Joseph Mitola

Cognitive radio: making software radios more personal

Software radios are emerging as platforms for multiband multimode personal communications systems. Radio etiquette is the set of RF bands, air interfaces, protocols, and spatial and temporal patterns that moderate the use of the radio spectrum. Cognitive radio extends the software radio with radio-domain model-based reasoning about such etiquettes. Cognitive radio enhances the flexibility of personal services through a radio knowledge representation language. This language represents knowledge of radio etiquette, devices, software modules, propagation, networks, user needs, and application scenarios in a way that supports automated reasoning about the needs of the user. This empowers software radios to conduct expressive negotiations among peers about the use of radio spectrum across fluents of space, time, and user context. With RKRL, cognitive radio agents may actively manipulate the protocol stack to adapt known etiquettes to better satisfy the users needs. This transforms radio nodes from blind executors of predefined protocols to radio-domain-aware intelligent agents that search out ways to deliver the services the user wants even if that user does not know how to obtain them. Software radio provides an ideal platform for the realization of cognitive radio.

The software radio architecture

As communications technology continues its rapid transition from analog to digital, more functions of contemporary radio systems are implemented in software, leading toward the software radio. This article provides a tutorial review of software radio architectures and technology, highlighting benefits, pitfalls, and lessons learned. This includes a closer look at the canonical functional partitioning of channel coding into antenna, RF, IF, baseband, and bitstream segments. A more detailed look at the estimation of demand for critical resources is key. This leads to a discussion of affordable hardware configurations, the mapping of functions to component hardware, and related software tools. This article then concludes with a brief treatment of the economics and likely future directions of software radio technology. >

Cognitive radio for flexible mobile multimedia communications

Wireless multimedia applications require significant bandwidth, some of which will be provided by third-generation (3G) services. Even with substantial investment in 3G infrastructure, the radio spectrum allocated to 3G will be limited. Cognitive radio offers a mechanism for the flexible pooling of radio spectrum using a new class of protocols called formal radio etiquettes. This approach could expand the bandwidth available for conventional uses (e.g., police, fire and rescue) and extend the spatial coverage of 3G in a novel way. Cognitive radio is a particular extension of software radio that employs model-based reasoning about users, multimedia content, and communications context. This paper characterizes the potential contributions of cognitive radio to spectrum pooling and outlines an initial framework for formal radio-etiquette protocols.Wireless multimedia applications require significant bandwidth, some of which will be provided by third-generation (3G) services. even with substantial investment in 3G infrastructure, the radio spectrum allocated to 3G will be limited. Cognitive radio offers a mechanism for the flexible pooling of radio spectrum using a new class of protocols called formal radio etiquettes. This approach could expand the bandwidth available for conventional uses (e.g., police, fire and rescue) and extend the spatial coverage of 3G in a novel way. Cognitive radio is a particular extension of software radio that employs model-based reasoning about users, multimedia content, and communications context. This paper characterizes the potential contributions of cognitive radio to spectrum pooling and outlines an initial framework for formal radio-etiquette protocols.

Cognitive Radio Architecture Evolution

The radio research community has aggressively embraced cognitive radio for dynamic radio spectrum management to enhance spectrum usage, e.g., in ISM bands and as secondary users in unused TV bands, but the needs of the mobile wireless user have not been addressed as thoroughly on the question of high quality of information (QoI) as a function of place, time, and social setting (e.g. commuting, shopping, or in need of medical assistance). This paper considers the evolution of cognitive radio architecture (CRA) in the context of motivating use cases such as public safety and sentient spaces to characterize CRA with an interdisciplinary perspective where machine perception in visual, acoustic, speech, and natural language text domains provide cues to the automatic detection of stereotypical situations, enabling radio nodes to select from among radio bands and modes more intelligently and enabling cognitive wireless networks to deliver higher QoI within social and technical constraints, made more cost effective via embedded and distributed computational intelligence.

Software radio architecture: a mathematical perspective

As the software radio makes its transition from research to practice, it becomes increasingly important to establish provable properties of the software radio architecture on which product developers and service providers can base technology insertion decisions. Establishing provable properties requires a mathematical perspective on the software radio architecture. This paper contributes to that perspective by critically reviewing the fundamental concept of the software radio, using mathematical models to characterize this rapidly emerging technology in the context of similar technologies like programmable digital radios. The software radio delivers dynamically defined services through programmable processing capacity that has the mathematical structure of the Turing machine. The bounded recursive functions, a subset of the total recursive functions, are shown to be the largest class of Turing-computable functions for which software radios exhibit provable stability in plug-and-play scenarios. Understanding the topological properties of the software radio architecture promotes plug-and-play applications and cost-effective reuse. Analysis of these topological properties yields a layered distributed virtual machine reference model and a set of architecture design principles for the software radio. These criteria may be useful in defining interfaces among hardware, middleware, and higher level software components that are needed for cost-effective software reuse.

Cognitive Radio Architecture

This chapter develops five complementary perspectives of cognitive radio architecture (CRA), called CRA-I through CRA-V, each building on the previous in capability. Architecture is driven top-down by market needs and bottom-up by available, affordable technologies. Taking the top-down perspective requires some attention to the use cases that the functions are intended to realize. This chapter therefore reviews the substantial changes in use cases that drive cognitive wireless architecture. Often technical architectures of the kind accelerate the state of practice by catalyzing work across the industry on plug-and-play, teaming, and collaboration. The thought is that to propel wireless technology from limited spectrum awareness toward valuable user awareness, an architecture is needed. The CRA articulates the functions, components, and design rules of next-generation stand-alone and embedded wireless devices and networks.

Accelerating 5G QoE via public-private spectrum sharing

Fifth generation wireless systems (5G) must achieve high user Quality of Experience (QoE) in order to compete for market share. Each candidate 5G wireless radio frequency (RF) band offers advantages such as longer range or higher data rate than 2G, 3G, and 4G, but no single band or air interface standard by itself fully achieves ubiquitous levels of QoE for the complete range of wireless access devices. Spectrum clearing cannot keep pace with user demand, so public-private spectrum sharing is emerging as an affordable, near-term method of increasing radio access network (RAN) capacities for content delivery. This paper presents a fresh look at QoE; spectrum scarcity; public uses that underutilize candidate 5G radio frequency (RF) spectrum; and emerging public-private radio interference management frameworks that enable near-term spectrum sharing, with positive consequences for 5G price, performance, and total user QoE.

Distributed Consensus-Based Weight Design for Cooperative Spectrum Sensing

In this paper, we study the distributed spectrum sensing in cognitive radio networks. Existing distributed consensus-based fusion algorithms only ensure equal gain combining of local measurements, whose performance may be incomparable to various centralized soft combining schemes. Motivated by this fact, we consider practical channel conditions and link failures, and develop new weighted soft measurement combining without a centralized fusion center. Following the measurement by its energy detector, each secondary user exchanges its own measurement statistics with its local one-hop neighbors, and chooses the information exchanging rate according to the measurement channel condition, e.g., the signal-to-noise ratio (SNR). We rigorously prove the convergence of the new consensus algorithm, and show all secondary users hold the same global decision statistics from the weighted soft measurement combining throughout the network. We also provide distributed optimal weight design under uncorrelated measurement channels. The convergence rate of the consensus iteration is given under the assumption that each communication link has an independent probability to fail, and the upper bound of the iteration number of the ε-convergence is explicitly given as a function of system parameters. Simulation results show significant improvement of the sensing performance compared to existing consensus-based approaches, and the performance of the distributed weighted design is comparable to the centralized weighted combining scheme.

Guest Editorial - Cognitive Radio: Theory and Application

The 17 papers in this special issue focus on the theory and applications of cognitive radio.

Distributed Cooperative Spectrum Sensing Based on Weighted Average Consensus

In this paper, we study the distributed spectrum sensing in cognitive radio networks. Using weighted average consensus algorithm, we develop a weighted soft measurement combining scheme without the centralized fusion center. After the measurement by the energy detector, each secondary user (SU) exchanges their own measurement statistics with its local neighbors, and chooses the information exchanging rate according to the estimated average signal-to-noise ratio (SNR). We prove the convergence of the consensus iteration, and each SU will hold the global decision statistics from the weighted soft measurement combining throughout the network. The proposed scheme is robust with respect to temporary communication link failures. Simulation results show our method has a better performance than the existing average consensus-based approach.