Symeon Chatzinotas

Generic Optimization of Linear Precoding in Multibeam Satellite Systems

Multibeam satellite systems have been employed to provide interactive broadband services to geographical areas under-served by terrestrial infrastructure. In this context, this paper studies joint multiuser linear precoding design in the forward link of fixed multibeam satellite systems. We provide a generic optimization framework for linear precoding design to handle any objective functions of data rate with general linear and nonlinear power constraints. To achieve this, an iterative algorithm which optimizes the precoding vectors and power allocation alternatingly is proposed and most importantly, the proposed algorithm is proved to always converge. The proposed optimization algorithm is also applicable to nonlinear dirty paper coding. As a special case, a more efficient algorithm is devised to find the optimal solution to the problem of maximizing the proportional fairness among served users. In addition, the aforementioned problems and algorithms are extended to the case that each terminal has multiple co-polarization or dual-polarization antennas. Simulation results demonstrate substantial performance improvement of the proposed schemes over conventional multibeam satellite systems, zero-forcing and regularized zero-forcing precoding schemes in terms of meeting the traffic demand, e.g., using real beam patterns, over twice higher throughput can be achieved compared with the conventional scheme. The performance of the proposed linear precoding scheme is also shown to be very close to the dirty paper coding.

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Cognitive radio (CR) has been considered as a potential candidate for addressing the spectrum scarcity problem of future wireless networks. Since its conception, several researchers, academic institutions, industries, and regulatory and standardization bodies have put their significant efforts toward the realization of CR technology. However, as this technology adapts its transmission based on the surrounding radio environment, several practical issues may need to be considered. In practice, several imperfections, such as noise uncertainty, channel/interference uncertainty, transceiver hardware imperfections, signal uncertainty, and synchronization issues, may severely deteriorate the performance of a CR system. To this end, the investigation of realistic solutions toward combating various practical imperfections is very important for the successful implementation of cognitive technology. In this direction, first, this survey paper provides an overview of the enabling techniques for CR communications. Subsequently, it discusses the main imperfections that may occur in the most widely used CR paradigms and then reviews the existing approaches toward addressing these imperfections. Finally, it provides some interesting open research issues.

Weighted Fair Multicast Multigroup Beamforming Under Per-antenna Power Constraints

A multiantenna transmitter that conveys independent sets of common data to distinct groups of users is considered. This model is known as physical layer multicasting to multiple cochannel groups. In this context, the practical constraint of a maximum permitted power level radiated by each antenna is addressed. The per-antenna power constrained system is optimized in a maximum fairness sense with respect to predetermined quality of service weights. In other words, the worst scaled user is boosted by maximizing its weighted signal-to-interference plus noise ratio. A detailed solution to tackle the weighted max-min fair multigroup multicast problem under per-antenna power constraints is therefore derived. The implications of the novel constraints are investigated via prominent applications and paradigms. What is more, robust per-antenna constrained multigroup multicast beamforming solutions are proposed. Finally, an extensive performance evaluation quantifies the gains of the proposed algorithm over existing solutions and exhibits its accuracy over per-antenna power constrained systems.

Satellite cognitive communications: Interference modeling and techniques selection

Due to increasing demand of high speed data rate for satellite multimedia and broadcasting services and spectrum scarcity problem in satellite bands, exploring new techniques for enhancing spectral efficiency in satellite communication has become an important research challenge. In this aspect, satellite cognitive communication can be considered as a promising solution to solve spectrum scarcity problem. In this paper, different cognitive techniques such as underlay, overlay, interweave and database related techniques are discussed by reviewing the current state of art. Exact beam patterns of a multi-beam satellite are plotted over the Europe map and interference modeling between terrestrial Base Station (BS) and satellite terminal is carried out on the basis of interference power level. Furthermore, suitable cognitive techniques are proposed in high and low interference regions in the context of satellite cognitive communication.

Interference alignment for spectral coexistence of heterogeneous networks

The coexistence of heterogeneous networks within the same spectrum for enhancing the spectrum efficiency has attracted large interest lately in the research community. Furthermore, the research interest towards the deployment of small cells and multibeam satellites is increasing due to high capacity, easier deployment and higher energy efficiency. However, due to the scarcity of available spectrum and the requirement of additional spectrum for these systems, small cells need to coexist with macrocells and multibeam satellites need to coexist with monobeam satellites within the same spectrum. In this context, this contribution investigates an underlay spectral coexistence mechanism which exploits an interference alignment (IA) technique in order to mitigate the interference of cognitive transmitters towards the primary receivers in a normal uplink mode. More specifically, three types of IA techniques, namely static, uncoordinated and coordinated are investigated. The performance of the IA technique is evaluated and compared with primary only, resource division and no-mitigation techniques in terms of sum-rate capacity, primary to secondary rate ratio and primary rate protection ratio. It is shown that the coordinated IA technique perfectly protects the primary rate in both terrestrial and satellite coexistence scenarios.

On the multicell processing capacity of the cellular MIMO uplink channel in correlated rayleigh fading environment

In the context of cellular systems, it has been shown that multicell processing can eliminate inter-cell interference and provide high spectral efficiencies with respect to traditional interference-limited implementations. Moreover, it has been proved that the multiplexing sum-rate capacity gain of multicell processing systems is proportional to the number of base station (BS) antennas. These results have been also established for cellular systems, where BSs and user terminals (UTs) are equipped with multiple antennas. Nevertheless, a common simplifying assumption in the literature is the uncorrelated nature of the Rayleigh fading coefficients within the BSUT MIMO links. In this direction, this paper investigates the ergodic multicell-processing sum-rate capacity of the Gaussian MIMO cellular multiple-access channel in a correlated fading environment. More specifically, the multiple antennas of both BSs and UTs are assumed to be correlated according to the Kronecker product model. Furthermore, the current system model considers Rayleigh fading, uniformly distributed UTs over a planar coverage area and power-law path loss. Based on free probabilistic arguments, the empirical eigenvalue distribution of the channel covariance matrix is derived and it is used to calculate both optimal joint decoding and minimum mean square error (MMSE) filtering capacity. In addition, numerical results are presented, where the per-cell sum-rate capacity is evaluated while varying the cell density of the system, as well as the level of fading correlation. In this context, it is shown that the capacity performance is greatly compromised by BS-side correlation, whereas UT-side correlation has a negligible effect on the systems performance. Furthermore, MMSE performance is shown to be greatly suboptimal but more resilient to fading correlation in comparison to optimal decoding.

Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel

This paper investigates the problem of interference among the simultaneous multiuser transmissions in the downlink of multiple-antenna systems. Using symbol-level precoding, a new approach to exploit the multiuser interference is discussed. The concept of exploiting the interference between spatial multiuser transmissions by jointly utilizing data information (DI) and channel state information (CSI), in order to design symbol-level precoders, is proposed. To this end, the interference between data streams is transformed under certain conditions into useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. We propose a maximum ratio transmission (MRT) based algorithm that jointly exploits DI and CSI to glean the benefits from constructive multiuser interference. Subsequently, a relation between the constructive interference downlink transmission and physical layer multicasting is established. In this context, novel constructive interference precoding techniques that tackle the transmit power minimization (min-power) with individual SINR constraints at each users receivers is proposed. Furthermore, fairness through maximizing the weighted minimum SINR (max-min SINR) of the users is addressed by finding the link between the min power and max min SINR problems. Moreover, heuristic precoding techniques are proposed to tackle the weighted sum rate problem. Finally, extensive numerical results show that the proposed schemes outperform other state of the art techniques.

Cognitive spectrum utilization in Ka band multibeam satellite communications

Multibeam satellite networks in Ka band have been designed to accommodate the increasing traffic demands expected in the future. However, these systems are spectrum limited due to the current spectrum allocation policies. This paper investigates the potential of applying cognitive radio techniques in satellite communications (SatCom) in order to increase the spectrum opportunities for future generations of satellite networks without interfering with the operation of incumbent services. These extra spectrum opportunities can potentially amount to 2.4 GHz of bandwidth in the downlink and 2 GHz of bandwidth in the uplink for high density fixed satellite services (HDFSS).

Linear and nonlinear techniques for multibeam joint processing in satellite communications

Existing satellite communication standards such as DVB-S2, operate under highly-efficient adaptive coding and modulation schemes thus making significant progress in improving the spectral efficiencies of digital satellite broadcast systems. However, the constantly increasing demand for broadband and interactive satellite links emanates the need to apply novel interference mitigation techniques, striving towards Terabit throughput. In this direction, the objective of the present contribution is to investigate joint multiuser processing techniques for multibeam satellite systems. In the forward link, the performance of linear precoding is investigated with optimal nonlinear precoding (i.e., dirty article coding) acting as the upper performance limit. To this end, the resulting power and precoder design problems are approached through optimization methods. Similarly, in the return link the concept of linear filtering (i.e., linear minimum mean square error) is studied with the optimal successive interference cancelation acting as the performance limit. The derived capacity curves for both scenarios are compared to conventional satellite systems where beams are processed independently and interbeam interference is mitigated through a four color frequency reuse scheme, in order to quantify the potential gain of the proposed techniques.

Eigenvalue-Based Sensing and SNR Estimation for Cognitive Radio in Presence of Noise Correlation

Herein, we present a detailed analysis of an eigenvalue-based sensing technique in the presence of correlated noise in the context of a cognitive radio (CR). We use standard-condition-number (SCN)-based decision statistics based on asymptotic random matrix theory (RMT) for the decision process. First, the effect of noise correlation on eigenvalue-based spectrum sensing (SS) is analytically studied under both the noise-only and signal-plus-noise hypotheses. Second, new bounds for the SCN are proposed to achieve improved sensing in correlated noise scenarios. Third, the performance of fractional-sampling (FS)-based SS is studied, and a method to determine the operating point for the FS rate in terms of sensing performance and complexity is suggested. Finally, a signal-to-noise ratio (SNR) estimation technique based on the maximum eigenvalue of the covariance matrix of the received signal is proposed. It is shown that the proposed SCN-based threshold improves sensing performance in correlated noise scenarios, and SNRs up to 0 dB can be reliably estimated with a normalized mean square error (MSE) of less than 1% in the presence of correlated noise without the knowledge of noise variance.