Showing papers by "Mats Viberg published in 2017"

Simultaneous information and power transfer under a non-linear RF energy harvesting model

Abstract: In the design of simultaneous wireless information and power transfer (SWIPT) systems, it has been typically assumed that energy conversion efficiency is independent from the level of the input power at the energy receiver. On the other hand, in practice the energy conversion efficiency exhibits a nonlinear behavior and highly depends on the input power. This leads to a discrepancy between the practical energy harvesting (EH) hardware available and the resource allocation designs made for the SWIPT systems. This work is concerned with this issue. In particular, we propose a practical quadratic model for the power conversion efficiency in EH circuitry. Comparisons with the constant efficiency models used in conventional SWIPT system design as well as another non-linear model proposed in the literature are made. With its convexity properties together with the good match it provides for the measurement data from practical EH circuitry, the proposed model is shown to be a promising alternative to the existing EH approaches. Using the proposed model, the problem of resource allocation for a multiuser Orthogonal Frequency-Division Multiple Access (OFDMA) system is investigated. The performance improvement due to the usage of the proposed non-linear model is illustrated.

Massive MIMO Systems With IQ Imbalance: Channel Estimation and Sum Rate Limits

Abstract: In this paper, we study the impact of in-phase and quadrature imbalance (IQI) on single-cell multiuser multiple-input multiple-output systems with large antenna arrays. Moreover, we consider a time-division duplex system, where we assume uplink/downlink channel reciprocity in the downlink precoding design. First, we investigate the effect of transceiver IQI on the uplink channel estimation by deriving the linear minimum-mean-square-error estimator for the IQ-impaired model and prove that only the receiver IQI at the base station (BS) limits the estimation accuracy. Then, we study the impact of uplink/downlink channel mismatch on the downlink rate caused by different IQI at the BS and user equipments (UEs). We prove that the achievable downlink rate of each UE is limited either by the receiver IQI at the UEs or jointly by the transmit and receive IQI at the BS, when there is mismatch between the uplink and downlink channels.

Transmission Strategies for Remote Estimation With an Energy Harvesting Sensor

Abstract: We consider the remote estimation of a time-correlated signal using an energy harvesting (EH) sensor. The sensor observes the unknown signal and communicates its observations to a remote fusion center using an amplify-and-forward strategy. We consider the design of optimal power allocation strategies in order to minimize the mean-square error at the fusion center. Contrary to the traditional approaches, the degree of correlation between the signal values constitutes an important aspect of our formulation. We provide the optimal power allocation strategies for a number of illustrative scenarios. We show that the most majorized power allocation strategy, i.e., the power allocation as balanced as possible, is optimal for the cases of circularly wide-sense stationary (c.w.s.s.) signals with a static correlation coefficient and sampled low-pass c.w.s.s. signals for a static channel. We show that the optimal strategy can be characterized as a water-filling type solution for sampled low-pass c.w.s.s. signals for a fading channel. Motivated by the high-complexity of the numerical solution of the optimization problem, we propose low-complexity policies for the general scenario. Numerical evaluations illustrate the close performance of these low-complexity policies to that of the optimal policies and demonstrate the effect of the EH constraints and the degree of freedom of the signal.

Improved DOA estimators using partial relaxation approach

Abstract: In this paper, the partial relaxation approach is introduced and applied to DOA estimation using spectral search. Unlike existing methods like Capon or MUSIC which can be considered as single source approximations of multi-source estimation criteria, the proposed approach accounts for the existence of multiple sources. At each direction, the manifold structure of interfering signals impinging on the sensor array is relaxed, which results in closed form estimates for the interference parameters. The conventional multidimensional optimization problem reduces, thanks to this relaxation, to a simple spectral search. Following this principle, proposed estimators based on the Deterministic Maximum Likelihood, Weighted Subspace Fitting and Covariance Fitting method are derived. Simulation results show that the performance of the proposed estimators is superior to conventional methods especially in the case of low SNR and low number of snapshots, irrespectively of the special structure of the sensor array.

Performance Analysis of Sparsity-Based Parameter Estimation

Abstract: Since the advent of the $\ell _1$ regularized least squares method (LASSO), a new line of research has emerged, which has been geared toward the application of the LASSO to parameter estimation problems. Recent years witnessed a considerable progress in this area. The notorious difficulty with discretization has been settled in the recent literature, and an entirely continuous estimation method is now available. However, an adequate analysis of this approach lacks in the current literature. This paper provides a novel analysis of the LASSO as an estimator of continuous parameters. This analysis is different from the previous ones in that our parameters of interest are associated with the support of the LASSO solution. In other words, our analysis characterizes the error in the parameterization of the support. We provide a novel framework for our analysis by studying nearly ideal sparse solutions. In this framework, we quantify the error in the high signal-to-noise ratio regime. As the result depends on the choice of the regularization parameter, our analysis also provides a new insight into the problem of selecting the regularization parameter. Without loss of generality, the results are expressed in the context of direction of arrival estimation problem.

Hybrid beamforming in uplink massive MIMO systems in the presence of blockers

Abstract: Hybrid beamforming (HBF) is a potential solution to reduce the baseband hardware cost in massive multiple-input multiple-output (MIMO) systems that has drawn considerable attention recently. In this paper, we consider the uplink of a multiuser massive MIMO system in the presence of blockers. Such blockers, which arise from, for example, users served by other non-cooperative base stations (BSs), can limit the system performance if not handled properly. We propose a HBF scheme that can remove the impact of blockers, while preserving signals from intended users. Specifically, in our two-step receive beamforming scheme, the analog beamformer (ABF) is designed based on channel covariance matrices to minimize the powers of blockers, while the digital beamformer (DBF) deals with inter-user interference. We propose an iterative algorithm that efficiently gives a good sub-optimal solution to the NP-hard problem in the ABF design. Moreover, we consider a more complete BS architecture by incorporating automatic gain control (AGC) and analog-to-digital converter (ADC). As we show in the simulations, for a system with full-precision ADCs, our scheme approaches the sum rate of an ideal fully-digital system. Interestingly, for a system with low-resolution ADCs, our HBF scheme can even outperform a fully-digital system.

Downlink performance of regularized ZF in massive MIMO systems subject to IQ imbalance

Abstract: This paper studies the impact of in-phase and quadrature imbalance (IQI) on the downlink of a single-cell multiuser multiple-input multiple-output (MU-MIMO) system with large antenna arrays. Moreover, we consider a time-division duplex (TDD) system where we assume uplink/downlink channel reciprocity in the downlink precoding design. We study the impact of uplink/downlink channel mismatch on the downlink rate caused by different IQI at the base station (BS) and users equipment (UEs). A tractable analytical expression to predict the achievable downlink rates is derived for the regularized zero-forcing (RZF) and based on this expression, we prove that, as the number of BS antennas grow large, the achievable downlink rate of each UE is limited either by the RX IQI at the UEs or by the simultaneous presence of the transmit/receive IQI at the BS and TX IQI at the UEs, when there is uplink/downlink channel mismatch.