arXiv subjects

Luc Vandendorpe

Publications and source records attributed to Luc Vandendorpe.

At least 55 records · Page 3Linked to original sources

arXiv2019

(l1,l2)-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements

This letter analyzes the performances of a simple reconstruction method, namely the Projected Back-Projection (PBP), for estimating the direction of a sparse signal from its phase-only (or amplitude-less) complex Gaussian random measurements, i.e., an extension of one-bit compressive sensing to the complex field. To study the performances of this algorithm, we show that complex Gaussian random matrices respect, with high probability, a variant of the Restricted Isometry Property (RIP) relating to the l1 -norm of the sparse signal measurements to their l2 -norm. This property allows us to upper-bound the reconstruction error of PBP in the presence of phase noise. Monte Carlo simulations are performed to highlight the performance of our approach in this phase-only acquisition model when compared to error achieved by PBP in classical compressive sensing.

eess.SP↗

arXiv2019

Online Power Allocation at Energy Harvesting Transmitter for Multiple Receivers with and without Individual Rate Constraints for OMA and NOMA Transmissions

In this paper, we propose an online power allocation scheme to maximize the time averaged sum rate for multiple downlink receivers with energy harvesting transmitter. The transmitter employs non-orthogonal multiple access (NOMA) and/or orthogonal multiple access (OMA) to transmit data to multiple users. Additionally, we consider the scenario where each individual user has a quality of service constraint on its required instantaneous rate. The decisions of total transmit power and power allocation for different users in a given time slot are obtained with the help of Lyapunov optimization technique. The proposed schemes do not require any statistical information of the channel states and the harvested energy. The proposed power allocation schemes entail in small complexity based power allocation decisions. Therefore, the proposed schemes can provide solutions in real time and are more suited for online power allocation problems where the system state parameters (e.g. channel state, harvested energy etc) change quickly. The performances of the proposed schemes are demonstrated with the help of simulation results.

cs.IT↗

arXiv2019

Minimization of Sum Inverse Energy Efficiency for Multiple Base Station Systems

A sum inverse energy efficiency (SIEE) minimization problem is solved. Compared with conventional sum energy efficiency (EE) maximization problems, minimizing SIEE achieves a better fairness. The paper begins by proposing a framework for solving sum-fraction minimization (SFMin) problems, then uses a novel transform to solve the SIEE minimization problem in a multiple base station (BS) system. After the reformulation into a multi-convex problem, the alternating direction method of multipliers (ADMM) is used to further simplify the problem. Numerical results confirm the efficiency of the transform and the fairness improvement of the SIEE minimization. Simulation results show that the algorithm convergences fast and the ADMM method is efficient.

eess.SP↗

arXiv2019

Weighted Spectral Efficiency Optimization for Hybrid Beamforming in Multiuser Massive MIMO-OFDM Systems

In this paper, we consider hybrid beamforming designs for multiuser massive multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. Aiming at maximizing the weighted spectral efficiency, we propose one alternating maximization framework where the analog precoding is optimized by Riemannian manifold optimization. If the digital precoding is optimized by a locally optimal algorithm, we obtain a locally optimal alternating maximization algorithm. In contrast, if we use a weighted minimum mean square error (MMSE)-based iterative algorithm for digital precoding, we obtain a suboptimal alternating maximization algorithm with reduced complexity in each iteration. By characterizing the upper bound of the weighted arithmetic and geometric means of mean square errors (MSEs), it is shown that the two alternating maximization algorithms have similar performance when the user specific weights do not have big differences. Verified by numerical results, the performance gap between the two alternating maximization algorithms becomes large when the ratio of the maximal and minimal weights among users is very large. Moreover, we also propose a low-complexity closed-form method without iterations. It employs matrix decomposition for the analog beamforming and weighted MMSE for the digital beamforming. Although it is not supposed to maximize the weighted spectral efficiency, it exhibits small performance deterioration compared to the two iterative alternating maximization algorithms and it qualifies as a good initialization for iterative algorithms, saving thereby iterations.

eess.SP↗

arXiv2019

Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce

In this work, a heterogeneous set of wireless devices sharing a common access point collaborates to perform a set of tasks. Using the Map-Reduce distributed computing framework, the tasks are optimally distributed amongst the nodes with the objective of minimizing the total energy consumption of the nodes while satisfying a latency constraint. The derived optimal collaborative-computing scheme takes into account both the computing capabilities of the nodes and the strength of their communication links. Numerical simulations illustrate the benefits of the proposed optimal collaborative-computing scheme over a blind collaborative-computing scheme and the non-collaborative scenario, both in term of energy savings and achievable latency. The proposed optimal scheme also exhibits the interesting feature of allowing to trade energy for latency, and vice versa.

eess.SP↗

arXiv2018

An extreme bit-rate reduction scheme for 2D radar localization

In this paper, we further expand on the work in [1] that focused on the localization of targets in a 2D space using 1-bit dithered measurements coming from a 2 receiving antennae radar. Our aim is to further reduce the hardware requirements and bit-rate, by dropping one of the baseband IQ channel from each receiving antenna. To that end, the structure of the received signals is exploited to recover the positions of multiple targets. Simulations are performed to highlight the accuracy and limitations of the proposed scheme under severe bit-rate reduction.

eess.SP↗

arXiv2018

Quantity over Quality: Dithered Quantization for Compressive Radar Systems

In this paper, we investigate a trade-off between the number of radar observations (or measurements) and their resolution in the context of radar range estimation. To this end, we introduce a novel estimation scheme that can deal with strongly quantized received signals, going as low as 1-bit per signal sample. We leverage for this a dithered quantized compressive sensing framework that can be applied to classic radar processing and hardware. This allows us to remove ambiguous scenarios prohibiting correct range estimation from (undithered) quantized base-band radar signal. Two range estimation algorithms are studied: Projected Back Projection (PBP) and Quantized Iterative Hard Thresholding (QIHT). The effectiveness of the reconstruction methods combined with the dithering strategy is shown through Monte Carlo simulations. Furthermore we show that: (i), in dithered quantization, the accuracy of target range estimation improves when the bit-rate (i.e., the total number of measured bits) increases, whereas the accuracy of other undithered schemes saturate in this case; and (ii), for fixed, low bit-rate scenarios, severely quantized dithered schemes exhibit better performances than their full resolution counterparts. These observations are confirmed using real measurements obtained in a controlled environment, demonstrating the feasibility of the method in real ranging applications.

eess.SP↗

arXiv2018

SWIPT-based Real-Time Mobile Computing Systems: A Stochastic Geometry Perspective

Driven by the Internet of Things vision, recent years have seen the rise of new horizons for the wireless ecosystem in which a very large number of mobile low power devices interact to run sophisticated applications. The main hindrance to the massive deployment of low power nodes is most probably the prohibitive maintenance cost of battery replacement and the ecotoxicity of the battery production/end-of-life. An emerging research direction to avoid battery replacement is the combination of radio frequency energy harvesting and mobile computing (MC). In this paper, we propose the use of simultaneous information and power transfer (SWIPT) to control the distributed computation process while delivering power to perform the computation tasks requested. A real-time MC system is considered, meaning that the trade-off between the information rate and the energy harvested must be carefully chosen to guarantee that the CPU may perform tasks of given complexity before receiving a new control signal. In order to provide a system-level perspective on the performance of SWIPT-MC networks, we propose a mathematical framework based on stochastic geometry to characterise the rate-energy trade-off of the system. The resulting achievable performance region is then put in relation with the CPU energy consumption to investigate the operating conditions of real-time computing systems. Finally, numerical results illustrate the joint effect of the network densification and the propagation environment on the optimisation of the CPU usage.

cs.IT↗

arXiv2018

1-bit Localization Scheme for Radar using Dithered Quantized Compressed Sensing

We present a novel scheme allowing for 2D target localization using highly quantized 1-bit measurements from a Frequency Modulated Continuous Wave (FMCW) radar with two receiving antennas. Quantization of radar signals introduces localization artifacts, we remove this limitation by inserting a dithering on the unquantized observations. We then adapt the projected back projection algorithm to estimate both the range and angle of targets from the dithered quantized radar observations, with provably decaying reconstruction error when the number of observations increases. Simulations are performed to highlight the accuracy of the dithered scheme in noiseless conditions when compared to the non-dithered and full 32-bit resolution under severe bit-rate reduction. Finally, measurements are performed using a radar sensor to demonstrate the effectiveness and performances of the proposed quantized dithered scheme in real conditions.

eess.SP↗

arXiv2018

On the effect of blockage objects in dense MIMO SWIPT networks

Simultaneous information and power transfer (SWIPT) is characterised by the ambiguous role of multi-user interference. In short, the beneficial effect of multi-user interference on RF energy harvesting is obtained at the price of a reduced link capacity, thus originating nontrivial trade-offs between the achievable information rate and the harvestable energy. Arguably, in indoor environments, this trade-off might be affected by the propagation loss due to blockage objects like walls. Hence, a couple of fundamental questions arise. How much must the network elements be densified to counteract the blockage attenuation? Is blockage always detrimental on the achievable rate-energy trade-off? In this paper, we analyse the performance of an indoor multiple-input multiple-output (MIMO) SWIPT-enabled network in the attempt to shed a light of those questions. The effects of the obstacles are examined with the help of a stochastic approach in which energy transmitters (also referred to as power heads) are located by using a Poisson Point Process and walls are generated through a Manhattan Poisson Line Process. The stochastic behaviour of the signal attenuation and the multi-user interference is studied to obtain the Joint Complementary Cumulative Distribution Function (J-CCDF) of information rate and harvested power. Theoretical results are validated through Monte Carlo simulations. Eventually, the rate-energy trade-off is presented as a function of the frequency of walls to emphasise the cross-dependences between the deployment of the network elements and the topology of the venue.

cs.IT↗

arXiv2017

Optimal Resource Allocation in Ultra-low Power Fog-computing SWIPT-based Networks

In this paper, we consider a fog computing system consisting of a multi-antenna access point (AP), an ultra-low power (ULP) single antenna device and a fog server. The ULP device is assumed to be capable of both energy harvesting (EH) and information decoding (ID) using a time-switching simultaneous wireless information and power transfer (SWIPT) scheme. The ULP device deploys the harvested energy for ID and either local computing or offloading the computations to the fog server depending on which strategy is most energy efficient. In this scenario, we optimize the time slots devoted to EH, ID and local computation as well as the time slot and power required for the offloading to minimize the energy cost of the ULP device. Numerical results are provided to study the effectiveness of the optimized fog computing system and the relevant challenges.

eess.SP↗

arXiv2017

Pilot Contamination for Wideband Massive MMO: Number of cells Vs Multipath

This paper proposes a novel joint channel estimation and beamforming approach for multicell wideband massive multiple input multiple output (MIMO) systems. With the proposed channel estimation and beamforming approach, we determine the number of cells $N_c$ that can utilize the same time and frequency resource while mitigating the effect of pilot contamination. The proposed approach exploits the multipath characteristics of wideband channels. Specifically, when the channel has a maximum of $L$ multipath taps, \textcolor{red}{it is shown that $N_c\leq L$ cells can estimate the channels of their user equipments (UEs) and perform beamforming while mitigating the effect of pilot contamination.} In a typical long term evolution (LTE) channel environment having delay spread $T_d=4.69μ$ second and channel bandwidth $B=2.5$MHz, we have found that $L=18$ cells can use this band. In practice, $T_d$ is constant for a particular environment and carrier frequency, and hence $L$ increases as the bandwidth increases. All the analytical expressions have been validated, and the superiority of the proposed design over the existing ones is demonstrated using extensive numerical simulations both for correlated and uncorrelated channels. The proposed channel estimation and beamforming design is linear and simple to implement.

cs.IT↗

arXiv2017

Multipath Multiplexing for Capacity Enhancement in SIMO Wireless Systems

This paper proposes a novel and simple orthogonal faster than Nyquist (OFTN) data transmission and detection approach for a single input multiple output (SIMO) system. It is assumed that the signal having a bandwidth $B$ is transmitted through a wireless channel with $L$ multipath components. Under this assumption, the current paper provides a novel and simple OFTN transmission and symbol-by-symbol detection approach that exploits the multiplexing gain obtained by the multipath characteristic of wideband wireless channels. It is shown that the proposed design can achieve a higher transmission rate than the existing one (i.e., orthogonal frequency division multiplexing (OFDM)). Furthermore, the achievable rate gap between the proposed approach and that of the OFDM increases as the number of receiver antennas increases for a fixed value of $L$. This implies that the performance gain of the proposed approach can be very significant for a large-scale multi-antenna wireless system. The superiority of the proposed approach is shown theoretically and confirmed via numerical simulations. {Specifically, we have found {upper-bound average} rates of 15 bps/Hz and 28 bps/Hz with the OFDM and proposed approaches, respectively, in a Rayleigh fading channel with 32 receive antennas and signal to noise ratio (SNR) of 15.3 dB. The extension of the proposed approach for different system setups and associated research problems is also discussed.

cs.IT↗

arXiv2016

Joint MOO of Transmit Precoding and Receiver Design in a Downlink Time Switching MISO SWIPT System

In this paper, we consider a time-switching (TS) co-located simultaneous wireless information and power transfer (SWIPT) system consisting of multiple multi-antenna access points which serve multiple single antenna users. In this scenario, we propose a multi-objective optimization (MOO) framework to design jointly the Pareto optimal beamforming vector and the TS ratio for each receiver. The objective is to maximize the utility vector including the achieved data rates and the harvested energies of all users simultaneously. This problem is a non-convex rank-constrained MOO problem which is relaxed and transformed into a non-convex semidefinite program (SDP) based on the weighted Chebycheff method. The majorization-minimization algorithm is utilized to solve the nonconvex SDP and the optimal solution is proved to satisfy the rank constraint. We also study the problem of optimizing the beamforming vectors in a fixed TS ratio scenario with the same approach. Numerical results are provided for two coordinated access points with MISO configuration. The results illustrate the trade-off between harvested energy and information data rate objectives and show the effect of optimizing the precoding strategy and TS ratio on this trade-off.

cs.IT↗

arXiv2016

On the Number of RF Chains and Phase Shifters, and Scheduling Design with Hybrid Analog-Digital Beamforming

This paper considers hybrid beamforming (HB) for downlink multiuser massive multiple input multiple output (MIMO) systems with frequency selective channels. For this system, first we determine the required number of radio frequency (RF) chains and phase shifters (PSs) such that the proposed HB achieves the same performance as that of the digital beamforming (DB) which utilizes $N$ (number of transmitter antennas) RF chains. We show that the performance of the DB can be achieved with our HB just by utilizing $r_t$ RF chains and $2r_t(N-r_t + 1)$ PSs, where $r_t \leq N$ is the rank of the combined digital precoder matrices of all sub-carriers. Second, we provide a simple and novel approach to reduce the number of PSs with only a negligible performance degradation. Numerical results reveal that only $20-40$ PSs per RF chain are sufficient for practically relevant parameter settings. Finally, for the scenario where the deployed number of RF chains $(N_a)$ is less than $r_t$, we propose a simple user scheduling algorithm to select the best set of users in each sub-carrier. Simulation results validate theoretical expressions, and demonstrate the superiority of the proposed HB design over the existing HB designs in both flat fading and frequency selective channels.

cs.IT↗

arXiv2015

Mean Square Error bounds for parameter estimation under model misspecification

In parameter estimation, assumptions about the model are typically considered which allow us to build optimal estimation methods under many statistical senses. However, it is usually the case where such models are inaccurately known or not capturing the complexity of the observed phenomenon. A natural question arises to whether we can find fundamental estimation bounds under model mismatches. This paper derives a general bound on the mean square error (MSE) following the Ziv-Zakai methodology for the widely used additive Gaussian model. The general result accounts for erroneous functionals, hyperparameters, and distributions differing from the Gaussian. The result is then particularized to gain some insight into specific problems and some illustrative examples demonstrate the predictive capabilities of the bound.

math.ST↗

arXiv2015

Pilot Contamination Mitigation for Wideband Massive MMO: Number of Cells Vs Multipath

This paper proposes novel joint channel estimation and beamforming approach for multicell wideband massive multiple input multiple output (MIMO) systems. Using our channel estimation and beamforming approach, we determine the number of cells $N_c$ that can utilize the same time and frequency resource while mitigating the effect of pilot contamination. The proposed approach exploits the multipath characteristics of wideband channels. Specifically, when the channel has $L$ multipath taps, it is shown that $N_c\leq L$ cells can reliably estimate the channels of their user equipments (UEs) and perform beamforming while mitigating the effect of pilot contamination. For example, in a long term evolution (LTE) channel environment having delay spread $T_d=4.69μ$ second and channel bandwidth $B=2.5$MHz, we have found that $L=18$ cells can use this band. In practice, $T_d$ is constant for a particular environment and carrier frequency, and hence $L$ increases as the bandwidth increases. The proposed channel estimation and beamforming design is linear, simple to implement and significantly outperforms the existing designs, and is validated by extensive simulations.

cs.IT↗

arXiv2015

Power Control in Networks With Heterogeneous Users: A Quasi-Variational Inequality Approach

This work deals with the power allocation problem in a multipoint-to-multipoint network, which is heterogenous in the sense that each transmit and receiver pair can arbitrarily choose whether to selfishly maximize its own rate or energy efficiency. This is achieved by modeling the transmit and receiver pairs as rational players that engage in a non-cooperative game in which the utility function changes according to each player's nature. The underlying game is reformulated as a quasi variational inequality (QVI) problem using convex fractional program theory. The equivalence between the QVI and the non-cooperative game provides us with all the mathematical tools to study the uniqueness of its Nash equilibrium (NE) points and to derive novel algorithms that allow the network to converge to these points in an iterative manner both with and without the need for a centralized processing. A small-cell network is considered as a possible case study of this heterogeneous scenario. Numerical results are used to validate the proposed solutions in different operating conditions.

cs.IT↗