Behrouz Farhang-Boroujeny

Bio: Behrouz Farhang-Boroujeny is an academic researcher from University of Utah. The author has contributed to research in topics: Orthogonal frequency-division multiplexing & Filter bank. The author has an hindex of 39, co-authored 297 publications receiving 8101 citations. Previous affiliations of Behrouz Farhang-Boroujeny include IBM & National University of Singapore.

OFDM Versus Filter Bank Multicarrier

Abstract: As of today, orthogonal frequency division multiplexing (OFDM) has been the dominant technology for broadband multicarrier communications. However, in certain applications such as cognitive radios and uplink of multiuser multicarrier systems, where a subset of subcarriers is allocated to each user, OFDM may be an undesirable solution. In this article, we address the shortcomings of OFDM in these and other applications and show that filter bank multicarrier (FBMC) could be a more effective solution. Although FBMC methods have been studied by a number of researchers, and some even before the invention of OFDM, only recently has FBMC been seriously considered by a few standard committees.

Adaptive Filters Theory and Applications

Abstract: From the Publisher: Adaptive filtering is an advanced and growing field in signal processing. A filter is a transmission network used in electronic circuits for the selective enhancement or reduction of specified components of an input signal. Filtering is achieved by selectively attenuating those components of the input signal which are undesired, relative to those which it is desired to enhance. This comprehensive book is both a valuable student resource and a useful technical reference for signal processing engineers in industry. The author is experienced in teaching graduates and practicing engineers and the text offers good theoretical coverage complemented by plenty of application examples.

Filter Bank Spectrum Sensing for Cognitive Radios

Abstract: The primary task in any cognitive radio (CR) network is to dynamically explore the radio spectrum and reliably determine portion(s) of the frequency band that may be used for the communication link(s). Accordingly, each CR node in the network has to be equipped with a spectrum analyzer. In this paper, we propose filter banks as a tool for spectrum sensing in CR systems. Various choices of filter banks are suggested and their performance are evaluated theoretically and through numerical examples. Moreover, the proposed spectrum analyzer is contrasted with the Thomson's multitaper (MT) method - a method that in the recent literature has been recognized as the best choice for spectrum sensing in CR systems. A novel derivation of the MT method that facilitates our comparisons as well as reveals an important aspect of the MT method that has been less emphasized in the recent literature is also presented.

Multicarrier communication techniques for spectrum sensing and communication in cognitive radios

Abstract: In this tutorial article we review different multicarrier communication methods for the physical layer of cognitive radio systems. There, secondary users need to dynamically and reliably determine spectral holes, and transmit data in these resources without interfering with other parts of the frequency band. To satisfy the first, each SU has to be equipped with a spectrum analyzer. To satisfy the second, it is widely accepted that a multicarrier modulation technique should be adopted. Moreover, to maximize efficiency, it has been recognized that the side-lobes of each subcarrier band must be minimized. Much of the attention in the present literature emphasizes on the use of conventional OFDM, exploiting the fact that fast Fourier transform (FFT) as part of the OFDM modulator can also be used for channel sensing. Herein, we discuss the performance of OFDM, and also introduce filterbanks for multicarrier communication and spectral analysis in a CR setting. Moreover, the multitaper method has been proposed as an effective method for spectrum analysis. Our article provides an insight into the pros and cons of these technologies.

OFDM Inspired Waveforms for 5G

Abstract: As the standardization activities are being formed to lay the foundation of 5G wireless networks, there is a common consensus on the need to replace the celebrated orthogonal frequency division multiplexing (OFDM) by a more effective air interface that better serves the challenging needs of 5G. To this end, in the recent past, a number of new waveforms have been introduced in the literature. Interestingly, and at the same time not surprising, these methods share a common fundamental principle with OFDM: each data packet is made up of a number of complex-valued sinusoidals (pure tones) that are modulated by the information symbols. In this tutorial article, we build a common framework based on the said OFDM principle and derive these new waveforms from this point of view. This derivation provides a new perspective that facilitates straightforward understanding of channel equalization and the application of these new waveforms to multiple-input multiple-output channels. It also facilitates derivation of new structures for more efficient synthesis/analysis of these waveforms than those that have been reported in the literature.

What Will 5G Be

Abstract: What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

Abstract: Multiple-input multiple-output (MIMO) technology is maturing and is being incorporated into emerging wireless broadband standards like long-term evolution (LTE) [1]. For example, the LTE standard allows for up to eight antenna ports at the base station. Basically, the more antennas the transmitter/receiver is equipped with, and the more degrees of freedom that the propagation channel can provide, the better the performance in terms of data rate or link reliability. More precisely, on a quasi static channel where a code word spans across only one time and frequency coherence interval, the reliability of a point-to-point MIMO link scales according to Prob(link outage) ` SNR-ntnr where nt and nr are the numbers of transmit and receive antennas, respectively, and signal-to-noise ratio is denoted by SNR. On a channel that varies rapidly as a function of time and frequency, and where circumstances permit coding across many channel coherence intervals, the achievable rate scales as min(nt, nr) log(1 + SNR). The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time [2].

Scaling up MIMO: Opportunities and Challenges with Very Large Arrays

Abstract: This paper surveys recent advances in the area of very large MIMO systems. With very large MIMO, we think of systems that use antenna arrays with an order of magnitude more elements than in systems being built today, say a hundred antennas or more. Very large MIMO entails an unprecedented number of antennas simultaneously serving a much smaller number of terminals. The disparity in number emerges as a desirable operating condition and a practical one as well. The number of terminals that can be simultaneously served is limited, not by the number of antennas, but rather by our inability to acquire channel-state information for an unlimited number of terminals. Larger numbers of terminals can always be accommodated by combining very large MIMO technology with conventional time- and frequency-division multiplexing via OFDM. Very large MIMO arrays is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation. The ultimate vision of very large MIMO systems is that the antenna array would consist of small active antenna units, plugged into an (optical) fieldbus.

Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations

Abstract: Array processing involves manipulation of signals induced on various antenna elements. Its capabilities of steering nulls to reduce cochannel interferences and pointing independent beams toward various mobiles, as well as its ability to provide estimates of directions of radiating sources, make it attractive to a mobile communications system designer. Array processing is expected to play an important role in fulfilling the increased demands of various mobile communications services. Part I of this paper showed how an array could be utilized in different configurations to improve the performance of mobile communications systems, with references to various studies where feasibility of apt array system for mobile communications is considered. This paper provides a comprehensive and detailed treatment of different beam-forming schemes, adaptive algorithms to adjust the required weighting on antennas, direction-of-arrival estimation methods-including their performance comparison-and effects of errors on the performance of an array system, as well as schemes to alleviate them. This paper brings together almost all aspects of array signal processing.