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

Transparent Spectrum Co-Access in Cognitive Radio Networks

The licensed wireless spectrum is currently under-utilized by as much as 85%. Cognitive radio networks have been proposed to employ dynamic spectrum access to share this under-utilized spectrum between licensed primary user transmissions and unlicensed secondary user transmissions. Current secondary user opportunistic spectrum access methods, however, remain limited in their ability to provide enough incentive to convince primary users to share the licensed spectrum, and they rely on primary user absence to guarantee secondary user performance. These challenges are addressed by developing a Dynamic Spectrum Co-Access Architecture (DSCA) that allows secondary user transmissions to co-access transparently and concurrently with primary user transmissions. This work exploits dirty paper coding to precode the cognitive radio channel utilizing the redundant information found in primary user relay networks. Subsequently, the secondary user is able to provide incentive to the primary user through increased SINR to encourage licensed spectrum sharing. Then a region of co-accessis formulated within which any secondary user can co-access the licensed channel transparently to the primary user. In addition, a Spectrum Co-Access Protocol (SCAP) is developed to provide secondary users with guaranteed channel capacity and while minimizing channel access times. The numerical results show that the SCAP protocol build on the DSCA architecture is able to reduce secondary user channel access times compared with opportunistic spectrum access and increased secondary user network throughput. Finally, we present a novel method for increasing the secondary user channel capacity through sequential dirty paper coding. By exploiting similar redundancy in secondary user multi-hop networks as in primary user relay networks, the secondary user channel capacity can be increased. As a result of our work in overlay spectrum sharing through secondary user channel precoding, we provide a compelling argument that the current trend towards opportunistic spectrum sharing needs to be reconsidered. This work asserts that limitations of opportunistic spectrum access to transparently provide primary users incentive and its detrimental effect on secondary user performance due to primary user activity are enough to motivate further study into utilizing channel precoding schemes. The success of cognitive radios and its adoption into federal regulator policy will rely on providing just this type of incentive

Transmitter Optimization in Multiuser Wireless Systems with Quality of Service Constraints

In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other transmitters. This scenario models a wireless network in which several wireless service providers share the spectrum to offer their services by using dynamic spectrum access and cognitive radio (CR) technologies. The primary objective of dynamic spectrum access in the CR approach is to enable use of the frequency band dynamically and opportunistically without creating harmful interference to licensed incumbent users. Specifically, CR users are envisioned to be able to provide high bandwidth and efficient utilization of the spectrum via dynamic spectrum access in heterogeneous networks. In this scenario, a distributed method is investigated for combined precoder and power adaptation of CR transmitters for dynamic spectrum sharing in cognitive radio systems. Finally, the effect of limited feedback for transmitter optimization is analyzed where precoder adaptation uses the quantized version of interference information or the predictive vector quantization for incremental updates. The performance of the transmitter adaptation algorithms is also studied in the context of fading channels

Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining

The deployment of underlay small base stations (SBSs) is expected to significantly boost the spectrum efficiency and the coverage of next-generation cellular networks. However, the coexistence of SBSs underlaid to an existing macro-cellular network faces important challenges, notably in terms of spectrum sharing and interference management. In this paper, we propose a novel game-theoretic model that enables the SBSs to optimize their transmission rates by making decisions on the resource occupation jointly in the frequency and spatial domains. This procedure, known as interference draining, is performed among cooperative SBSs and allows to drastically reduce the interference experienced by both macro- and small cell users. At the macrocell side, we consider a modified water-filling policy for the power allocation that allows each macrocell user (MUE) to focus the transmissions on the degrees of freedom over which the MUE experiences the best channel and interference conditions. This approach not only represents an effective way to decrease the received interference at the MUEs but also grants the SBSs tier additional transmission opportunities and allows for a more agile interference management. Simulation results show that the proposed approach yields significant gains at both macrocell and small cell tiers, in terms of average achievable rate per user, reaching up to 37%, relative to the non-cooperative case, for a network with 150 MUEs and 200 SBSs

Performance evaluation of cross-layer energy-efficient transmit antenna selection for spatial multiplexing systems

Abstract Multiple-input multiple-output (MIMO) and cognitive radio (CR) are key techniques for present and future high-speed wireless technologies. On the other hand, there are rising energy costs and greenhouse emissions associated with the provision of high-speed wireless communications. Consequently, the design of high-speed energy efficient systems is paramount for next-generation wireless systems. This thesis studies energy-efficient antenna selection for spatial multiplexing multiple-antenna systems from a cross-layer perspective, contrary to the norm, where physical-layer energy efficiency metrics are optimized. The enhanced system performance achieved by cross-layer designs in wireless networks motivates this research. The aim of the thesis is to propose and analyze novel cross-layer energy-efficient transmit antenna selection schemes that enhance energy efficiency and system performance - with regard to throughput, transmission latency, packet error rate and receiver buffer requirements. Firstly, this thesis derives the analytical expression for data link throughput for point-to-point spatial multiplexing multiple-antenna systems - which include MIMO and underlay CR MIMO systems - equipped with linear receivers with N-process stop-and-wait (N-SAW) as the automatic repeat request (ARQ) protocol. The performance of cross-layer transmit antenna selection, which maximizes the derived throughput metric, is then analyzed. The impact of packet size, number of SAW processes and the stalling of packets inside the receiver reordering buffer is considered in the investigation. The results show that the cross-layer approach, which takes into account system characteristics at both the data link and physical layers, has superior performance in comparison with the conventional physical-layer approach, which optimizes capacity. Secondly, this thesis proposes a cross-layer energy efficiency metric, based on the derived system throughput. Energy-efficient transmit antenna selection for spatial multiplexing MIMO systems, which maximizes the proposed cross-layer energy efficiency metric, by jointly optimizing the transmit antenna subset and transmit power, subject to spectral efficiency and transmit power constraints, is then introduced and analyzed. Additionally, adaptive modulation is incorporated into the proposed cross-layer scheme to enhance system performance. Cross-layer energyefficient transmit antenna selection for underlay CR MIMO systems, where interference constraints now come into play, is then considered. Lastly, this thesis develops novel reduced complexity versions of the proposed cross-layer energyefficient transmit antenna selection schemes - along with detailed complexity analysis - which shows that the proposed cross-layer approach attains significant energy efficiency and performance gains at affordable computational complexity