Anna Vizziello

Cognitive radio resource management exploiting heterogeneous primary users and a radio environment map database

The efficient utilization of radio resources is a fundamental issue in cognitive radio (CR) networks. Thus, a novel cognitive radio resource management (RRM) is proposed to improve the spectrum utilization efficiency. An optimization framework for RRM is developed that makes the following contributions: (i) considering heterogeneous primary users (PUs) with multiple features stored in a radio environment map database, (ii) allowing variable CR demands, (iii) assuring interference protection towards PUs. After showing that the optimal solution is computationally infeasible, a suboptimal solution is consequently proposed. Performance evaluation is conducted in terms of total achieved data rate and satisfaction of CR requirements.

Cognitive Radio Resource Management Exploiting Heterogeneous Primary Users

In this paper, a novel Cognitive Radio Resource Management (RRM) is proposed to improve the spectrum utilization efficiency. In this system, heterogeneous Primary Users (PUs) with multiple features are considered where these PU features are exploited to improve the adaptability in Cognitive Radio (CR) networks and, thus, to design an efficient Cognitive RRM. An optimization framework is developed by considering heterogeneous PUs and variable CR demands while assuring interference protection towards PUs. A suboptimal solution is proposed after showing that an optimal solution is computationally infeasible. Simulation results are conducted in terms of total achieved data rate and satisfaction of CRs requirements.

Efficient RFID Tag Identification Exploiting Hybrid UHF-UWB Tags and Compressive Sensing

In this paper, we propose a novel tags identification protocol based on compressive sensing (CS) and ultra-wideband (UWB) for radio frequency identification (RFID) systems. In a hybrid RFID system, ultra-high-frequency (UHF) reader-to-tag communications are combined with the UWB transceivers for localization and ranging purposes. Here, the UWB information of such a hybrid UHF-UWB architecture is exploited to reduce the ID search space of a UHF-CS decoding scheme. Simulation results prove that our solution significantly decreases the amount of bits required for successful tags identification, compared with the state-of-the-art protocols.

Chipless RFID for space applications

Recent works reveal a great deal of interest in the subject of wireless passive sensor for space applications. In particular, wireless passive tags can be employed during in-flight operations as well as during ground test campaigns, thanks to their robustness in extreme environments since they do not contain batteries nor any active electronic circuits. Chipless backscatter-based radio frequency identification (RFID) could be a valid alternative to surface acoustic wave (SAW) imple-mentations, especially for short-range applications like sensor monitoring aboard of satellite systems. In this work we present chipless RFIDs based on resonant substrate integrated waveguide (SIW) cavities, showing both the experimental characterization and system simulations, proving the solution feasibility for their usage on space platforms.

Frequency Domain Estimation and Compensation of Intercarrier Interference in OFDM Systems

Orthogonal Frequency Division Multiplexing (OFDM) is a transmission technique which is robust in multipath channels. It is though sensitive to frequency errors that may be caused by several factors such as frequency offset at the local oscillator, phase noise and mobility of the receiver. These errors introduce Inter-Carrier Interference (ICI) that may be represented in the frequency domain by means of an ICI matrix. Since these types of errors greatly affect the performance of an OFDM system, estimation of this matrix is crucial. In this work we propose an iterative method that uses pilot tones in the frequency domain and converges very quickly. It works in two steps. In the first, correlation between received signal and estimated transmitted signal is used to estimate the channel matrix, and the second estimates the actual transmitted data by means of Minimum Mean Square Error (MMSE) equalization. Results, in the case of high frequency offset and of a time varying flat fading channel, show that the proposed method is very effective.

Location based routing protocol exploiting heterogeneous primary users in cognitive radio networks

In cognitive radio networks (CRNs), knowledge of the primary users (PUs) position can be used to avoid harmful interference to the primary network, while at the same time be exploited to improve CR performance. In this paper, a localization algorithm is developed to calculate PUs position and a novel location based CR (LCR) routing protocol is proposed that has the following properties: (i) it considers the existence of heterogeneous PUs, (ii) exploits PUs location information, (iii) jointly selects spectrum and route, (iv) protects PUs from interference. Clusters of CRs are defined according to the spectral characteristics in a given location area, and the LCR routing protocol acts in two steps: intra-cluster and inter-cluster. Simulations are conducted in terms of CR end-to-end performance and PUs collision risk. Results reveal the importance of formulating routing protocol in terms of PU protection, which is a unique features in CR networks.

OFDM Signal Type Recognition and Adaptability Effects in Cognitive Radio Networks

The ability of adapting to the environment in the most efficient way is a crucial issue in Cognitive Radio (CR) networks. For this purpose, an accurate estimation of the characteristics and activity of the Primary Users (PUs) is required. A system that takes into account heterogeneous PUs with several features is developed. A new scheme is integrated in the system to exploit these motleys and to improve the adaptability in CR networks. Through the proposed PU signal type recognition, the PU signal is detected and classified. The features of each PU type: the allowed interference levels, the bandwidth and the idle time, are extracted and exploited for CR adaptability effects. For this, a new CR throughput/interference adapter is proposed. The CR throughput is efficiently increased depending on the specific characteristics of PU types. Simulation results show that the proposed PU type recognition detects, distinguishes and classifies PU signals in Additive White Gaussian Noise (AWGN). It is shown that CR throughput varies with PU features for the improvement of CR adaptability.

Joint Phase Recovery for XPIC System Exploiting Adaptive Kalman Filtering

The phase recovery scheme of a cross-polar interference cancellation (XPIC) system is considered here, assuming two completely independent RF transceiver chains for the two different polarizations. A novel Kalman-based algorithm is proposed to jointly recover the phase of both the main polarization signal and the interfering one, at each single receiver of an XPIC system. The time evolution of the received phases and frequencies is represented by using both a new four-state model and a simplified two-state implementation. Simulations are conducted considering a typical backhaul link and the results prove the effectiveness of the proposed solution, compared to a common phase-locked loop (PLL) approach. Unlike the PLL scheme, the proposed Kalman-based algorithm directly adapts its parameters according to the different channel conditions, i.e., the signal-to-noise ratio per bit (

System architecture in cognitive radio networks using a radio environment map

E_b/N_0

Estimation and Mitigation of Intercarrier Interference for OFDM Systems in Multipath Fading Channels

) and the the cross-polarization discrimination (XPD).