in Multi-Level NOMA Random Access Systems

Abstract

With the popularity of intelligent terminals, the demand for wireless transmission rates has grown exponentially. Especially, various applications in Internet of Things (IoT), enterprise networking and critical communications make channel access challengeable for the 5G networks. Therefore, in order to meet high data rate and support massive connectivity that require the medium access control (MAC) to enable the high throughput. By accommodating multiple users at the same resource block (RB) (e.g, frequency and time), non-orthogonal multiple access (NOMA), is capable of improving the spectral efficiency (SE) significantly compared with orthogonal multiple access (OMA). Recently, uplink Power-Domain NOMA (PD-NOMA) becomes the major technique to multiplex the signals, while there are still some pressing challenges for the development. Such as, supporting the fairness for boundary users while improving total system throughput; proposing novel algorithms that are suitable for multiple power levels; and reducing the computation complexity of optimization algorithms.

In this thesis, we first discuss the ALOHA random access protocol and the general framework and key techniques of NOMA. Then, we make a brief classification of typical NOMA schemes and comprehensively investigate on the basic principles in order to clearly understand the NOMA schemes. Finally, yet importantly, we apply NOMA to uplink random access (RA) systems in which users randomly transmit packets in each slot while the transmit power is adjusted so that the receive power of each packet at the base station can be one of predetermined values. While the NOMA random access system can support simultaneous transmissions up to the number of target (receive) power levels, it complicates the access protocol design as each user not only has to optimize the transmission probability but also has to suitably choose the target receive power. By considering the fact that users may have different capability of choosing the target receive power due to their diverse locations in a cell, we first propose an online distributed channel access algorithm in a saturated traffic scenario where considered two target powers. Then, we explore a more complicated algorithm for NOMA random access systems with unsaturated traffic where support multiple target power levels. The proposed algorithms enable the users to adaptively choose the target receive power and control the transmission probability over time through observing channel outcomes such as idle, success and collision. Numerical results demonstrate that the proposed algorithms can optimize the system performance in terms of throughput and access fairness.