| 1. |
- Abdalmoaty, Mohamed, 1986-, et al.
(författare)
-
The Gaussian MLE versus the Optimally weighted LSE
- 2020
-
Ingår i: IEEE signal processing magazine (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-5888 .- 1558-0792. ; 37:6, s. 195-199
-
Tidskriftsartikel (refereegranskat)abstract
- In this note, we derive and compare the asymptotic covariance matrices of two parametric estimators: the Gaussian Maximum Likelihood Estimator (MLE), and the optimally weighted Least-Squares Estimator (LSE). We assume a general model parameterization where the model's mean and variance are jointly parameterized, and consider Gaussian and non-Gaussian data distributions.
|
|
| 2. |
- Arnab, Anurag, et al.
(författare)
-
Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction
- 2018
-
Ingår i: IEEE Signal Processing Magazine. - 1558-0792 .- 1053-5888. ; 35:1, s. 37-52
-
Tidskriftsartikel (refereegranskat)abstract
- Semantic segmentation is the task of labeling every pixel in an image with a predefined object category. It has numerous applications in scenarios where the detailed understanding of an image is required, such as in autonomous vehicles and medical diagnosis. This problem has traditionally been solved with probabilistic models known as conditional random fields (CRFs) due to their ability to model the relationships between the pixels being predicted. However, deep neural networks (DNNs) recently have been shown to excel at a wide range of computer vision problems due to their ability to automatically learn rich feature representations from data, as opposed to traditional handcrafted features. The idea of combining CRFs and DNNs have achieved state-of-the-art results in a number of domains. We review the literature on combining the modeling power of CRFs with the representation-learning ability of DNNs, ranging from early work that combines these two techniques as independent stages of a common pipeline to recent approaches that embed inference of probabilistic models directly in the neural network itself. Finally, we summarize future research directions.
|
|
| 3. |
- Axell, Erik, et al.
(författare)
-
Spectrum sensing for cognitive radio: State-of-the-art and recent advances
- 2012
-
Ingår i: IEEE signal processing magazine (Print). - : IEEE Signal Processing Society. - 1053-5888 .- 1558-0792. ; 29:3, s. 101-116
-
Tidskriftsartikel (refereegranskat)abstract
- The ever-increasing demand for higher data rates in wireless communications in the face of limited or underutilized spectral resources has motivated the introduction of cognitive radio. Traditionally, licensed spectrum is allocated over relatively long time periods and is intended to be used only by licensees. Various measurements of spectrum utilization have shown substantial unused resources in frequency, time, and space [1], [2]. The concept behind cognitive radio is to exploit these underutilized spectral resources by reusing unused spectrum in an opportunistic manner [3], [4]. The phrase cognitive radio is usually attributed to Mitola [4], but the idea of using learning and sensing machines to probe the radio spectrum was envisioned several decades earlier (cf., [5]).
|
|
| 4. |
- Aydogdu, Canan, 1978, et al.
(författare)
-
Radar Interference Mitigation for Automated Driving : Exploring Proactive Strategies
- 2020
-
Ingår i: IEEE signal processing magazine (Print). - Piscataway : Institute of Electrical and Electronics Engineers (IEEE). - 1053-5888 .- 1558-0792. ; 37:4, s. 72-84
-
Tidskriftsartikel (refereegranskat)abstract
- Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the amount of radars used on modern vehicles, where most radars operate in the same frequency band, the risk of radar interference becomes a compelling issue. This article analyzes automotive radar interference and proposes several new approaches that combine industrial and academic expertise toward the goal of achieving interference-free autonomous driving (AD). © IEEE.
|
|
| 5. |
- Bergqvist, Göran, et al.
(författare)
-
The Higher-Order Singular Value Decomposition Theory and an Application
- 2010
-
Ingår i: IEEE signal processing magazine (Print). - : Institute of Electrical and Electronic Engineers. - 1053-5888 .- 1558-0792. ; 27:3, s. 151-154
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Tensor modeling and algorithms for computing various tensor decompositions (the Tucker/HOSVD and CP decompositions, as discussed here, most notably) constitute a very active research area in mathematics. Most of this research has been driven by applications. There is also much software available, including MATLAB toolboxes [4]. The objective of this lecture has been to provide an accessible introduction to state of the art in the field, written for a signal processing audience. We believe that there is good potential to find further applications of tensor modeling techniques in the signal processing field.
|
|
| 6. |
- Beygi, Lotfollah, 1977, et al.
(författare)
-
Coded Modulation for Fiber-Optic Networks
- 2014
-
Ingår i: IEEE Signal Processing Magazine. - 1558-0792 .- 1053-5888.
-
Tidskriftsartikel (refereegranskat)abstract
- In this tutorial, we study the joint design of forward error correction and modulation for fiber-optic communications. To this end, we use an information-theoretic design framework to investigate coded modulation (CM) techniques for standard additive white Gaussian noise channels and fiber-optic channels. This design guideline helps us to provide a comprehensive overview of the CM schemes in the literature. Then, by invoking recent advances in optical channel modeling for non-dispersion-managed links, we discuss two- and four-dimensional CM schemes. Moreover, we discuss the electronic computational complexity and hardware constraints of CM schemes for optical communications. Finally, we address CM schemes with signal shaping and rate-adaptation capabilities to accommodate the data transmission scheme to optical links with different signal qualities.
|
|
| 7. |
- Björnson, Emil, Professor, 1983-, et al.
(författare)
-
Configuring an Intelligent Reflecting Surface for Wireless Communications : Highlights from the 2021 IEEE Signal Processing Cup student competition [SP Competitions]
- 2022
-
Ingår i: IEEE signal processing magazine (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-5888 .- 1558-0792. ; 39:1, s. 126-131
-
Tidskriftsartikel (refereegranskat)abstract
- The shape of a surface determines how it interacts with wireless radio-frequency signals. Taking a homogenous metal plate as an example, we can bend and rotate it in different ways to make the incident wireless signal become diffusely or specularly reflected in the desired manner. The same effect can be electronically achieved by using an intelligent reflecting surface (IRS), which is a 2D array of metamaterials. By creating heterogeneous impedance variations over the surface, we can synthesize the reflection of a bent and rotated surface but without any mechanical manipulations.
|
|
| 8. |
- Björnson, Emil, et al.
(författare)
-
Multiobjective Signal Processing Optimization : The way to balance conflicting metrics in 5G systems
- 2014
-
Ingår i: IEEE signal processing magazine (Print). - : IEEE. - 1053-5888 .- 1558-0792. ; 31:6, s. 14-23
-
Tidskriftsartikel (refereegranskat)abstract
- The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream; first by delivering wireless access to voice communications, then by providing wireless data services, and recently by delivering a Wi-Fi-like experience with wide-area coverage and user mobility management. The support for high data rates has been the main objective in recent years [1], as seen from the academic focus on sum-rate optimization and the efforts from standardization bodies to meet the peak rate requirements specified in IMT-Advanced. In contrast, a variety of metrics/objectives are put forward in the technological preparations for fifth-generation (5G) networks: higher peak rates, improved coverage with uniform user experience, higher reliability and lower latency, better energy efficiency (EE), lower-cost user devices and services, better scalability with number of devices, etc. These multiple objectives are coupled, often in a conflicting manner such that improvements in one objective lead to degradation in the other objectives. Hence, the design of future networks calls for new optimization tools that properly handle the existence of multiple objectives and tradeoffs between them.
|
|
| 9. |
- Björnson, Emil, et al.
(författare)
-
Optimal Multiuser Transmit Beamforming : A Difficult Problem with a Simple Solution Structure
- 2014
-
Ingår i: IEEE signal processing magazine (Print). - : Institute of Electrical and Electronic Engineers. - 1053-5888 .- 1558-0792. ; 31:4, s. 142-148
-
Tidskriftsartikel (refereegranskat)abstract
- Transmit beamforming is a versatile technique for signal transmission from an array of antennas to one or multiple users [1]. In wireless communications, the goal is to increase the signal power at the intended user and reduce interference to nonintended users. A high signal power is achieved by transmitting the same data signal from all antennas but with different amplitudes and phases, such that the signal components add coherently at the user. Low interference is accomplished by making the signal components add destructively at nonintended users. This corresponds mathematically to designing beamforming vectors (that describe the amplitudes and phases) to have large inner products with the vectors describing the intended channels and small inner products with nonintended user channels.
|
|
| 10. |
- Björnson, Emil, et al.
(författare)
-
Reconfigurable Intelligent Surfaces : A signal processing perspective with wireless applications
- 2022
-
Ingår i: IEEE signal processing magazine (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-5888 .- 1558-0792. ; 39:2, s. 135-158
-
Tidskriftsartikel (refereegranskat)abstract
- Antenna array technology enables the directional transmission and reception of wireless signals for communication, localization, and sensing purposes. The signal processing algorithms that underpin it began to be developed several decades ago [1], but it was with the deployment of 5G wireless mobile networks that the technology became mainstream [2]. The number of antenna elements in the arrays of 5G base stations (BSs) and user devices can be measured on the order of hundreds and tens, respectively. As networks shift toward using higher-frequency bands, more antennas fit into a given aperture. For communication purposes, the arrays are harnessed to form beams in desired directions to improve the signal-to-noise ratio (SNR) and multiplex data signals in the spatial domain (to one or multiple devices) and to suppress interference by spatial filtering [2]. For localization purposes, these arrays are employed to maintain the SNR when operating across wider bandwidths, for angle-of-arrival estimation, and to separate multiple sources and scatterers [3]. The practical use of these features requires that each antenna array is equipped with well-designed signal processing algorithms.
|
|
