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Symeon Chatzinotas

Publications and source records attributed to Symeon Chatzinotas.

432 records · Page 24Linked to original sources

Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications

The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to frame multiple users per transmission and the per-antenna transmit power limitations, are addressed. To this end, the so-called frame-based precoding problem is optimally solved using the principles of physical layer multicasting to multiple co-channel groups under per-antenna constraints. In this context, a novel optimization problem that aims at maximizing the system sum rate under individual power constraints is proposed. Added to that, the formulation is further extended to include availability constraints. As a result, the high gains of the sum rate optimal design are traded off to satisfy the stringent availability requirements of satellite systems. Moreover, the throughput maximization with a granular spectral efficiency versus SINR function, is formulated and solved. Finally, a multicast-aware user scheduling policy, based on the channel state information, is developed. Thus, substantial multiuser diversity gains are gleaned. Numerical results over a realistic simulation environment exhibit as much as 30% gains over conventional systems, even for 7 users per frame, without modifying the framing structure of legacy communication standards.

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Coordinated Multibeam Satellite Co-location: The Dual Satellite Paradigm

In the present article, a new system architecture for the next generation of satellite communication (SatComs) is presented. The key concept lies in the collaboration between multibeam satellites that share one orbital position. Multi-satellite constellations in unique orbital slots offer gradual deployment to cover unpredictable traffic patterns and redundancy to hardware failure advantages. They are also of high relevance during the satellite replacement phases or necessitated by constraints in the maximum communications payload that a single satellite can bear. In this context, the potential gains of advanced architectures, that is architectures enabled by the general class of cooperative and cognitive techniques, are exhibited via a simple paradigm. More specifically, the scenario presented herein, involves two co-existing multibeam satellites which illuminate overlapping coverage areas. Based on this scenario, specific types of cooperative and cognitive techniques are herein considered as candidate technologies that can boost the performance of multibeam satellite constellations. These techniques are compared to conventional frequency splitting configurations in terms of three different criteria, namely the spectral efficiency, the power efficiency and the fairness. Consequently, insightful guidelines for the design of future high throughput constellations of multibeam satellites are given.

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Multicast Multigroup Beamforming for Per-antenna Power Constrained Large-scale Arrays

Large in the number of transmit elements, multi-antenna arrays with per-element limitations are in the focus of the present work. In this context, physical layer multigroup multicasting under per-antenna power constrains, is investigated herein. To address this complex optimization problem low-complexity alternatives to semi-definite relaxation are proposed. The goal is to optimize the per-antenna power constrained transmitter in a maximum fairness sense, which is formulated as a non-convex quadratically constrained quadratic problem. Therefore, the recently developed tool of feasible point pursuit and successive convex approximation is extended to account for practical per-antenna power constraints. Interestingly, the novel iterative method exhibits not only superior performance in terms of approaching the relaxed upper bound but also a significant complexity reduction, as the dimensions of the optimization variables increase. Consequently, multicast multigroup beamforming for large-scale array transmitters with per-antenna dedicated amplifiers is rendered computationally efficient and accurate. A preliminary performance evaluation in large-scale systems for which the semi-definite relaxation constantly yields non rank-1 solutions is presented.

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Estimation-Throughput Tradeoff for Underlay Cognitive Radio Systems

Understanding the performance of cognitive radio systems is of great interest. To perform dynamic spectrum access, different paradigms are conceptualized in the literature. Of these, Underlay System (US) has caught much attention in the recent past. According to US, a power control mechanism is employed at the Secondary Transmitter (ST) to constrain the interference at the Primary Receiver (PR) below a certain threshold. However, it requires the knowledge of channel towards PR at the ST. This knowledge can be obtained by estimating the received power, assuming a beacon or a pilot channel transmission by the PR. This estimation is never perfect, hence the induced error may distort the true performance of the US. Motivated by this fact, we propose a novel model that captures the effect of channel estimation errors on the performance of the system. More specifically, we characterize the performance of the US in terms of the estimation-throughput tradeoff. Furthermore, we determine the maximum achievable throughput for the secondary link. Based on numerical analysis, it is shown that the conventional model overestimates the performance of the US.

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Large System Analysis for Amplify & Forward SIMO Multiple Access Channel with Ill-conditioned Second Hop

Relaying has been extensively studied during the last decades and has found numerous applications in wireless communications. The simplest relaying method, namely amplify and forward, has shown potential in MIMO multiple access systems, when Gaussian fading channels are assumed for both hops. However, in some cases ill conditioned channels may appear on the second hop. For example, this impairment could affect cooperative BS systems with microwave link backhauling, which involve strong line of sight channels with insufficient scattering. In this paper, we consider a large system analysis of such as model focusing on both optimal joint decoding and joint MMSE filtering receivers. Analytical methods based on free probability are presented for calculating the ergodic throughput, the MMSE error and the average SINR. Furthermore, the performance degradation of the system throughput is evaluated considering second hop impairments such as ill-conditioning and rank deficiency, while high- and low-SNR limits are calculated for the considered performance metrics. Finally, the cooperative BS system is compared to a conventional channel resource division strategy and suitable operating points are proposed.

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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 antennas systems. Using symbol level precoding, a new approach towards the multiuser interference is discussed along this paper. The concept of exploiting the interference between the spatial multiuser transmissions by jointly utilizing the data information (DI) and channel state information (CSI), in order to design symbol-level precoders, is proposed. In this direction, the interference among the data streams is transformed under certain conditions to 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 user's 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.

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Sum Rate Maximizing Multigroup Multicast Beamforming under Per-antenna Power Constraints

A multi-antenna transmitter that conveys independent sets of common data to distinct groups of users is herein considered, a model known as physical layer multicasting to multiple co-channel groups. In the recently proposed context of per-antenna power constrained multigroup multicasting, the present work focuses on a novel system design that aims at maximizing the total achievable throughput. Towards increasing the system sum rate, the available power resources need to be allocated to well conditioned groups of users. A detailed solution to tackle the elaborate sum rate maximization multigroup multicast problem under per-antenna power constraints is therefore derived. Numerical results are presented to quantify the gains of the proposed algorithm over heuristic solutions. Besides Rayleigh faded channels, the solution is also applied to uniform linear array transmitters operating in the far field, where line-ofsight conditions are realized. In this setting, a sensitivity analysis with respect to the angular separation of co-group users is included. Finally, a simple scenario providing important intuitions for the sum rate maximizing multigroup multicast solutions is elaborated.

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Multicast Multigroup Beamforming under Per-antenna Power Constraints

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.

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Weighted Fair Multicast Multigroup Beamforming under Per-antenna Power Constraints

A multi-antenna 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 co-channel 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.

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Constructive Interference in Linear Precoding Systems: Power Allocation and User Selection

The exploitation of interference in a constructive manner has recently been proposed for the downlink of multiuser, multi-antenna transmitters. This novel linear precoding technique, herein referred to as constructive interference zero forcing (CIZF) precoding, has exhibited substantial gains over conventional approaches; the concept is to cancel, on a symbol-by-symbol basis, only the interfering users that do not add to the intended signal power. In this paper, the power allocation problem towards maximizing the performance of a CIZF system with respect to some metric (throughput or fairness) is investigated. What is more, it is shown that the performance of the novel precoding scheme can be further boosted by choosing some of the constructive multiuser interference terms in the precoder design. Finally, motivated by the significant effect of user selection on conventional, zero forcing (ZF) precoding, the problem of user selection for the novel precoding method is tackled. A new iterative, low complexity algorithm for user selection in CIZF is developed. Simulation results are provided to display the gains of the algorithm compared to known user selection approaches.

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Multi-User Detection in Multibeam Mobile Satellite Systems: A Fair Performance Evaluation

Multi-User Detection (MUD) techniques are currently being examined as promising technologies for the next generation of broadband, interactive, multibeam, satellite communication (SatCom) systems. Results in the existing literature have shown that when full frequency and polarization reuse is employed and user signals are jointly processed at the gateway, more than threefold gains in terms of spectral efficiency over conventional systems can be obtained. However, the information theoretic results for the capacity of the multibeam satellite channel, are given under ideal assumptions, disregarding the implementation constraints of such an approach. Considering a real system implementation, the adoption of full resource reuse is bound to increase the payload complexity and power consumption. Since the novel techniques require extra payload resources, fairness issues in the comparison among the two approaches arise. The present contribution evaluates in a fair manner, the performance of the return link (RL) of a SatCom system serving mobile users that are jointly decoded at the receiver. More specifically, the achievable spectral efficiency of the assumed system is compared to a conventional system under the constraint of equal physical layer resource utilization. Furthermore, realistic link budgets for the RL of mobile SatComs are presented, thus allowing the comparison of the systems in terms of achievable throughput. Since the proposed systems operate under the same payload requirements as the conventional systems, the comparison can be regarded as fair. Finally, existing analytical formulas are also employed to provide closed form descriptions of the performance of clustered multibeam MUD, thus introducing insights on how the performance scales with respect to the system parameters.

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User Scheduling for Coordinated Dual Satellite Systems with Linear Precoding

The constantly increasing demand for interactive broadband satellite communications is driving current research to explore novel system architectures that reuse frequency in a more aggressive manner. To this end, the topic of dual satellite systems, in which satellites share spatial (i.e. same coverage area) and spectral (i.e. full frequency reuse) degrees of freedom is introduced. In each multibeam satellite, multiuser interferences are mitigated by employing zero forcing precoding with realistic per antenna power constraints. However, the two sets of users that the transmitters are separately serving, interfere. The present contribution, proposes the partial cooperation, namely coordination between the two coexisting transmitters in order to reduce interferences and enhance the performance of the whole system, while maintaining moderate system complexity. In this direction, a heuristic, iterative, low complexity algorithm that allocates users in the two interfering sets is proposed. This novel algorithm, improves the performance of each satellite and of the overall system, simultaneously. The first is achieved by maximizing the orthogonality between users allocated in the same set, hence optimizing the zero forcing performance, whilst the second by minimizing the level of interferences between the two sets. Simulation results show that the proposed method, compared to conventional techniques, significantly increases spectral efficiency.

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MMSE Performance Analysis of Generalized Multibeam Satellite Channels

Aggressive frequency reuse in the return link (RL) of multibeam satellite communications (SatComs) is crucial towards the implementation of next generation, interactive satellite services. In this direction, multiuser detection has shown great potential in mitigating the increased intrasystem interferences, induced by a tight spectrum reuse. Herein we present an analytic framework to describe the linear Minimum Mean Square Error (MMSE) performance of multiuser channels that exhibit full receive correlation: an inherent attribute of the RL of multibeam SatComs. Analytic, tight approximations on the MMSE performance are proposed for cases where closed form solutions are not available in the existing literature. The proposed framework is generic, thus providing a generalized solution straightforwardly extendable to various fading models over channels that exhibit full receive correlation. Simulation results are provided to show the tightness of the proposed approximation with respect to the available transmit power.

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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 a Standard Condition Number (SCN) based decision statistic based on asymptotic Random Matrix Theory (RMT) for decision process. Firstly, the effect of noise correlation on eigenvalue based Spectrum Sensing (SS) is studied analytically under both the noise only and the signal plus noise hypotheses. Secondly, new bounds for the SCN are proposed for achieving improved sensing in correlated noise scenarios. Thirdly, the performance of Fractional Sampling (FS) based SS is studied and a method for determining the operating point for the FS rate in terms of sensing performance and complexity is suggested. Finally, an SNR estimation technique based on the maximum eigenvalue of the received signal's covariance matrix is proposed. It is shown that proposed SCN-based threshold improves sensing performance in the presence of correlated noise and SNRs upto 0 dB can be reliably estimated without the knowledge of noise variance.

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Multi-Gateway Cooperation in Multibeam Satellite Systems

Multibeam systems with hundreds of beams have been recently deployed in order to provide higher capacities by employing fractional frequency reuse. Furthermore, employing full frequency reuse and precoding over multiple beams has shown great throughput potential in literature. However, feeding all this data from a single gateway is not feasible based on the current frequency allocations. In this context, we investigate a range of scenarios involving beam clusters where each cluster is managed by a single gateway. More specifically, the following cases are considered for handling intercluster interference: a) conventional frequency colouring, b) joint processing within cluster, c) partial CSI sharing among clusters, d) partial CSI and data sharing among clusters. CSI sharing does not provide considerable performance gains with respect to b) but combined with data sharing offers roughly a 40% improvement over a) and a 15% over b).

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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. 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. The performance of the proposed linear precoding scheme is also shown to be very close to the dirty paper coding.

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Interference Alignment for Clustered Multicell Joint Decoding

Multicell joint processing has been proven to be very efficient in overcoming the interference-limited nature of the cellular paradigm. However, for reasons of practical implementation global multicell joint decoding is not feasible and thus clusters of cooperating Base Stations have to be considered. In this context, intercluster interference has to be mitigated in order to harvest the full potential of multicell joint processing. In this paper, four scenarios of intercluster interference are investigated, namely a) global multicell joint processing, b) interference alignment, c) resource division multiple access and d) cochannel interference allowance. Each scenario is modelled and analyzed using the per-cell ergodic sum-rate capacity as a figure of merit. In this process, a number of theorems are derived for analytically expressing the asymptotic eigenvalue distributions of the channel covariance matrices. The analysis is based on principles from Free Probability theory and especially properties in the R and Stieltjes transform domain.

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Free Probability based Capacity Calculation of Multiantenna Gaussian Fading Channels with Cochannel Interference

During the last decade, it has been well understood that communication over multiple antennas can increase linearly the multiplexing capacity gain and provide large spectral efficiency improvements. However, the majority of studies in this area were carried out ignoring cochannel interference. Only a small number of investigations have considered cochannel interference, but even therein simple channel models were employed, assuming identically distributed fading coefficients. In this paper, a generic model for a multi-antenna channel is presented incorporating four impairments, namely additive white Gaussian noise, flat fading, path loss and cochannel interference. Both point-to-point and multiple-access MIMO channels are considered, including the case of cooperating Base Station clusters. The asymptotic capacity limit of this channel is calculated based on an asymptotic free probability approach which exploits the additive and multiplicative free convolution in the R- and S-transform domain respectively, as well as properties of the eta and Stieltjes transform. Numerical results are utilized to verify the accuracy of the derived closed-form expressions and evaluate the effect of the cochannel interference.

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