Linear interference alignment in cognitive radio networks

Abstract

Multi-input multi output (MIMO) systems are still developing via substantial research effort in the literature and leading telecommunication industry. MIMO communications that is a solution as countering fading and deep fade effect in wireless communication, presents spatial diversity of the system and increases data rates. Yet, the effective operation of MIMO systems depends on the design of the pre-coding and post-coding matrices. Cognitive radio networks, which have been proposed for a long time in the literature, are still being developed. The communication of two different types of users is achieved on the principle that they are based on the use of different kinds of techniques as a solution to the spectrum scarcity. Primary users are allocated as licensed users, besides secondary users are considered as unlicensed users in cognitive radio networks. Overlay, underlay and interweave techniques are among the outstanding techniques in the literature. It is essential to minimize interference components that occur between the primary users and the secondary users so that these techniques can work effectively. Interference alignment (IA) is a remedy for eliminating interference components due to the interference channel in MIMO networks. There are many variants for IA in the literature and linear interference alignment technique is the most frequently used due to its applicable approach. In the IA method using the MIMO network structure, the interference components are aligned in a specific direction by using the precoding and interference suppression matrices. However, the destruction of these interference components is accompanied by operative signal processing implementation. Additionally, IA technique has also known harmonious structure for CR networks. In this thesis, the interference alignment performance of a MIMO CR network is examined in the presence of multiple secondary users. In the proposed architecture, it is assumed that linear IA is used at the primary system to alleviate the interference between primary and secondary networks. Although linear IA can surpass the interference in CR considerably, interference leakages may occur due to fast fading channel. Herein, we derive the closed-form outage probability expression considering the interference leakage occurred in the primary system. The results which are validated with Monte-Carlo simulations show that interference leakages can deteriorate both system performance and diversity gains considerably. Furthermore, precoder and interference suppression matrix design is covered using the IA technique with MIMO zero-forcing receiver structure. Precoder and interference suppression matrix is designed considering the presence of a single primary user and two secondary users in the wireless environment. Sum rate performances and bit error rate performances are presented for both primary users and secondary users with respect to the number of antennas and distance.