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

Robust improper signaling for two-user SISO interference channels

It has been shown that improper Gaussian signaling (IGS) can improve the performance of wireless interference-limited systems when perfect channel-state information (CSI) is available. In this paper, we investigate the robustness of IGS against imperfect CSI on the transmitter side in a two-user single-input single-output (SISO) interference channel (IC) as well as in a SISO Z-IC, when interference is treated as noise. We assume that the true channel coefficients belong to a known region around the channel estimates, which we call the uncertainty region. Following a worst-case robustness approach, we study the rate-region boundary of the IC for the worst channel in the uncertainty region. For the two-user IC, we derive a robust design in closed form, which is independent of the phase of the channels by allowing only one of the users to transmit IGS. For the Z-IC, we provide a closed-form design for the transmission parameters by considering an enlarged uncertainty region and allowing both users to employ IGS. In both cases, the IGS-based designs are ensured to perform no worse than proper Gaussian signaling. Furthermore, we show, through numerical examples, that the proposed robust designs significantly outperform non-robust solutions.The work of M. Soleymani, C. Lameiro and P. J. Schreier was supported by the German Research Foundation (DFG) under grants LA 4107/1-1 and SCHR 1384/8-1. The work of I. Santamaria was supported by MINECO of Spain and AEI/FEDER funds of the E.U., under grant TEC2016-75067-C4-4-R (CARMEN)

Interference Aware Cognitive Femtocell Networks

Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks. Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision. This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference