Baris Ozgul

Iris: an architecture for cognitive radio networking testbeds

Iris is a software architecture for building highly reconfigurable radio networks. It has formed the basis for a wide range of dynamic spectrum access and cognitive radio demonstration systems presented at a number of international conferences between 2007 and 2010. These systems have been developed using heterogeneous processing platforms including general-purpose processors, field-programmable gate arrays and the Cell Broadband Engine. Focusing on runtime reconfiguration, Iris offers support for all layers of the network stack and provides a platform for the development of not only reconfigurable point-to-point radio links but complete networks of cognitive radios. This article provides an overview of Iris, presenting the unique features of the architecture and illustrating how it can be used to develop a cognitive radio testbed.

Development Framework for Implementing FPGA-Based Cognitive Network Nodes

This paper identifies important features a cognitive radio framework should provide, namely a virtual architecture for hardware abstraction, an adaptive run-time system for managing cognition, and high level design tools for cognitive radio development. We evaluate a range of existing frameworks with respect to these, and propose a novel FPGA-based framework that provides all these features. By abstracting away the details of hardware reconfiguration, radio designers can implement FPGA-based cognitive nodes much as they would do for a software implementation. We apply the proposed framework to the design and implementation of a receiver node that works in two modes: discovery, where it uses spectrum sensing to find a radio transmission, and communication, in which it receives and demodulates the said transmission. We show how the whole design process does not require any hardware experience on behalf of the radio designer.

Complexity of Spectrum Activity and Benefits of Reinforcement Learning for Dynamic Channel Selection

We explore the question of when learning improves the performance of opportunistic dynamic channel selection by characterizing the primary user (PU) activity using the concept of Lempel-Ziv complexity. We evaluate the effectiveness of a reinforcement learning algorithm by testing it with real spectrum occupancy data collected in the GSM, ISM, and DECT bands. Our results show that learning performance is highly correlated with the level of PU activity and the amount of structure in the use of spectrum. For low levels of PU activity and/or high complexity in its utilization of channels, reinforcement learning performs no better than simple random channel selection. We suggest that Lempel-Ziv complexity might be one of the features considered by a cognitive radio when deciding which channels to opportunistically explore.

Wireless access with blind collision-multiplicity detection and retransmission diversity for quasi-static channels

Wireless multiple-access protocols using retransmission diversity resolve packet collisions through source separation techniques. Retransmissions are applied to achieve the necessary diversity level to determine the collision multiplicity blindly, whose proper detection is essential for good resolution performance. The so-called network-assisted diversity multiple access (NDMA) employs the rank test (RT) method for blind multiplicity detection, but static channel parameters throughout the retransmissions and the tight control of the transmitter phase are required. In this paper, a superior blind collision multiplicity-detection technique is introduced by combining the minimum description length criterion and a variation of the RT method. Collision resolution is accomplished through independent component analysis (ICA). Unlike blind NDMA,the new protocol, named ICA-NDMA, works in quasi-static fading channels, and does not need any phase control. Extensive performance analyses corroborate the performance advantages offered by ICA-NDMA.

Dynamic Block-Edge Masks (BEMs) for Dynamic Spectrum Emission Masks (SEMs)

This paper explores the evolving role of transmitter spectrum masks in the emerging paradigm of service and technology neutral spectrum planning. We advocate the use of more dynamic approaches to spectrum mask generation and design. Furthermore, we advocate a role for such masks in the implementation of dynamic spectrum access networks. In this paper we distinguish between the block-edge mask (BEM) and the spectrum emission mask (SEM). A block-edge mask specifies permitted power levels over the block of spectrum of interest and its neighbouring blocks. The spectrum emission mask on the other hand describes the actual emission profile of a device. We show how advancements in technologies, especially in the area of cognitive radio and reconfigurable networks, make the notion of dynamic SEMs a reality and we argue that a more dynamic approach to BEMs opens the way for enabling technology and service neutrality in spectrum management. We present five different possible interpretations for the dynamic BEM. While recognising that the dynamic BEM will prove challenging on both a technological and regulatory front we turn to the \emph{Wireless Access Policy for Electronic Communications Services} (WAPECS) framework as a solid starting point.

OFDM Pulse-Shaped Waveforms for Dynamic Spectrum Access Networks

In dynamic spectrum access networks (DySPANs), users share access to available spectrum while minimizing the likelihood of harmful interference. In this demonstration we present a dynamic spectrum access network which employs a reconfigurable orthogonal frequency-division multiplexing (OFDM) based waveform. In order to avoid the creation of harmful interference, the out-of-band (OOB) emissions of the waveform are dynamically tailored to the properties of spectrum neighbours through the use of OFDM pulse shaping. The demonstration network is built upon the highly reconfigurable Iris 2.0 software radio platform and illustrates the capabilities of this platform as well as the utility of OFDM pulse shaping in the context of dynamic spectrum access networks.

Bandwidth-Adaptive Waveforms for Dynamic Spectrum Access Networks

This paper presents a novel solution to the challenge of waveform bandwidth estimation in DySPAN systems using intentionally embedded cyclostationary signatures. Dynamic spectrum access networks (DySPANs) achieve high levels of spectrum use efficiency by exploiting spectrum white spaces, radio frequencies which are unused at given times and places. These white spaces have bandwidths which may not be known in advance and so, in order to fully exploit them, a DySPAN system must employ bandwidth-adaptive waveforms. It has been shown that multi-carrier transmission schemes can be leveraged to generate waveforms of flexible bandwidth. However, robust bandwidth estimation techniques are required for receiving nodes to successfully detect these signals and establish communication links. This paper makes three key contributions. Firstly, a novel technique for the generation of bandwidth-adaptive multi- carrier waveforms is proposed. Secondly, two approaches for parametrization of these bandwidth-adaptive waveforms in receiving DySPAN nodes are presented. The advantages and disadvantages of both bandwidth estimation techniques are examined and comparisons are drawn with approaches adopted for the IEEE 802.16 and draft IEEE 802.22 standards. Finally, the performance of both techniques under multipath fading conditions are examined using simulation results.

Spectrum and Energy Efficient Block Edge Mask-Compliant Waveforms for Dynamic Environments

This paper suggests that the regulatory tool known as the Block Edge Mask (BEM), which is used to define the technical conditions governing a spectrum license, can be used as an instrument to jointly drive spectrum and energy efficiency in a network. The paper explores this concept and goes on to show how networks can generate waveforms which comply with the energy limits of the BEM and at the same time make best use of the spectral resources available to them. The focus of the paper is on orthogonal frequency division multiplexing (OFDM) waveforms. The spectrum- and energy-efficient BEM-compliant waveforms are generated using a process that optimally combines symbol shaping and subcarrier-power loading to create a waveform that minimizes the difference between the transmitted wave and BEM. Practical considerations relating to peak-to-average-power-ratio (PAPR) reduction and time and frequency synchronization issues are explored to ensure the BEM-compliant waveforms can be transmitted with minimal changes to the transceiver. It is envisaged that these techniques will be used by transmitters that change their frequency of operation and in doing so need to shape their transmitted waveforms to comply with the different BEMs governing the use of the different spectrum blocks they wish to access.

Efficient sidelobe suppression for OFDM systems with peak-to-average power ratio reduction

This paper describes a practical method for sidelobe suppression for orthogonal frequency-division multiplexing (OFDM) signals. Most of the existing sidelobe suppression techniques are computationally expensive. The proposed technique is simpler in terms of computational complexity, and it enables high suppression capability. In addition, most of the related work deals with either sidelobe suppression or peak-to-average power ratio (PAPR) reduction which are mutually exclusive in some cases. However, the proposed technique is compatible with some PAPR reduction techniques. Simulation results show that the proposed technique can achieve significant sidelobe suppression. In addition, under adjacent channel interference constraints, the proposed algorithm outperforms the conventional OFDM transmissions in terms of bit-error rate (BER). Moreover, the proposed algorithm is implemented on a software defined radio and tested for practical and real-time transmissions.

Experiences from the Iris Testbed in Dynamic Spectrum Access and Cognitive Radio Experimentation

Abstract-The focus of this paper is an experimentation platform known as Iris that has a runtime reconfigurable software radio at its core. We have employed this platform to enable a wide variety of tests and experimentation in the fields of dynamic spectrum access and cognitive radio. The paper charts the progress of the Iris system since its inception as well as details of some of the experiments and trials conducted using this platform. We also discuss the challenges involved in the development and deployment of a software radio platform that supports runtime reconfigurability and provide recommendations for future improvements.