Chenzi Jiang

Bio: Chenzi Jiang is an academic researcher from University of Delaware. The author has contributed to research in topics: Precoding & Beamforming. The author has an hindex of 7, co-authored 10 publications receiving 1101 citations.

A survey of energy-efficient wireless communications

Abstract: Reducing energy consumption in wireless communications has attracted increasing attention recently. Advanced physical layer techniques such as multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM), cognitive radio, network coding, cooperative communication, etc.; new network architectures such as heterogeneous networks, distributed antennas, multi-hop cellulars, etc.; as well as radio and network resource management schemes such as various cross-layer optimization algorithms, dynamic power saving, multiple radio access technologies coordination, etc. have been proposed to address this issue. In this article, we overview these technologies and present the state-of-the-art on each aspect. Some challenges that need to be solved in the area are also described.

Antenna Selection for Energy-Efficient MIMO Transmission

Abstract: In previous works on multiple-input multiple-output (MIMO) antenna selection, it is usually assumed that the transmit power and the number of active antennas is fixed and the antenna subset is selected to maximize the capacity. In this paper, we jointly optimize the transmit power, the number of active antennas, and the antenna subsets at the transmitter and receiver to maximize the energy efficiency. The optimal solution can be obtained by exhaustive search; suboptimal algorithms are also developed to reduce the complexity. Simulation results show that antenna selection can improve the energy efficiency significantly.

Energy-efficient transmission for MIMO interference channels

Abstract: In previous work on multiple-input multiple-output (MIMO) interference channels, it has usually been assumed that the transmit power at each transmitter is fixed. Power is equally allocated among different streams, and MIMO beamforming is applied only to mitigate interference and improve the system performance. In this paper, we design the transmit powers, power allocation among streams, and beamforming matrices jointly for each transmit-receive pair (link) to maximize the energy efficiency in a MIMO interference channel. Centralized and decentralized energy-efficient beamforming algorithms are developed based on global and local channel state information (CSI) at each transmitter, respectively. A distributed beamforming algorithm that combines minimum mean squared error (MMSE) and two power allocation algorithms is also developed; this algorithm only requires the information of the desired link. The decentralized and distributed schemes can be combined with scheduling to achieve good performance when the interference among links cannot be canceled. Simulation results show that the proposed algorithms can achieve good performance close to the upper bound, and the decentralized algorithm can perform as well as the centralized scheme. The distributed algorithm is suboptimal, but requires much less signaling. In addition, we show that the decentralized and distributed schemes result in a fairer allocation than the centralized approach.

Downlink energy-efficient multiuser beamforming with individual SINR constraints

Abstract: Transmit beamforming in multiuser wireless systems is typically designed to minimize the transmit power subject to signal-to-interference-plus-noise ratio (SINR) constraints, or maximize the SINR with a total transmit power constraint. However, transmit power is only one part of the total power consumption during the transmission. Circuit power, incurred by devices and signal processing, also needs to be taken into account. In this paper, we consider energy efficiency as the objective function, which can be defined as the number of information bits per unit energy usage. We design the beamforming vectors to maximize energy efficiency with individual SINR constraints for each user. A zero-gradient-based energy-efficient multiuser downlink beamforming algorithm is developed which optimizes the normalized beamforming vectors and the transmitted powers jointly for each user. A simpler method of power allocation among users, with the normalized beamforming vectors given, is also described when the interference among users can be eliminated. Based on this power allocation approach, an additional iterative beamforming algorithm is presented. Simulation results show the advantages of the proposed energy-efficient multiuser beamforming algorithms over traditional downlink beamforming schemes.

Energy-efficient transmission for MIMO interference channels

Abstract: In the previous works on multiple-input multiple-output (MIMO) interference channels, it is usually assumed that the transmit power is fixed and only MIMO beamforming is applied to mitigate interference. In this paper, we design the transmit powers and beamforming vectors jointly for each transmit-receive pairs (links) to maximize the energy efficiency in MIMO interference channels. Centralized and decentralized energy-efficient beamforming algorithms are developed based on global and local channel state information (CSI) at each transmitter, respectively. The decentralized scheme can be combined with scheduling to achieve good performance when the interference among links cannot be canceled. Simulation results show that the proposed algorithms can achieve good performance, close to the upper bound, and the decentralized algorithm can perform as well as the centralized scheme.

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.

Is the Random Access Channel of LTE and LTE-A Suitable for M2M Communications? A Survey of Alternatives

Abstract: The 3GPP has raised the need to revisit the design of next generations of cellular networks in order to make them capable and efficient to provide M2M services. One of the key challenges that has been identified is the need to enhance the operation of the random access channel of LTE and LTE-A. The current mechanism to request access to the system is known to suffer from congestion and overloading in the presence of a huge number of devices. For this reason, different research groups around the globe are working towards the design of more efficient ways of managing the access to these networks in such circumstances. This paper aims to provide a survey of the alternatives that have been proposed over the last years to improve the operation of the random access channel of LTE and LTE-A. A comprehensive discussion of the different alternatives is provided, identifying strengths and weaknesses of each one of them, while drawing future trends to steer the efforts over the same shooting line. In addition, while existing literature has been focused on the performance in terms of delay, the energy efficiency of the access mechanism of LTE will play a key role in the deployment of M2M networks. For this reason, a comprehensive performance evaluation of the energy efficiency of the random access mechanism of LTE is provided in this paper. The aim of this computer-based simulation study is to set a baseline performance upon which new and more energy-efficient mechanisms can be designed in the near future.

Energy Efficiency in Wireless Networks via Fractional Programming Theory

Abstract: This monograph presents a unified framework for energy efficiency maximization in wireless networks via fractional programming theory. The definition of energy efficiency is introduced, with reference to single-user and multi-user wireless networks, and it is observed how the problem of resource allocation for energy efficiency optimization is naturally cast as a fractional program. An extensive review of the state-of-the-art in energy efficiency optimization by fractional programming is provided, with reference to centralized and distributed resource allocation schemes. A solid background on fractional programming theory is provided. The key-notion of generalized concavity is presented and its strong connection with fractional functions described. A taxonomy of fractional problems is introduced, and for each class of fractional problem, general solution algorithms are described, discussing their complexity and convergence properties. The described theoretical and algorithmic framework is applied to solve energy efficiency maximization problems in practical wireless networks. A general system and signal model is developed which encompasses many relevant special cases, such as one-hop and two-hop heterogeneous networks, multi-cell networks, small-cell networks, device-to-device systems, cognitive radio systems, and hardware-impaired networks, wherein multiple-antennas and multiple subcarriers are possibly employed. Energy-efficient resource allocation algorithms are developed, considering both centralized, cooperative schemes, as well as distributed approaches for self-organizing networks. Finally, some remarks on future lines of research are given, stating some open problems that remain to be studied. It is shown how the described framework is general enough to be extended in these directions, proving useful in tackling future challenges that may arise in the design of energy-efficient future wireless networks.

Design Guidelines for Spatial Modulation

Abstract: A new class of low-complexity, yet energy-efficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely, the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO), has emerged. These systems are capable of exploiting the spatial dimensions (i.e., the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication while relying on a single-Radio Frequency (RF) chain. Moreover, SM may be also viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/cooperative protocol design issues, and on their meritorious variants.

User Association in 5G Networks: A Survey and an Outlook

Abstract: The fifth generation (5G) mobile networks are envisioned to support the deluge of data traffic with reduced energy consumption and improved quality of service (QoS) provision. To this end, key enabling technologies, such as heterogeneous networks (HetNets), massive multiple-input multiple-output (MIMO), and millimeter wave (mmWave) techniques, have been identified to bring 5G to fruition. Regardless of the technology adopted, a user association mechanism is needed to determine whether a user is associated with a particular base station (BS) before data transmission commences. User association plays a pivotal role in enhancing the load balancing, the spectrum efficiency, and the energy efficiency of networks. The emerging 5G networks introduce numerous challenges and opportunities for the design of sophisticated user association mechanisms. Hence, substantial research efforts are dedicated to the issues of user association in HetNets, massive MIMO networks, mmWave networks, and energy harvesting networks. We introduce a taxonomy as a framework for systematically studying the existing user association algorithms. Based on the proposed taxonomy, we then proceed to present an extensive overview of the state-of-the-art in user association algorithms conceived for HetNets, massive MIMO, mmWave, and energy harvesting networks. Finally, we summarize the challenges as well as opportunities of user association in 5G and provide design guidelines and potential solutions for sophisticated user association mechanisms.