Zhongding Lei

Bio: Zhongding Lei is an academic researcher from Institute for Infocomm Research Singapore. The author has contributed to research in topics: Multipath propagation & Iterative method. The author has an hindex of 28, co-authored 135 publications receiving 3324 citations. Previous affiliations of Zhongding Lei include Beijing Jiaotong University & National University of Singapore.

IEEE 802.22: The first cognitive radio wireless regional area network standard

Abstract: This article presents a high-level overview of the IEEE 802.22 standard for cognitive wireless regional area networks (WRANs) that is under development in the IEEE 802 LAN/MAN Standards Committee.

Coordinated Multipoint Transmission with Limited Backhaul Data Transfer

Abstract: When the joint processing technique is applied in the coordinated multipoint (CoMP) downlink transmission, the user data for each mobile station needs to be shared among multiple base stations (BSs) via backhaul. If the number of users is large, this data exchange can lead to a huge backhaul signaling overhead. In this paper, we consider a multi-cell CoMP network with multi-antenna BSs and single antenna users. The problem that involves the joint design of transmit beamformers and user data allocation at BSs to minimize the backhaul user data transfer is addressed, which is subject to given quality-of-service and per-BS power constraints. We show that this problem can be cast into an l0-norm minimization problem, which is NP-hard. Inspired by recent results in compressive sensing, we propose two algorithms to tackle it. The first algorithm is based on reweighted l1-norm minimization, which solves a series of convex l0-norm minimization problems. In the second algorithm, we first solve the l2-norm relaxation of the joint clustering and beamforming problem and then iteratively remove the links that correspond to the smallest transmit power. The second algorithm enjoys a faster solution speed and can also be implemented in a semi-distributed manner under certain assumptions. Simulations show that both algorithms can significantly reduce the user data transfer in the backhaul.

Method for selecting switched orthogonal beams for downlink diversity transmission

Abstract: A scheme for selecting two beams in a switched beam antenna system for providing downlink communications in a downlink channel, the switched beam antenna system providing uplink reception and downlink transmission is described The scheme involves selecting a pair of beams based on the uplink reception of the switched beam antenna system, and determining from the pair of beams a corresponding pair of orthogonal beams The scheme also involves providing the pair of orthogonal beams as a pair of transmit beams for the downlink transmission of the switched beam antenna system

An improved square-root algorithm for BLAST

Abstract: In this letter, an improved square-root algorithm for Bell Labs Layered Space-Time (BLAST) system is proposed. It speeds up the original square-root algorithm by 36% in terms of the number of multiplications and additions. Compared with the recursive algorithm, it requires only a 13.6% higher number of multiplications and a 38.9% higher number of additions. Since it uses unitary transformations to avoid the computation of any matrix inversion or "squaring" operation, it maintains the advantages of the square-root based algorithms that are numerically stable, robust, and hardware friendly.

A Comparative Study of QRD-M Detection and Sphere Decoding for MIMO-OFDM Systems

Abstract: We present a comparative study of two tree search based detection algorithms, namely, the M-algorithm combined with QR decomposition (QRD-M) and the sphere decoding (SD) algorithms, for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems First, we show that nodes ordering before and during the tree search are important for both algorithms With appropriate ordering, QRD-M can improve detection performance significantly and SD can reduce decoding complexity substantially Then we compare the implementation complexity of the two algorithms, in terms of the number of nodes required to search or the required number of multiplications to achieve maximum likelihood detection performance It is interesting to show that the average complexity of SD is lower than that of QRD-M, whereas the worst case complexity of SD is much higher than that of QRD-M

Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency

Abstract: Massive multiple-input multiple-output MIMO is one of themost promising technologies for the next generation of wirelesscommunication networks because it has the potential to providegame-changing improvements in spectral efficiency SE and energyefficiency EE. This monograph summarizes many years ofresearch insights in a clear and self-contained way and providesthe reader with the necessary knowledge and mathematical toolsto carry out independent research in this area. Starting froma rigorous definition of Massive MIMO, the monograph coversthe important aspects of channel estimation, SE, EE, hardwareefficiency HE, and various practical deployment considerations.From the beginning, a very general, yet tractable, canonical systemmodel with spatial channel correlation is introduced. This modelis used to realistically assess the SE and EE, and is later extendedto also include the impact of hardware impairments. Owing tothis rigorous modeling approach, a lot of classic "wisdom" aboutMassive MIMO, based on too simplistic system models, is shownto be questionable.

Advances in cognitive radio networks: A survey

Abstract: With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.

Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances

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]).

Fixed Point Theory

Abstract: Formally we have arrived at the middle of the book. So you may need a pause for recovering, a pause which we want to fill up by some fixed point theorems supplementing those which you already met or which you will meet in later chapters. The first group of results centres around Banach’s fixed point theorem. The latter is certainly a nice result since it contains only one simple condition on the map F, since it is so easy to prove and since it nevertheless allows a variety of applications. Therefore it is not astonishing that many mathematicians have been attracted by the question to which extent the conditions on F and the space Ω can be changed so that one still gets the existence of a unique or of at least one fixed point. The number of results produced this way is still finite, but of a statistical magnitude, suggesting at a first glance that only a random sample can be covered by a chapter or even a book of the present size. Fortunately (or unfortunately?) most of the modifications have not found applications up to now, so that there is no reason to write a cookery book about conditions but to write at least a short outline of some ideas indicating that this field can be as interesting as other chapters. A systematic account of more recent ideas and examples in fixed point theory should however be written by one of the true experts. Strange as it is, such a book does not seem to exist though so many people are puzzling out so many results.

Cognitive radio networking and communications: an overview

Abstract: Cognitive radio (CR) is the enabling technology for supporting dynamic spectrum access: the policy that addresses the spectrum scarcity problem that is encountered in many countries. Thus, CR is widely regarded as one of the most promising technologies for future wireless communications. To make radios and wireless networks truly cognitive, however, is by no means a simple task, and it requires collaborative effort from various research communities, including communications theory, networking engineering, signal processing, game theory, software-hardware joint design, and reconfigurable antenna and radio-frequency design. In this paper, we provide a systematic overview on CR networking and communications by looking at the key functions of the physical (PHY), medium access control (MAC), and network layers involved in a CR design and how these layers are crossly related. In particular, for the PHY layer, we will address signal processing techniques for spectrum sensing, cooperative spectrum sensing, and transceiver design for cognitive spectrum access. For the MAC layer, we review sensing scheduling schemes, sensing-access tradeoff design, spectrum-aware access MAC, and CR MAC protocols. In the network layer, cognitive radio network (CRN) tomography, spectrum-aware routing, and quality-of-service (QoS) control will be addressed. Emerging CRNs that are actively developed by various standardization committees and spectrum-sharing economics will also be reviewed. Finally, we point out several open questions and challenges that are related to the CRN design.