New Generation Cooperative and Cognitive Dual Satellite Systems: Performance Evaluation

in Proceedings of 32nd AIAA ICSSC (2014, August)

Investigating innovative satellite architectures with enhanced system through- put is one of the most important challenges towards realizing the next generation of satellite communication systems. In this ... [more ▼]

Investigating innovative satellite architectures with enhanced system through- put is one of the most important challenges towards realizing the next generation of satellite communication systems. In this context, we study two advanced architectures, namely cooperative and cognitive satellite systems. These designs allow the spectral coexistence of two multibeam satellites over a common coverage area with the overlapping beam patterns. In the cooperative dual satellite system, we consider coordination between two coexisting transmitters in order to reduce the intersatellite interference. This is achieved by employing adequate user scheduling, based on the channel state information of each user. To this end, a semi-orthogonal interference aware scheduling algorithm is applied. Further, in the cognitive dual satellite system, we employ a cognitive beamhopping technique assuming that the secondary gateway is aware of the primary's beamhopping pattern. Moreover, we compare the performances of these schemes with those of the conventional multi- beam and overlapping dual satellite systems in terms of spectral efficiency, power efficiency and user fairness. Finally, we provide several insights on the performance of these schemes and provide interesting future works in these domains. [less ▲]

Compressive Sparsity Order Estimation for Wideband Cognitive Radio Receiver

in Proceedings of IEEE International Conference on Communications (ICC) (2014, June)

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity ... [more ▼]

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity pattern. However, the sparsity order of the channel occupancy is time-varying and the sampling rate of the CS receiver needs to be adjusted based on its value in order to fully exploit the potential of CS-based techniques. In this context, investigating blind Sparsity Order Estimation (SOE) techniques is an open research issue. To address this, we study an eigenvalue based compressive SOE technique using asymptotic Random Matrix Theory. We carry out detailed theoretical analysis for the signal plus noise case to derive the asymptotic eigenvalue probability distribution function (aepdf) of the measured signal’s covariance matrix for sparse signals. Subsequently, based on the derived aepdf expression, we present a technique to estimate the sparsity order of the wideband spectrum with compressive measurements using the maximum eigenvalue of the measured signal’s covariance matrix. The performance of the proposed technique is evaluated in terms of normalized SOE Error (SOEE). It is shown that the sparsity order of the wideband spectrum can be reliably estimated using the proposed technique. [less ▲]

Weighted Fair Multicast Multigroup Beamforming Under Per-antenna Power Constraints

in Multicast multigroup beamforming under per-antenna power constraints (2014, June)

Linear precoding exploits the spatial degrees of freedom offered by multi-antenna transmitters to serve multiple users over the same frequency resources. The present work focuses on simultaneously serving ... [more ▼]

Linear precoding exploits the spatial degrees of freedom offered by multi-antenna transmitters to serve multiple users over the same frequency resources. The present work focuses on simultaneously serving multiple groups of users, each with its own channel, by transmitting a stream of common symbols to each group. This scenario is known as physical layer multicasting to multiple co-channel groups. Extending the current state of the art in multigroup multicasting, the practical constraint of a maximum permitted power level radiated by each antenna is tackled herein. The considered per antenna power constrained system is optimized in a maximum fairness sense. In other words, the optimization aims at favoring the worst user by maximizing the minimum rate. This Max-Min Fair criterion is imperative in multicast systems, where the performance of all the receivers listening to the same multicast is dictated by the worst rate in the group. An analytic framework to tackle the Max-Min Fair multigroup multicasting scenario under per antenna power constraints is therefore derived. Numerical results display the accuracy of the proposed solution and provide insights to the performance of a per antenna power constrained system. [less ▲]

A Hybrid Cognitive Transceiver Architecture: Sensing-Throughput Tradeoff

in Proceedings of 9th International Conference on Cognitive Radio Oriented Wireless Networks (2014, June)

Spectrum Sensing (SS) and underlay have been considered as two important techniques for enabling the spectral coexistence of the licensed and unlicensed wireless communication systems. The SS only ... [more ▼]

Spectrum Sensing (SS) and underlay have been considered as two important techniques for enabling the spectral coexistence of the licensed and unlicensed wireless communication systems. The SS only approach ignores the interference tolerance capability of the Primary Users (PUs) while assuming the bursty PU traffic whereas the possibility of having secondary transmission with full power is neglected in an underlay based approach. To address this, it’s crucial to investigate suitable hybrid spectrum awareness and transmission strategies which can overcome the aforementioned drawbacks and achieve higher secondary throughput while protecting the PUs. In this context, we propose a hybrid cognitive transceiver which combines the SS approach with the power control based underlay approach. Furthermore, we evaluate the performance of the proposed hybrid approach considering both periodic sensing and simultaneous sensing/transmission schemes. Moreover, sensing-throughput tradeoff for the proposed hybrid approach is investigated and the performance is compared with the conventional SS only approaches in terms of the achievable throughput. It is shown that the proposed scheme can achieve a significant improvement in the secondary throughput over the conventional approaches while respecting the interference constraints of the PUs. [less ▲]

Maximum Eigenvalue Detection for Spectrum Sensing Under Correlated Noise

in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing 2014 (2014, May)

Herein, we consider the problem of detecting primary users’ signals in the presence of noise correlation, which may arise due to imperfections in filtering and oversampling operations in a Cognitive Radio ... [more ▼]

Herein, we consider the problem of detecting primary users’ signals in the presence of noise correlation, which may arise due to imperfections in filtering and oversampling operations in a Cognitive Radio (CR) receiver. In this context, we study a Maximum Eigenvalue (ME) detection technique using recent results from Random Matrix Theory (RMT) for characterizing the distribution of the maximum eigenvalue of a class of sample covariance matrices. Subsequently, we derive a theoretical expression for a sensing threshold as a function of the probability of false alarm and evaluate the sensing performance in terms of probability of correct decision. It is shown that the proposed approach significantly improves the sensing performance of the ME detector in correlated noise scenarios. [less ▲]

Cognitive Beamhopping for Spectral Coexistence of Multibeam Satellites

in International Journal of Satellite Communications and Networking (2014)

Herein, the spectral coexistence scenario of two multibeam satellites over a common coverage area is studied where a primary satellite produces larger beams while a secondary satellite has smaller beams ... [more ▼]

Herein, the spectral coexistence scenario of two multibeam satellites over a common coverage area is studied where a primary satellite produces larger beams while a secondary satellite has smaller beams. A novel cognitive beamhopping satellite system is proposed assuming that the secondary gateway is aware of the primary’s beamhopping pattern. The performance of the proposed system is evaluated and compared with that of conventional multibeam and beamhopping systems in terms of throughput. It is shown that the proposed system significantly enhances the Spectral Efficiency (SE) in comparison to other systems. Furthermore, a power control technique is applied on the secondary transmission in order to adhere to the primary’s interference constraint. It is noted that the total SE increases with the number of secondary users in the full frequency reuse approach. Moreover, the Exclusion Zone (EZ) principle is applied to exploit the regions in which the secondary system can operate without causing harmful interference to the primary system. It is shown that the EZ radius of 8.5 dB is sufficient to protect the primary system perfectly with a significant gain in SE. Finally, it is shown that power control and the EZ methods are suitable for lower and higher values of secondary aggregated interference respectively. [less ▲]

Cognitive Interference Alignment for Spectral Coexistence

in Cognitive Radio and Networking for Heterogeneous Wireless Networks (2014)

Interference Alignment (IA) has been widely recognized as a promising interference mitigation technique since it can achieve the optimal degrees of freedom in certain interference limited channels. In the ... [more ▼]

Interference Alignment (IA) has been widely recognized as a promising interference mitigation technique since it can achieve the optimal degrees of freedom in certain interference limited channels. In the context of Cognitive Radio (CR) networks, this technique allows the coexistence of two heterogeneous wireless systems in an underlay cognitive mode. The main concept behind this technique is the alignment of the interference on a signal subspace in such a way that it can be filtered out at the non-intended receiver by sacrificing some signal dimensions. This chapter starts with an overview of IA principle, Degree of Freedom (DoF) concept, and the classification of existing IA techniques. Furthermore, this chapter includes a discussion about IA applications in CR networks.Moreover, a generic system model is presented for allowing the coexistence of two heterogeneous networks using IA approach while relevant precoding and filtering processes are described. In addition, two important practical applications of the IA technique are presented along with the numerical results for underlay spectral coexistence of (i) femtocell-macrocell systems, and (ii) monobeam-multibeam satellite systems. More specifically, an uplink IA scheme is investigated in order to mitigate the interference of femtocell User Terminals (UTs) towards the macrocell Base Station (BS) in the spatial domain and the interference of multibeam satellite terminals towards the monobeam satellite in the frequency domain. [less ▲]

Distribution Grid Monitoring through Pilot Injection and Successive Interference Cancellation

in Proceedings of IAEE Conference (2014)

Due to the push for renewable energy in the last decades, European countries have witnessed an exponential growth of Distributed Generation (DG) on the Medium Voltage (MV) network. An increasingly large ... [more ▼]

Due to the push for renewable energy in the last decades, European countries have witnessed an exponential growth of Distributed Generation (DG) on the Medium Voltage (MV) network. An increasingly large portion of the electricity demand is fed in through the distribution grid, whose good health and operational status will be important for guaranteeing grid stability. In Luxembourg, the distribution network is sparsely monitored and controlled, thus instabilities arising due to line overvoltage or DG malfunctioning are not rapidly detected and resolved. This research discusses a novel and low infrastructure methodology for online monitoring of the distribution grid. Such a tool will be increasingly necessary in order to guarantee the stability, reliability and security of the power network, as a larger and larger portion of the energy demand will be satisfied by DG in future years. In this research, advanced system identification techniques utilized in communications, such as Pseudo-Random Binary Sequences, Successive Interference Cancellation are applied to estimate the transfer function of power network propagation paths. The developed method proposes an online monitoring tool that computes grid parameters in real time during operation, without extensive infrastructure addition, by utilizing the PWM based inverters on the grid for active system identification. [less ▲]

Compressive Sparsity Order Estimation for Wideband Cognitive Radio Receiver

in IEEE Transactions on Signal Processing (2014)

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity ... [more ▼]

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity pattern. However, the sparsity order of the channel occupancy is time-varying and the sampling rate of the CS receiver needs to be adjusted based on its value in order to fully exploit the potential of CS-based techniques. In this context, investigating blind Sparsity Order Estimation (SOE) techniques is an open research issue. To address this, we study an eigenvalue-based compressive SOE technique using asymptotic Random Matrix Theory. We carry out detailed theoretical analysis for the signal plus noise case to derive the asymptotic eigenvalue probability distribution function (aepdf) of the measured signal’s covariance matrix for sparse signals. Subsequently, based on the derived aepdf expressions, we propose a technique to estimate the sparsity order of the wideband spectrum with compressive measurements using the maximum eigenvalue of the measured signal’s covariance matrix. The performance of the proposed technique is evaluated in terms of normalized SOE Error (SOEE). It is shown that the sparsity order of the wideband spectrum can be reliably estimated using the proposed technique for a variety of scenarios. [less ▲]

Performance of the Multibeam Satellite Return Link With Correlated Rain Attenuation

in Wireless Communications, IEEE Transactions on (2014), 13(11), 6286-6299

Rain attenuation is among the major impairments for satellite systems operating in the K-band and above. In this paper, we investigate the impact of spatially correlated rain attenuation on the ... [more ▼]

Rain attenuation is among the major impairments for satellite systems operating in the K-band and above. In this paper, we investigate the impact of spatially correlated rain attenuation on the performance of a multibeam satellite return link. For a comprehensive assessment, an analytical model for the antenna pattern that generates the beams is also proposed. We focus on the outage capacity of the link and obtain analytical approximations at high and low signal-to-noise ratio. The derived approximations provide insights into the effect of key system parameters such as the interuser distance, the satellite beam radius, or the rain intensity, and simulation results show that it fits tightly with the Monte Carlo results. Additionally, the derived expressions can be easily particularized for the single-user case, providing some novel insights. [less ▲]