Analysis and design of energy harvesting wireless communication systems

Wireless-powered communication is an emerging technology for powering the large number of miniature devices of the future. In a wireless-powered communication system, low-power sensors extract energy from the incident wireless signals to power their operations such as information transmission, sensing or reception. Due to sporadic energy availability, however, such a system is fundamentally different from a traditionally-powered communication system. This dissertation investigates three distinct aspects of wireless-powered communications to get insights on the system operation. First, leveraging concepts from finite-length information theory, an analytical framework is developed for examining wireless-powered communications with short packets, i.e., in the finite blocklength regime. This is relevant as remotely-powered communications may entail short packets due to small payloads, low-latency requirements, or limited energy to support a longer transmission. Second, using a stochastic geometry framework, an analytical model is developed for characterizing the performance of wireless-powered communications in the millimeter wave (mmWave) band. The proposed model incorporates the key features of mmWave systems such as directional beamforming and sensitivity to building blockages. Finally, the power transfer efficiency and the energy efficiency of a wireless-powered communication system aided by massive MIMO is characterized. The broad goal of this dissertation is to better understand wireless-powered communications in the context of the emerging technologies for 5G.Electrical and Computer Engineerin

Efficient resource allocation for 5G hybrid wireless networks

This thesis explores three directions of energy-efficiency(EE) and spectral efficiency(SE) under 5G wireless networks. Firstly, we study the optimization of power control for the small (two-user) interference channel in which the terminals are time-switched between the signal-processing and energy-harvesting phases. Both energy harvesting and signal-processing processes are during the downlink. The objective is to maximize the sum-rate, subject to the minimum data and harvested energy constraints at the receivers, assuming a fixed time-switching coefficient. The key contribution is using a geometric approach that analyzes the feasible region governed by the constraints, which gives rise to the optimal power control solution. Another topic focuses on the performance analysis of two user association schemes for wireless power transfer (WPT) in heterogeneous networks (HetNets) massive multiple-input multiple-output (MIMO) antennas, downlink for the WPT in the first phase and uplink for wireless information transfer (WIT) in the second phase. The two user association schemes considered in the analysis are the Downlink received signal power (DRSP) based approach for maximizing the harvested energy; and the uplink received signal power (URSP) based approach for minimizing the uplink path loss. In the downlink, we adopt a low-complexity approach for massive MIMO power transfer to recharge users. Then we derive the average uplink achievable rate with the harvested energy. The last topic analyses a large-scale mmWave ad hoc network in the randomly located eavesdroppers area, where eavesdroppers can still intercept the confidential messages, since they may reside in the signal beam. This chapter explores the potential of physical layer security in mmWave ad hoc networks. Specifically, we characterize the impact of mmWave channel characteristics, random blockages, and antenna gains on the secrecy performance. For the special case of the uniform linear array (ULA), a tractable approach is proposed to evaluate the average achievable secrecy rate

Wireless Power Transfer in Massive MIMO Aided HetNets with User Association

This paper explores the potential of wireless power transfer (WPT) in massive multiple input multiple output (MIMO) aided heterogeneous networks (HetNets), where massive MIMO is applied in the macrocells, and users aim to harvest as much energy as possible and reduce the uplink path loss for enhancing their information transfer. By addressing the impact of massive MIMO on the user association, we compare and analyze two user association schemes. We adopt the linear maximal ratio transmission beam-forming for massive MIMO power transfer to recharge users. By deriving new statistical properties, we obtain the exact and asymptotic expressions for the average harvested energy. Then we derive the average uplink achievable rate under the harvested energy constraint.Comment: 36 pages, 11 figures, to appear in IEEE Transactions on Communication

Integrating Sensing, Communication, and Power Transfer: Multiuser Beamforming Design

In the sixth-generation (6G) networks, massive low-power devices are expected to sense environment and deliver tremendous data. To enhance the radio resource efficiency, the integrated sensing and communication (ISAC) technique exploits the sensing and communication functionalities of signals, while the simultaneous wireless information and power transfer (SWIPT) techniques utilizes the same signals as the carriers for both information and power delivery. The further combination of ISAC and SWIPT leads to the advanced technology namely integrated sensing, communication, and power transfer (ISCPT). In this paper, a multi-user multiple-input multiple-output (MIMO) ISCPT system is considered, where a base station equipped with multiple antennas transmits messages to multiple information receivers (IRs), transfers power to multiple energy receivers (ERs), and senses a target simultaneously. The sensing target can be regarded as a point or an extended surface. When the locations of IRs and ERs are separated, the MIMO beamforming designs are optimized to improve the sensing performance while meeting the communication and power transfer requirements. The resultant non-convex optimization problems are solved based on a series of techniques including Schur complement transformation and rank reduction. Moreover, when the IRs and ERs are co-located, the power splitting factors are jointly optimized together with the beamformers to balance the performance of communication and power transfer. To better understand the performance of ISCPT, the target positioning problem is further investigated. Simulations are conducted to verify the effectiveness of our proposed designs, which also reveal a performance tradeoff among sensing, communication, and power transfer.Comment: This paper has been submitted to IEEE for possible publicatio

Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer

This paper studies a wireless-energy-transfer (WET) enabled massive multiple-input-multiple-output (MIMO) system (MM) consisting of a hybrid data-and-energy access point (H-AP) and multiple single-antenna users. In the WET-MM system, the H-AP is equipped with a large number $M$ of antennas and functions like a conventional AP in receiving data from users, but additionally supplies wireless power to the users. We consider frame-based transmissions. Each frame is divided into three phases: the uplink channel estimation (CE) phase, the downlink WET phase, as well as the uplink wireless information transmission (WIT) phase. Firstly, users use a fraction of the previously harvested energy to send pilots, while the H-AP estimates the uplink channels and obtains the downlink channels by exploiting channel reciprocity. Next, the H-AP utilizes the channel estimates just obtained to transfer wireless energy to all users in the downlink via energy beamforming. Finally, the users use a portion of the harvested energy to send data to the H-AP simultaneously in the uplink (reserving some harvested energy for sending pilots in the next frame). To optimize the throughput and ensure rate fairness, we consider the problem of maximizing the minimum rate among all users. In the large-$M$ regime, we obtain the asymptotically optimal solutions and some interesting insights for the optimal design of WET-MM system. We define a metric, namely, the massive MIMO degree-of-rate-gain (MM-DoRG), as the asymptotic UL rate normalized by $\log(M)$. We show that the proposed WET-MM system is optimal in terms of MM-DoRG, i.e., it achieves the same MM-DoRG as the case with ideal CE.Comment: 15 double-column pages, 6 figures, 1 table, to appear in IEEE JSAC in February 2015, special issue on wireless communications powered by energy harvesting and wireless energy transfe

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin