Mathematical optimization techniques for resource allocation and spatial multiplexing in spectrum sharing networks

Due to introduction of smart phones with data intensive multimedia and interactive applications and exponential growth of wireless devices, there is a shortage for useful radio spectrum. Even though the spectrum has become crowded, many spectrum occupancy measurements indicate that most of the allocated spectrum is underutilised. Hence radically new approaches in terms of allocation of wireless resources are required for better utilization of radio spectrum. This has motivated the concept of opportunistic spectrum sharing or the so-called cognitive radio technology that has great potential to improve spectrum utilization. The cognitive radio technology allows an opportunistic user namely the secondary user to access the spectrum of the licensed user (known as primary user) provided that the secondary transmission does not harmfully affect the primary user. This is possible with the introduction of advanced resource allocation techniques together with the use of wireless relays and spatial diversity techniques. In this thesis, various mathematical optimization techniques have been developed for the efficient use of radio spectrum within the context of spectrum sharing networks. In particular, optimal power allocation techniques and centralised and distributed beamforming techniques have been developed. Initially, an optimization technique for subcarrier and power allocation has been proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) based secondary wireless network in the presence of multiple primary users. The solution is based on integer linear programming with multiple interference leakage and transmission power constraints. In order to enhance the spectrum efficiency further, the work has been extended to allow multiple secondary users to occupy the same frequency band under a multiple-input and multiple-output (MIMO) framework. A sum rate maximization technique based on uplink-downlink duality and dirty paper coding has been developed for the MIMO based OFDMA network. The work has also been extended to handle fading scenarios based on maximization of ergodic capacity. The optimization techniques for MIMO network has been extended to a spectrum sharing network with relays. This has the advantage of extending the coverage of the secondary network and assisting the primary network in return for the use of the primary spectrum. Finally, instead of considering interference mitigation, the recently emerged concept of interference alignment has been used for the resource allocation in spectrum sharing networks. The performances of all these new algorithms have been demonstrated using MATLAB based simulation studies

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

Space Alignment Based on Regularized Inversion Precoding in Cognitive Transmission

For a two-tier Multiple-Input Multiple-Output (MIMO) cognitive network with common receiver, the precoding matrix has a compact relationship with the capacity performance in the unlicensed secondary system. To increase the capacity of secondary system, an improved precoder based on the idea of regularized inversion for secondary transmitter is proposed. An iterative space alignment algorithm is also presented to ensure the Quality of Service (QoS) for primary system. The simulations reveal that, on the premise of achieving QoS for primary system, our proposed algorithm can get larger capacity in secondary system at low Signal-to-Noise Ratio (SNR), which proves the effectiveness of the algorithm

A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment

The application of multiple-input multiple-output (MIMO) techniques to non-orthogonal multiple access (NOMA) systems is important to enhance the performance gains of NOMA. In this paper, a novel MIMO-NOMA framework for downlink and uplink transmission is proposed by applying the concept of signal alignment. By using stochastic geometry, closed-form analytical results are developed to facilitate the performance evaluation of the proposed framework for randomly deployed users and interferers. The impact of different power allocation strategies, such as fixed power allocation and cognitive radio inspired power allocation, on the performance of MIMO-NOMA is also investigated. Computer simulation results are provided to demonstrate the performance of the proposed framework and the accuracy of the developed analytical results

Channels Reallocation In Cognitive Radio Networks Based On DNA Sequence Alignment

Nowadays, It has been shown that spectrum scarcity increased due to tremendous growth of new players in wireless base system by the evolution of the radio communication. Resent survey found that there are many areas of the radio spectrum that are occupied by authorized user/primary user (PU), which are not fully utilized. Cognitive radios (CR) prove to next generation wireless communication system that proposed as a way to reuse this under-utilised spectrum in an opportunistic and non-interfering basis. A CR is a self-directed entity in a wireless communications environment that senses its environment, tracks changes, and reacts upon its findings and frequently exchanges information with the networks for secondary user (SU). However, CR facing collision problem with tracks changes i.e. reallocating of other empty channels for SU while PU arrives. In this paper, channels reallocation technique based on DNA sequence alignment algorithm for CR networks has been proposed.Comment: 12 page

A Distributed Approach to Interference Alignment in OFDM-based Two-tiered Networks

In this contribution, we consider a two-tiered network and focus on the coexistence between the two tiers at physical layer. We target our efforts on a long term evolution advanced (LTE-A) orthogonal frequency division multiple access (OFDMA) macro-cell sharing the spectrum with a randomly deployed second tier of small-cells. In such networks, high levels of co-channel interference between the macro and small base stations (MBS/SBS) may largely limit the potential spectral efficiency gains provided by the frequency reuse 1. To address this issue, we propose a novel cognitive interference alignment based scheme to protect the macro-cell from the cross-tier interference, while mitigating the co-tier interference in the second tier. Remarkably, only local channel state information (CSI) and autonomous operations are required in the second tier, resulting in a completely self-organizing approach for the SBSs. The optimal precoder that maximizes the spectral efficiency of the link between each SBS and its served user equipment is found by means of a distributed one-shot strategy. Numerical findings reveal non-negligible spectral efficiency enhancements with respect to traditional time division multiple access approaches at any signal to noise (SNR) regime. Additionally, the proposed technique exhibits significant robustness to channel estimation errors, achieving remarkable results for the imperfect CSI case and yielding consistent performance enhancements to the network.Comment: 15 pages, 10 figures, accepted and to appear in IEEE Transactions on Vehicular Technology Special Section: Self-Organizing Radio Networks, 2013. Authors' final version. Copyright transferred to IEE