MIMO Spectrum Sensing

The increasing demand of wireless applications has put a lot of limitations on the use of available radio spectrum is limited and precious resource. Many survey of spectrum utilization shows that entire spectrum is not used at all the times, so many of the radio spectrum is underutilized. Some of the frequency bands in the spectrum are unoccupied, some of the frequency bands less occupied and few bands are over utilized. Cognitive radio system is a technique which overcomes that spectrum underutilization. Cognitive radio is a technique where secondary user looks for a free band to use when primary user is not in use of its licensed band. A function of cognitive radio is called Spectrum sensing which enables to search for the free bands and it helps to detect the spectrum hole (frequency band which is free enough to be used) which can be utilized by secondary user with high spectral resolution capability. The idea of simulation and analysis of Cognitive Radio System to reuse unused spectrum to increase the total system capacity was brought in this paper and this work digs into the practical implementation of a Cognitive radio system. MATLAB R2007b (version7.5) has been used to test the performance of Cognitive radio dynamically

Cognitive radio is an enabling technology that allows opportunistic users to reuse licensed spectrum in order to overcome the artificial spectrum scarcity. In cognitive radio networks, opportunistic users collaboratively perform spectrum sensing to detect the presence of incumbent users. Collaborative Spectrum Sensing (CSS) performance suffers due to the presence of malicious users. We propose a robust malicious user detection algorithm which exploits inherent statistical moments of the sensing observations from collaborating users to identify malicious users among them. In this way, CSS performance is improved by detecting and marginalizing the effects of malicious users.

A scenario is presented in spectrum sensing for Cognitive Radio Networks based on energy detectors. Results are presented for the performance of the energy detector based on Welch periodogram. The effect of the number of signal samples and the time domain window function are demonstrated for low Signal-to-Noise Ratio values. Furthermore, the detector performance is linked to a general probabilistic scheme for sensing algorithms. Important system issues such as receiver feedback and cooperative spectrum sensing are included in this framework. Parametric computations of the probability of correct decision are presented to show the detrimental effect of the hidden node problem in a simple collaborative spectrum sensing scheme.

Multi-user MIMO offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned, with roughly equal numbers of service antennas and terminals and frequency-division duplex operation, is not a scalable technology. Massive MIMO (also known as large-scale antenna systems, very large MIMO, hyper MIMO, full-dimension MIMO, and ARGOS) makes a clean break with current practice through the use of a large excess of service antennas over active terminals and time-division duplex operation.

Incorporating full duplex operation in Multiple Input Multiple Output (MIMO) systems provides the potential of boosting throughput performance. However, the hardware complexity of the analog self-interference canceller in emerging full duplex MIMO designs mostly scales with the number of transmit and receive antennas, thus exploiting the benefits of analog cancellation becomes impractical for full duplex MIMO transceivers, even for moderate number of antennas. In this paper, we present two novel architectures for the analog canceller comprising of reduced number of cancellation elements, compared to the state of the art, and simple multiplexers for efficient signal routing among the transmit and receive radio frequency chains. One architecture is based on analog taps (tap refers to a line of fixed delay, variable phase shifter, and attenuator) and the other on AUXiliary (AUX) Transmitters (TXs) that locally generate the cancellation signal. In contrast to the available analog cancellation architectures, the values for each tap or each AUX TX and the configuration of the multiplexers are jointly designed with the digital transmit and receive beamforming filters according to certain performance objectives. Focusing on a narrowband flat fading channel model as an example, we present a general optimization framework for the joint design of analog self-interference cancellation and digital beamforming. We also detail the sum rate optimization objective together with its derived solution for the latter architectural components. Representative computer simulation results demonstrate the superiority both in terms of hardware complexity and achievable performance of the proposed low complexity full duplex MIMO schemes over the lately available ones.

Multiuser Multiple-Input Multiple-Output (MIMO) offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multiuser MIMO, as originally envisioned with roughly equal numbers of service-antennas and terminals and frequency division duplex operation, is not a scalable technology. Massive MIMO (also known as "Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension MIMO" and "ARGOS") makes a clean break with current practice through the use of a large excess of service-antennas over active terminals and time division duplex operation. Extra antennas help by focusing energy into ever-smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include the extensive use of inexpensive low-power components, reduced latency, simplification of the media access control (MAC) layer, and robustness to intentional jamming. The anticipated throughput depend on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly-joined terminals, the exploitation of extra degrees of freedom provided by the excess of service-antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This paper presents an overview of the massive MIMO concept and of contemporary research on the topic. 1 Background: MultiUser MIMO Maturing MIMO, Multiple-Input Multiple Output, technology relies on multiple antennas to simultaneously transmit multiple streams of data in wireless communication systems. When MIMO is used to communicate with several terminals at the same time, we speak of multiuser MIMO. Here, we just say MU-MIMO for short.

Multiple Input and Multiple Output (MIMO) system have the potential to achieve very high capacities, depending on the propagation environment. A MIMO system provides multiple independent transmission channels, thus, leading (under certain conditions) to a channel capacity that increases linearly with the number of antenna elements. It is well known that the employment of multiple antennas at both the transmitter and receiver increases the overall system capacity. The objective of this paper is to simulate the Nakagami -m fading model using MATLAB and to analysis channel capacity. The program, when called in the MATLAB workspace, will generate random variables (RVs) that follow the Nakagami -m distribution. The generated random variable processes, includes the PDF and Nakagami PDF plots were drawn and which is suggested to apply this method to generate the Nakagami -m fading channel with MIMO Channel matrices by applying waterfilling algorithm using the same technique. For maximizing the capacity of MIMO systems, waterfilling algorithm is implemented by singular value decomposition (SVD) of received signal.

Razvoj savremenih aplikacija iziskuje potrebu za što većim protokom informacija. Postaje jasno da trenutni frekventni spektar ne može pratiti razvoj i zahteve novih uređaja, ali i sami načini i tehnike dodeljivanja spektra su dovele do njegovog neefikasnog iskorišćenja. Kao odgovor na sve ove probleme, potrebnoje predstaviti inovativne tehnike koje mogu pružiti efikasnije metode dodeljivanja i raspodele frekvencijskog opsega u slučajevima kada se on ne koristi.

 Abstract-Pilot contamination is the major factor to limit the performance of massive MIMO systemsdue to degraded channel estimation. In this paper, we have tried to provide an extensive survey on pilot contamination, and identify all possible sources causing it. We mostly cover the theoretical aspect and review the established theories that have analyzed the effect of pilot contamination on the performance of massive MIMO systems. We studied about a pilot pattern design where zero pilot symbols are inserted into the pilot sequence to reduce the pilot contamination impact on uplink channel estimate and bit error rate performance. We evaluate the achievable rate in forward link with maximum-ratio and zero-forcing precoding at the BS. We analyze spectral efficiency when employing maximum ratio transmission or zero forcing precoding at the base station. We investigate the performance of simple least-squares channel estimator with the higher-complexity minimum mean square error estimator. A brief analysis of mitigation techniques based on existing long term evolution (LTE) measurements-open loop power control (OLPC) and pilot sequence reuse schemes, that avoid PC within a group of cells has been done. Finally, some open problems are highlighted and concluded with broader perspective and a look at future trends in pilot contamination inmassive MIMO systems. Index Terms-About four key words or phrases in alphabetical order, separated by commas. I. INTRODUCTION Over the past decade multi input, multiple-output (MIMO) has emerged as one of the prime technologies for achieving high data rates and spectral efficiency in wireless communication systems. Recently, it was experimented that the use of very large antenna arrays, typically of the order of few thousands, at the base station (BS) can potentially provide huge gains in system throughput, energy efficiency, security and robustness of wireless communication systems. Use of massive MIMO is a promising technology that is expected to deliver high data rates as well as enhanced link reliability, coverage, and energy efficiency; and has therefore attracted lots of research interests. Hand in hand with the advantages, there are entirely new research challenges that need to be tackled for massive MIMO. Due to the dense network deployment and limited orthogonal pilot sequences, multiple neighbor cells may use the same pilot sequence, and the pilot positions in pilot patternsof the multiple neighbor cells may overlap, which will directly affect the performance of the channel estimation. This is called pilot contamination.

The electromagnetic spectrum is a natural scarce resource. Radio transmission involves the use of part of the electromagnetic spectrum. Use of spectrum is regulated by government agencies such as Federal Communications Commission (FCC) in the United States. Cognitive radio provides solution to the spectrum scarcity problem. Spectrum sensing for CR is an extremely well researched topic. The biggest challenge related to spectrum sensing is in developing sensing techniques which are able to detect very weak primary user signals while being sufficiently fast and low cost to implement. The various spectrum sensing techniques are: classical spectrum sensing, cooperative spectrum sensing, multiple antenna sensing and MIMO spectrum sensing. This paper provides brief overview of all existing spectrum sensing techniques and comparison is evaluated on the basis of their capacity of detecting the presence of primary users. Among these entire spectrum sensing techniques MIMO spectrum sensing is most efficient as it provides higher capacity, low value of probability of false alarm  and high value of probability of detection

Multiuser Multiple-Input Multiple-Output (MIMO) offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multiuser MIMO, as originally envisioned with roughly equal numbers of service-antennas and terminals and frequency division duplex operation, is not a scalable technology. Massive MIMO (also known as "Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension MIMO" and "ARGOS") makes a clean break with current practice through the use of a large excess of service-antennas over active terminals and time division duplex operation. Extra antennas help by focusing energy into ever-smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include the extensive use of inexpensive low-power components, reduced latency, simplification of the media access control (MAC) layer, and robustness to intentional jamming. The anticipated throughput depend on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly-joined terminals, the exploitation of extra degrees of freedom provided by the excess of service-antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This paper presents an overview of the massive MIMO concept and of contemporary research on the topic. 1 Background: MultiUser MIMO Maturing MIMO, Multiple-Input Multiple Output, technology relies on multiple antennas to simultaneously transmit multiple streams of data in wireless communication systems. When MIMO is used to communicate with several terminals at the same time, we speak of multiuser MIMO. Here, we just say MU-MIMO for short.

This paper asks is whether (i) 3rd generation wireless services, as embodied in the planned and soon to be offered services emerging first in Asia and Europe, or (ii) the unlicensed wireless services such as 802.11 or wi-fi but also including more advanced wideband and ultrawideband (UWB) services which are being experimented with primarily in North America, offer more compelling visions for advanced wireless services. we conclude that secondary spectrum markets are important for the viability of the 3G industry, and not only ...

Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fundamental problem in cognitive radio. Since the statistical covariances of the received signal and noise are usually different, they can be used to differentiate the case where the primary user's signal is present from the case where there is only noise. In this paper, spectrum-sensing algorithms are proposed based on the sample covariance matrix calculated from a limited number of received signal samples. Two test statistics are then extracted from the sample covariance matrix. A decision on the signal presence is made by comparing the two test statistics. Theoretical analysis for the proposed algorithms is given. Detection probability and the associated threshold are found based on the statistical theory. The methods do not need any information about the signal, channel, and noise power a priori. In addition, no synchronization is needed. Simulations based on narrow-band signals, captured digital television (DTV) signals, and multiple antenna signals are presented to verify the methods.

Multiple Input and Multiple Output (MIMO) system have
the potential to achieve very high capacities, depending on
the propagation environment. A MIMO system provides
multiple independent transmission channels, thus, leading
(under certain conditions) to a channel capacity that
increases linearly with the number of antenna elements. It is
well known that the employment of multiple antennas at
both the transmitter and receiver increases the overall system
capacity. The objective of this paper is to simulate the
Nakagami – m fading model using MATLAB and to analysis
channel capacity. The program, when called in the
MATLAB workspace, will generate random variables (RVs)
that follow the Nakagami – m distribution. The generated
random variable processes, includes the PDF and Nakagami
PDF plots were drawn and which is suggested to apply this
method to generate the Nakagami – m fading channel with
MIMO Channel matrices by applying waterfilling algorithm
using the same technique. For maximizing the capacity of
MIMO systems, waterfilling algorithm is implemented by
singular value decomposition (SVD) of received signal.

This paper addresses the maximizing network lifetime problem in wireless sensor networks (WSNs) taking into account the total Symbol Error rate (SER) at destination. Therefore, efficient power management is needed for extend network lifetime. Our approach consists to provide the optimal transmission power using the orthogonal multiple access channels between each sensor. In order to deeply study the
properties of our approach, firstly, the simple case is considered; the information sensed by the source node passes by a single relay before reaching the destination node. Secondly, global case is studied; the information passes by several relays. We consider, in the previous both cases, that the batteries are non rechargeable.
Thirdly, we spread our work the case where the batteries are rechargeable with unlimited storage capacity. In all three cases, we suppose that Maximum Ratio Combining (MRC) is used as a detector, and Amplify and Forward (AF) as a relaying strategy. Simulation results show the viability of our approach which the network lifetime is extended of more than 70.72%when the batteries are non
rechargeable and 100.51% when the batteries are rechargeable in comparison with other traditional
method.

Reservations represent an alternative implementation of secondary markets for spectrum with respect to spot selling through auctions. In a previous paper we have shown that reservation mechanisms may be profitable to mobile operators, be they virtual or endowed with a network, assuming the reservation price as a parameter. Pricing reservations, when the owner of spectrum usage rights applies overbooking and pays a penalty if the reservation is not honoured, is still an open issue. Here we propose an iterative algorithm, based on tools derived from the field of financial markets, to set prices for reservations under overbooking. We analyse the sensitivity of the reservation price to a number of parameters (the purchase price, the expiration time of reservation, the overbooking probability, and the penalty value), and show that the reservation prices decay fast with the overbooking probability, and increase with the penalty value, but short expiration times may make the penalty ineffective.

Mobile Virtual Network Operators (MVNO) operate without owning spectrum usage rights, by leasing spectrum from Mobile Network Operators owning a license. Spectrum leasing may occur through a reservation process that assigns the MVNO the right, but not the obligation, to lease spectrum at a later time. Reservation contracts may be signed with strict guarantees, that provide MVNOs with the certainty of obtaining the needed spectrum, or soft guarantees, which allow the MNO to adopt an overbooking policy and refusing to lease the spectrum, compensating the refused MVNO through the payment of a penalty. In this paper the two kinds of reservation contracts are compared from the viewpoint of the MVNO, by considering the profitability of the two alternatives. The cash flows associated to the two kinds of reservation contracts are determined and employed to compare the alternatives. The probability of overbooking and the expiry time of reservations appear as the major decision factors, while the penalty value has a negligible influence. It is shown that the reservation contract with soft guarantees is to be prefereed for larger values of the expiry time and for the lower values of the overbooking probability.

Cognitive radio allows spectrum bands which
is a limited supply to be used efficiently and actively.
Spectrum sensing which is an important function of cognitive
radio detects whether there are licensed users in the
environment and the unused spectrum band by scanning all
spectrum bands continuously. In this study, the effects of the
number of multiple antennas used at the receiver and
transmitter side, the mobile speed and the number of
multipath on energy based spectrum sensing performance in
MIMO systems improving spectral efficiency and data rate
significantly are examined. The facts that multiple antennas
and the number of multipath affects spectrum sensing
performance in the positive direction while the speed of the
mobile affects this performance in the negative direction
were obtained.

Powerful spectrum sensing schemes enable cognitive radios (CRs) to find transmission opportunities in spectral resources allocated exclusively to primary users. In this paper, the problem of maximizing the average throughput of a cognitive radio system through optimizing its spectrum sensing time is investigated, and a systematic neural network-based optimization approach is proposed which avoids challenges associated with the conventional analytical solutions. The proposed method exploits a novel learning and optimization cycle to enable an effective cooperation between two kinds of well-known artificial neural networks and finds the optimum value of the channel sensing time without any prior knowledge or assumption about the wireless environment. The structure and algorithm of the proposed sensing time optimization scheme are discussed in detail, and a set of illustrative numerical results is presented to validate its performance.

In this paper, we consider the optimization of wireless capacity-limited backhaul links in future heterogeneous networks (HetNets). We assume that the HetNet is formed with one macro-cell base station (MBS), which is associated with multiple small-cell base stations (SBSs). It is also assumed both the MBS and the SBSs are equipped with massive arrays, while all mobiles users (macro-cell and small-cell users) have single antenna. For the backhaul links, we propose to use a capacity-aware beamforming scheme at the SBSs and MRC at the MBS. Using particle swarm optimization (PSO), each SBS seeks the optimal transmit weight vectors that maximize the backhaul uplink capacity and the access uplinks signal-to-interference plus noise ratio (SINR). The performance evaluation in terms of the symbol error rate (SER) and the ergodic system capacity shows that the proposed capacity-aware backhaul link scheme achieves similar or better performance than traditional wireless backhaul links and requi...

In this paper, we consider the optimization of wireless capacity-limited backhaul links in future heterogeneous networks (HetNets). We assume that the HetNet is formed with one macro-cell base station (MBS), which is associated with multiple small-cell base stations (SBSs). It is also assumed both the MBS and the SBSs are equipped with massive arrays, while all mobiles users (macro-cell and small-cell users) have single antenna. For the backhaul links, we propose to use a capacity-aware beamforming scheme at the SBSs and MRC at the MBS. Using particle swarm optimization (PSO), each SBS seeks the optimal transmit weight vectors that maximize the backhaul uplink capacity and the access uplinks signal-to-interference plus noise ratio (SINR). The performance evaluation in terms of the symbol error rate (SER) and the ergodic system capacity shows that the proposed capacity-aware backhaul link scheme achieves similar or better performance than traditional wireless backhaul links and requires considerably less computational complexity.

Spectrum sharing has been recently proposed as a promising paradigm to improve the efficiency of resource usage in next generation mobile networks. In particular, non orthogonal spectrum sharing allows the operators to re-use the available frequencies at the cost of higher interference at the receivers. In this paper, we mathematically analyze the performance of this technique and how it is statistically related to the channel coefficients. Moreover, we compare different kinds of schedulers that exploit various aspects of non orthogonal spectrum sharing. Finally, the resulting system performance is assessed, first through an exact statistical framework and then by simulating the schedulers in an LTE scenario with the opensource network simulator ns3.

Setting a powerful spectrum sensing and access policy increases the throughput of cognitive radio networks (CRNs). In this paper, the problem of maximizing the average throughput of a CRN through setting proper sensing sequences is investigated. In addition, a systematic neural network-based optimization approach is developed which avoids challenges associated with the conventional analytical solutions. The proposed intelligent learning and optimization cycle, based on a cooperation between two kinds of well-known artificial neural networks, finds the optimal sensing sequence for each secondary user without any prior knowledge or presumptions about the wireless environment. The structure of the proposed scheme is discussed in detail, and its efficiencies are verified through a set of illustrative numerical results.

Abstract Wireless communication relies on access to the radiocommunications spectrum. A series of high-priced spectrum auctions has indicated that there is a scarcity or an inefficient use of spectrum resources. This paper presents an Agent-based Computational Economics (ACE) model designed to study the secondary use spectrum market, which improves spectrum usage by allowing incumbent spectrum users to lease unused portions of their assigned spectrum to third parties who could put them to a better use.

Abstract: New technologies can have a significant impact on what we teach and what we do in an iSchool. In this paper, I describe how a new infrastructure option has emerged for information systems and services. The FCC's “White Spaces” decision involved a large segment of what used to be the NII (National Information Infrastructure) community, a community of considerable affinity to iSchools.

A scenario is presented in spectrum sensing for Cognitive Radio Networks based on energy detectors. Results are presented for the performance of the energy detector based on Welch periodogram. The effect of the number of signal samples and the time domain window function are demonstrated for low Signal-to-Noise Ratio values. Furthermore, the detector performance is linked to a general probabilistic scheme for sensing algorithms. Important system issues such as receiver feedback and cooperative spectrum sensing are included in this framework. Parametric computations of the probability of correct decision are presented to show the detrimental effect of the hidden node problem in a simple collaborative spectrum sensing scheme.

The spectrum access rights granted by the Federal government to spectrum users come with the expectation of protection from harmful interference. As a consequence of the growth of wireless demand and services of all types, technical progress enabling smart agile radio networks, and on-going spectrum management reform, there is both a need and opportunity to use and share spectrum more intensively and dynamically. A key element of any framework for managing harmful interference is the mechanism for enforcement of those rights. Since the rights to use spectrum and to protection from harmful interference vary by band (licensed/unlicensed, legacy/newly reformed) and type of use/users (primary/secondary, overlay/underlay), it is reasonable to expect that the enforcement mechanisms may need to vary as well.

This paper deals with spectrum sensing for cognitive radio scenarios where the decision fusion center (DFC) exploits array processing. More specifically, we explore the impact of user cooperation and orthogonal transmissions among secondary users (SUs) on the reporting channel. To this aim four protocols are considered: (i) non-orthogonal and non-cooperative; (ii) orthogonal and non-cooperative; (iii) non-orthogonal and cooperative; (iv) orthogonal and cooperative. The DFC employs maximum ratio combining (MRC) rule and performance are evaluated in terms of complementary receiver operating characteristic (CROC). Analytical results, coupled with Monte Carlo simulations, are presented.

This paper asks is whether (i) 3rd generation wireless services, as embodied in the planned and soon to be offered services emerging first in Asia and Europe, or (ii) the unlicensed wireless services such as 802.11 or wi-fi but also including more advanced wideband and ultrawideband (UWB) services which are being experimented with primarily in North America, offer more compelling visions for advanced wireless services. we conclude that secondary spectrum markets are important for the viability of the 3G industry, and not only ...

This paper investigates the detection performance of an improved energy detector for a secondary user with spatially correlated multiple antennas. In an improved energy detector, an arbitrary positive power operation p replaces the squaring operation in a conventional energy detector, and the optimum value of p that gives the best detection performance may be different from 2. Firstly, for a given value of p, we derive closed-form expressions for the probability of detection and the probability of false alarm when antennas at the secondary user are exponentially correlated. We then find the optimum value of p for two different detection criteria−maximizing the probability of detection for a target probability of false alarm, and minimizing the probability of false alarm for a target probability of detection. We show that the optimum p is strongly dependent on system parameters like number of antennas, antenna correlation coefficient among multiple antennas, and average received signal-to-noise ratio (SNR). From results, we infer that, in low SNR regime, the effect of antenna correlation is less pronounced on the optimum p. Finally, we find the optimum values of p and threshold jointly that minimize the total error rate.

Mobile Virtual Network Operators (MVNO) operate without owning spectrum usage rights, by leasing spectrum from Mobile Network Operators owning a license. Spectrum leasing may occur through a reservation process that assigns the MVNO the right, but not the obligation, to lease spectrum at a later time. Reservation contracts may be signed with strict guarantees, that provide MVNOs with the certainty of obtaining the needed spectrum, or soft guarantees, which allow the MNO to adopt an overbooking policy and refusing to lease the spectrum, compensating the refused MVNO through the payment of a penalty. In this paper the two kinds of reservation contracts are compared from the viewpoint of the MVNO, by considering the profitability of the two alternatives. The cash flows associated to the two kinds of reservation contracts are determined and employed to compare the alternatives. The probability of overbooking and the expiry time of reservations appear as the major decision factors, while the penalty value has a negligible influence. It is shown that the reservation contract with soft guarantees is to be prefereed for larger values of the expiry time and for the lower values of the overbooking probability.

Il presente Work Paper 1 (WP.1) analizza l’attività di standardizzazione e ricerca in ambiente Cognitive Radio (CR) sviluppata negli ultimi anni da diversi organi preposti a livello internazionale. In particolare, vengono individuati i possibili scenari applicativi delle Cognitive Radio Networks (CRN) definendone: architetture, funzionalità, meccanismi di coesistenza ed interoperabilità dei sistemi, protocolli di comunicazione tra i dispositivi, algoritmi per l’accesso cognitivo, etc.
A partire dalle definizioni di sistema CR, di ciclo cognitivo: osservazione-decisione-azione e di “opportunità spettrali” (anche dette “White Spaces”), il lavoro svolto indaga le soluzioni individuate in letteratura per l’espletamento delle funzioni di spectrum opportunity detection (negli approcci di sensing e geo-database), spectrum management, spectrum sharing e spectrum mobility. Viene analizzato poi lo standard IEEE 802.22, attualmente l’unico che definisca la struttura protocollare (layers: PHY, MAC e cognitive), gli schemi ed il funzionamento di un sistema operante mediante utilizzo opporunistico delle frequenze (nello specifico, le bande televisive VHF e UHF). Per meglio focalizzare la discussione sulle problematiche inerenti il digital divide, il WP.1 delinea modelli, scenari di riferimento ed architetture fisiche di rete in grado di offrire soluzioni per fornire l’accesso a banda larga in aree rurali e sub-rurali.

This paper asks is whether (i) 3 rd generation wireless services, as embodied in the planned and soon to be offered services emerging first in Asia and Europe, or (ii) the unlicensed wireless services such as 802.11 or wi-fi but also including more advanced wideband and ultrawideband (UWB) services which are being experimented with primarily in North America, offer more compelling visions for advanced wireless services. we conclude that secondary spectrum markets are important for the viability of the 3G industry, and not only for reasons of efficiency. One large difference between 2G and 3G networks, observed in our models, was that voice services alone would not generate sufficient revenues for a 3G system. License holders which up to now have concentrated on selling a single product, will need to develop a much larger range of advanced applications, which will have to be marketed and packaged in different ways for different market segments.