Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Orbital Angular Momentum Waves: Generation, Detection and Emerging Applications

Orbital angular momentum (OAM) has aroused a widespread interest in many fields, especially in telecommunications due to its potential for unleashing new capacity in the severely congested spectrum of commercial communication systems. Beams carrying OAM have a helical phase front and a field strength with a singularity along the axial center, which can be used for information transmission, imaging and particle manipulation. The number of orthogonal OAM modes in a single beam is theoretically infinite and each mode is an element of a complete orthogonal basis that can be employed for multiplexing different signals, thus greatly improving the spectrum efficiency. In this paper, we comprehensively summarize and compare the methods for generation and detection of optical OAM, radio OAM and acoustic OAM. Then, we represent the applications and technical challenges of OAM in communications, including free-space optical communications, optical fiber communications, radio communications and acoustic communications. To complete our survey, we also discuss the state of art of particle manipulation and target imaging with OAM beams

Adaptive Beamforming and Adaptive Modulation-Assisted Network Performance of Multiuser Detection-Aided FDD and TDD CDMA Systems

The network performance of a frequency division duplex and time division duplex (TDD) code division multiple access (CDMA)-based system is investigated using system parameters similar to those of the Universal Mobile Telecommunication System. The new call blocking and call dropping probabilities, the probability of low-quality access, and the required average transmit power are quantified both with and without adaptive antenna arrays (AAAs), as well as when subjected to shadow fading. In some of the scenarios investigated, the system’s user capacity is doubled with the advent of adaptive antennas. The employment of adaptive modulation techniques in conjunction with AAAs resulted in further significant network capacity gains. This is particularly so in the context of TDD CDMA, where the system’s capacity becomes poor without adaptive antennas and adaptive modulation owing to the high base station (BS) to BS interference inflicted as a consequence of potentially using all time slots in both the uplink and downlink of the emerging wireless Internet. Index Terms—Adaptive beamforming, adaptive modulation, code division multiple access (CDMA) systems, Universal Mobile Telecommunication System Terrestrial Radio Access (UTRA), wireless network performance

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table

Turbo-Coded Adaptive Modulation Versus Space-Time Trellis Codes for Transmission over Dispersive Channels

Decision feedback equalizer (DFE)-aided turbocoded wideband adaptive quadrature amplitude modulation (AQAM) is proposed, which is capable of combating the temporal channel quality variation of fading channels. A procedure is suggested for determining the AQAM switching thresholds and the specific turbo-coding rates capable of maintaining the target bit-error rate while aiming for achieving a highly effective bits per symbol throughput. As a design alternative, we also employ multiple-input/multiple-output DFE-aided space–time trellis codes, which benefit from transmit diversity and hence reduce the temporal channel quality fluctuations. The performance of both systems is characterized and compared when communicating over the COST 207 typical urban wideband fading channel. It was found that the turbo-coded AQAM scheme outperforms the two-transmitter space–time trellis coded system employing two receivers; although, its performance is inferior to the space–time trellis coded arrangement employing three receivers. Index Terms—Coded adaptive modulation, dispersive channels, space–time trellis codes

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig