Uplink Phase Research Articles

NOMA-based energy efficient resource allocation in wireless energy harvesting sensor networks

Non Orthogonal Multiple Access (NOMA) and energy harvesting are two widely used concepts to improve the performance of Wireless Sensor Networks. In this paper, we consider a NOMA-based Wireless Energy Harvesting Sensor Network (WEHSN), in which all sensors harvest their energy from a Hybrid Access Point (HAP), and then, simultaneously transmit their information in NOMA-based protocol to the HAP, if their harvested energy are sufficient and they have data for transmission. We formulate the resource allocation as an optimization problem to maximize the energy efficiency, defined as system throughput per total energy consumption in the network, in which the total energy consumption is summation of energy consumption in downlink and uplink phases. The optimization problem constraints are the time scheduling parameters and the sensors’ transmission powers. To solve this maximization problem, we use the Dinkelbach method to convert it to the parametric form and then, we apply the Karush–Kuhn–Tucker (KKT) conditions in the parametric optimization problem to derive the closed form expression for optimization problem. We evaluate the performance of proposed scheme in relation to energy efficiency, throughput and total energy consumption, and we compare them with OFDMA and TDMA-based WEHSN method. The numerical results show that, NOMA-based WEHSN has better performance in compared with OFDMA and TDMA-based WEHSN. Also, the effect of different amount of data at the sensors has been considered in numerical result which shows that when the sensors always have data for transmission, the system has better performance in terms of energy efficiency and throughput but it has more total energy consumption in comparison to the situation that the sensors occasionally have data for transmission.

Achievable Rates and Resource Allocation for CDMA-Based Overlay Cognitive Radio With RF Energy Harvesting

This article introduced a cognitive wireless powered communication network with an uplink (UL) code-division multiple access (CDMA) scheme consisting of one hybrid access point (H-AP) and multiple energy harvesting secondary users (SUs), which are coexisted with a primary wireless network. The frame structure is coordinated through the two-phase harvest-then-transmit protocol. The energy-limited SUs first harvest wireless energy in the downlink phase and then transmit their information signals simultaneously to H-AP with the CDMA scheme in the UL phase. An overlay spectrum sharing model is also considered where H-AP has access to the primary transmitter's codebook and primary network's channel. Our goal is to maximize the sum-throughput optimization problem of SUs via jointly optimizing power and time allocation. The considered joint optimization problem is generally nonconvex due to coupled variables. As a solution, we first transform it into the equivalent convex form using proper variables and then we solve it using the convex optimization technique. The closed-form solutions for time and power allocations are given. We also confirm from various simulations’ results that our proposed CDMA scheme is superior to the conventional time-division multiple access schemes.

Development and Analysis of Mathematical Plunger Lift Models of the Low-Permeability Sulige Gas Field

The Sulige is a low-permeability tight gas sandstone field whose natural gas production has gradually declined with continuous development. The primary reason was that most of the wells in the field flew below their critical rates and liquids started to accumulate in the wellbore at different levels, which resulted in the production reduction due to the wellbore pressure decrease and back pressure increase on the produced gas. An artificial lift was required to remove the liquids from those wells. With the advantages such as simple installation and operation, low cost and high liquid-carrying capacity, the plunger lift has been proven effective in the Sulige Gas Field. In this paper, firstly, a series of mathematical models were developed to investigate plunger displacement and velocity in the uplink and downside phases, fluid leakage in the uplink phase, and the characteristics of tubing pressure and casing pressure in the uplink and pressure build-up phases. Then, taking well X1 and well X2 at Su 59 area of the gas field as an example, the established mathematical models were applied to estimate its tubing and casing pressure, plunger moving displacement and speed, fluid leakage during the uplink phase, and gas production during the plunger lift. Hence, the well production cycle operated by the maximum gas rate was optimized. This study provides a theoretical basis for the optimal design of plunger lift parameters and the improvement of gas production.

Two-Tier NOMA-Based Wireless Powered Communication Networks

In this article, we investigate two-tier nonorthogonal multiple access (NOMA)-based wireless powered communication networks. The considered network consists of a hybrid access point and two groups of users, namely near and far users. A near user and a far user are selected to form a NOMA pair, which harvest energy during the downlink phase and transmit information during the uplink phase. Specifically, we consider two cases of energy-transfer time and analyze the corresponding performance. We first analyze the performance of the case with fixed energy-transfer time and derive the exact expression for the ergodic rate. Due to the doubly near-far effect, the far user experiences poor performance. To address this issue, an adaptive energy-transfer time scheme is designed by maximizing the far user’s data rate, and the optimal solution is derived. To reduce the system complexity, a suboptimal solution is proposed, and the ergodic rate's exact expression is derived. Simulation results reveal that the suboptimal solution achieves near-optimal performance and has a lower computational complexity. Moreover, a one-tier NOMA network is set to be a benchmark, and numerical results show that the two-tier system outperforms the one-tier system significantly under the appropriate radius setting.

On channel estimation and spectral efficiency for cell‐free massive MIMO with multi‐antenna access points considering spatially correlated channels

AbstractChannel estimation (CE) and spectral efficiency (SE) are two processes that have a major influence on system performance, especially in a more practical channel scenario with spatially correlated Rayleigh fading. During this work, we address the uplink phase CE process and the SE for spatially correlated Rayleigh fading in a cell‐free (CF) massive multiple‐input multiple‐output (M‐MIMO) network and in the conventional M‐MIMO network operating under the time‐division duplex protocol. Since practical channels are correlated spatially with Rayleigh fading; thereby, this work addresses spatially correlated Rayleigh fading channels in both networks using a combination of the exponential correlation model with large‐scale variation across the array. Moreover, this work addresses the correlated and uncorrelated channels, where the correlated one is investigated using two array arrangements, namely, a uniform linear array (ULA) and a uniform planar array (UPA). For the two networks, the CE and SE are addressed using the minimum mean square error (MMSE) estimator and the MMSE combining vector, respectively. We propose a novel array design for CF M‐MIMO using the Kronecker product of a ULA arrangement, where each access point has a UPA arrangement. In other words, we propose the covariance matrix generated by the UPA arrangement for CF M‐MIMO using the Kronecker product of the covariance matrix generated by the ULA arrangement for CF M‐MIMO. Numerical results are presented to validate our theoretical expressions, where we evaluate the performance of the MMSE estimator and MMSE combining vector, respectively, using the normalized mean square error metric and the quantity of information effectively transmitted per second.

Message-Passing-Based Joint User Association and Time Allocation for Wireless Powered Communication Networks

This work develops a joint design of user association and time allocation for wireless powered communication networks. A harvest-then-transmit protocol is applied with base stations (BSs) transfer wireless energy to users in the first downlink phase. Then, the users utilize the harvested energy for their information transmission to the BS in the subsequent uplink phase. In this configuration, we employ a general <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> –fair utility to maximize the network throughput. In particular, the maximization of sum-rate, proportional fairness and minimum rate are investigated individually. We introduce a new message-passing based framework to provide an efficient distributed solution for the user association and optimize the time allocation between the downlink and uplink phase. To achieve this joint goal, each user selects a BS in a distributed manner to maximize the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> –fair utility. After identifying the user association, the time allocation is determined by an efficient line search technique. Simulation results show that the proposed algorithm outperforms existing approaches.

Energy-Efficient Massive MIMO for Federated Learning: Transmission Designs and Resource Allocations

This work proposes novel synchronous, asynchronous, and session-based designs for energy-efficient massive multiple-input multiple-output networks to support federated learning (FL). The synchronous design relies on strict synchronization among users when executing each FL communication round, while the asynchronous design allows more flexibility for users to save energy by using lower computing frequencies. The session-based design splits the downlink and uplink phases in each FL communication round into separate sessions. In this design, we assign users such that one of the participating users in each session finishes its transmission and does not join the next session. As such, more power and degrees of freedom will be allocated to unfinished users, resulting in higher rates, lower transmission times, and hence, higher energy efficiency. In all three designs, we use zero-forcing processing for both uplink and downlink, and develop algorithms that optimize user assignment, time allocation, power, and computing frequencies to minimize the energy consumption at the base station and users, while guaranteeing a predefined maximum execution time of each FL communication round.

On Channel Estimation for Rician Fading with the Phase-Shift in Cell-Free Massive MIMO System

Channel estimation (CE) is a crucial phase in wireless communication systems, especially in cell-free (CF) massive multiple input multiple output (M-MIMO) since it is a dynamic wireless network. Therefore, this work is introduced to study CE for the CF M-MIMO system in the uplink phase, wherein the performance of different estimators are evaluated, discussed, and compared in various situations. We assume the scenario in which each access point has prior knowledge of the channel statistics. The phase-aware-minimum mean square error (PA-MMSE) estimator, the non-phase-aware-MMSE (NPA-MMSE) estimator, and the least-squares estimator are the three estimators which are exploited in this work. Besides, we consider the Rician fading channel in which the line-of-sight path is realized with a phase-shift that models the users’ mobility where the considered phase-shift follows a uniform distribution. On the other hand, the mean-squared error metric is employed in order to evaluate the performance of each estimator, where an analytical and simulated result is provided for the PA-MMSE estimator and the NPA-MMSE estimator in order to assert our numerical results.

A Novel Pilot Spoofing Scheme via Intelligent Reflecting Surface Based on Statistical CSI

Pilot spoofing attack brings new challenges to physical layer secure transmission. However, this method will not work without any knowledge about the pilot sequence and active eavesdropping can be detected by constructing random pilot sequence. Intelligent reflecting surface (IRS), with the real-time programmable features for wireless channels, provides new possibilities for effective pilot spoofing. In this paper, the IRS is deployed near the legitimate users and the legitimate signal can always be passively reflected. Then the control strategy is embedded into the communication process under time-division duplex mode to assist eavesdroppers to conduct pilot spoofing. By setting different phase shifts at the IRS during the uplink phase and downlink phase, the channel reciprocity disappears, and thus secure beamforming vector is biased towards the eavesdropper. Furthermore, in order to overhear more information, the average secrecy rate minimization problem based on statistical channel state information is established by carefully designing the phase shifts, which is non-trivial to solve. With alternating optimization and Charnes-Cooper transformation technique, the original problem is transformed into convex form and a near optimal solution is achieved. Finally, simulation results show that our proposed scheme can pose serious secure threat without any energy footprint. What's more, if the IRS is not utilized by the internal users properly, it will bring more threat.

On channel estimation in cell‐free massive MIMO for spatially correlated channels with correlated shadowing under Rician fading

SummaryThis work addresses channel estimation (CE) in the uplink phase for a cell‐free massive multiple‐input multiple‐output system operating under the time division duplex protocol. Considering that, channels are spatially correlated under the Rician fading model, where the investigated model is composed of two components: deterministic and nondeterministic, with the deterministic component describing the line‐of‐sight paths and the nondeterministic component describing the non‐line‐of‐sight paths. Additionally, we dealt with correlated shadow fading that represents the most realistic situation. On the other hand, this work introduces a dynamic cooperation cluster framework in which the user is not served with the whole network ( i.e., all access points [APs]) but only the APs that present the best channel conditions regarding that user. In other words, this work proposes partial CE for each user because only APs with the best channel conditions are allowed to compute channel estimates. Consequently, we proposed partial channel estimators that perform the CE process with low complexity, namely, a partial minimum mean square error estimator and a partial element‐wise minimum mean square error estimator. In addition, a simple pilot assignment technique is proposed in order to reduce interference signals so that each user experiences low interference from other users. Furthermore, the computational complexity required by each estimator is derived, where it is represented by the number of complex multiplications that each estimator requires in each consistency block. Theoretical and simulated results are provided, where the performance of each estimator is evaluated and analyzed using the normalized mean‐square error metric.

Energy efficiency maximization strategy for Sink node in SWIPT-enabled sensor-cloud based on optimal stopping rules

Leveraging energy harvesting abilities in wireless network devices has emerged as an effective way to prolong the lifetime of energy constrained systems. The system gains are usually optimized by designing resource allocation algorithm appropriately. However, few works focus on the interaction that channel's time-vary characters make the energy transfer inefficiently. To address this, we propose a novel system operation sequence for sensor-cloud system where the Sinks provide SWIPT for sensor nodes opportunistically during downlink phase and collect the data transmitted from sensor nodes in uplink phase. Then, the energy-efficiency maximization problem of the Sinks is presented by considering the time costs and energy consumption of channel detection. It is proved that the formulated problem is an optimal stopping process with optimal stopping rules. An optimal energy-efficiency (OEE) algorithm is designed to obtain the optimal stopping rules for SWIPT. Finally, the simulations are performed based on the OEE algorithm compared with the other two strategies to verify the effectiveness and gains in improving the system efficiency.

Wirelessly Powered Cell-Free IoT: Analysis and Optimization

In this article, we propose a wirelessly powered Internet-of-Things (IoT) system based on the cell-free massive MIMO technology. In such a system, during the downlink phase, the sensors harvest radio-frequency (RF) energy emitted by the distributed access points (APs). During the uplink phase, sensors transmit data to the APs using the harvested energy. Collocated massive MIMO and small-cell IoT can be treated as special cases of cell-free IoT. We derive the tight closed-form lower bound on the amount of harvested energy, and the closed-form expression of SINR as the metrics of power transfer and data transmission, respectively. To improve energy efficiency, we jointly optimize the uplink and downlink power control coefficients to minimize the total transmit energy consumption while meeting the target SINRs. Extended simulation results show that cell-free IoT outperforms collocated massive MIMO and small-cell IoT in terms of both downlink and uplink 95% likely performances. Moreover, significant gains can be achieved by the proposed joint power control in terms of both per user throughput and energy consumption.

Time Allocation Optimization and Trajectory Design in UAV-Assisted Energy and Spectrum Harvesting Network

The scarcity of energy resources and spectrum resources has become an urgent problem with the exponential increase of communication devices. Meanwhile, unmanned aerial vehicle (UAV) is widely used to help communication network recently due to its maneuverability and flexibility. In this paper, we consider a UAV-assisted energy and spectrum harvesting (ESH) network to better solve the spectrum and energy scarcity problem, where nearby secondary users (SUs) harvest energy from the base station (BS) and perform data transmission to the BS, while remote SUs harvest energy from both BS and UAV but only transmit data to UAV to reduce the influence of near-far problem. We propose an unaligned time allocation scheme (UTAS) in which the uplink phase and downlink phase of nearby SUs and remote SUs are unaligned to achieve more flexible time schedule, including schemes (a) and (b) in remote SUs due to the half-duplex of energy harvesting circuit. In addition, maximum throughput optimization problems are formulated for nearby SUs and remote SUs respectively to find the optimal time allocation. The optimization problem can be divided into three cases according to the relationship between practical data volume and theoretical throughput to avoid the waste of time resource. The expressions of optimal energy harvesting time and data transmission time of each node are derived. Lastly, a successive convex approximation based iterative algorithm (SCAIA) is designed to get the optimal UAV trajectory in broadcast mode. Simulation results show that the proposed UTAS can achieve better performance than traditional time allocation schemes.

Enabling Full-Duplex and Energy Harvesting in Uplink and Downlink of Small-Cell Network Relying on Power Domain Based Multiple Access

In this article, we introduce a small-cell network operating in the context of heterogeneous cellular networks for both downlink (DL) and uplink (UL) by deploying three techniques of full-duplex transmission mode, energy harvesting, and power domain-based non-orthogonal multiple access (NOMA) schemes. Compared to the conventional half-duplex orthogonal multiple access (OMA) scheme that has been widely implemented in current wireless communication systems, the full-duplex (FD) NOMA relying on energy harvesting scheme has a great potential to further enhance the system performance in terms of connectivity capability, spectral efficiency and outage performance. In the proposed two-user small-cell relying on NOMA scheme, the small-cell base station first transfers an energy-bearing signal to serve the two users in the DL phase. Later, an energy harvesting technique is proceeded to encourage the strong user and the weak user to transmit their messages in the UL phase in a FD manner. However, one major challenge related to the FD strategy is the self-interference signal due to a signal leakage from the terminal’s output to the input. Besides that, the interference from macro-cell users is also main reason of degradation of the system performance. In this article, we derive analytical expressions to describe the system’s performance in terms of the outage probability and throughput. Moreover, extensive numerical simulations are performed to compare and highlight the performance of the proposed small-cell network with several practical scenarios.

Coverage Analysis for Energy-Harvesting UAV-Assisted mmWave Cellular Networks

In this paper, we jointly consider the downlink simultaneous wireless information and power transfer (SWIPT) and uplink information transmission in unmanned aerial vehicle (UAV)-assisted millimeter wave (mmWave) cellular networks, in which the user equipment (UE) locations are modeled using Poisson cluster processes (e.g., Thomas cluster processes or Matérn cluster processes). Distinguishing features of mmWave communications, such as different path loss models for line-of-sight (LOS) and non-LOS (NLOS) links and directional transmissions are taken into account. In the downlink phase, the association probability, and energy coverages of different tier UAVs and ground base stations (GBSs) are investigated. Moreover, we define a successful transmission probability to jointly present the energy and signal-to-interference-plus-noise ratio (SINR) coverages and provide general expressions. In the uplink phase, we consider the scenario that each UAV receives information from its own cluster member UEs. We determine the Laplace transform of the interference components and characterize the uplink SINR coverage. In addition, we formulate the average uplink throughput, with the goal to identify the optimal time division multiplexing between the donwlink and uplink phases. Through numerical results we investigate the impact of key system parameters on the performance. We show that the network performance is improved when the cluster size becomes smaller. In addition, we analyze the optimal height of UAVs, optimal power splitting value and optimal time division multiplexing that maximizes the network performance.

Detection of Eavesdropping Attack in UAV-Aided Wireless Systems: Unsupervised Learning With One-Class SVM and K-Means Clustering

A wireless relaying system in the presence of an active eavesdropper is considered. The system is assumed to use an unmanned aerial vehicle (UAV) as a relay and the uplink phase is for authentication. The active eavesdropper is assumed to sneak into the system by attacking the UAV during the process of authentication. To detect the eavesdropping attacks, we consider building predictive models with one-class support vector machines (OC-SVM) and K-means clustering. To prepare datasets for training predictive models, we propose a framework for creating the features of testing data from wireless signals and another framework for generating training data. Our results show the superiority of OC-SVM over K-means in terms of stability, while K-means clustering is better when the eavesdropper uses high power in transmission.

Physical Layer Security in &lt;inline-formula&gt; &lt;tex-math notation="LaTeX"&gt;$K$ &lt;/tex-math&gt; &lt;/inline-formula&gt;-Tier Heterogeneous Cellular Networks Over Nakagami-&lt;inline-formula&gt; &lt;tex-math notation="LaTeX"&gt;$m$ &lt;/tex-math&gt; &lt;/inline-formula&gt; Channel During Uplink and Downlink Phases

In this paper, we study the physical layer security performance under K-tier heterogeneous cellular network during both downlink and uplink phases. Especially, Nakagami-m fading is used to capture the characteristics of line-of-sight (LoS) propagation. Using stochastic geometry tool, tractable expressions of connection probability are derived accordingly. Upper-bound expression of secrecy probability is derived through only considering the closest eavesdropper, whose rationality is validated theoretically. While lowerbound expression of secrecy probability is derived through using Jensen's inequality. Moreover, we demonstrate the effects of parameter setting upon network connection and secrecy performances through numerical simulation. For example, Rayleigh fading and LoS scenario (an extreme Rician case) can be regarded as special cases of this paper through properly setting m 0 value. Connection probability is insensitive to BS density during downlink phases, while it is an increasing function of BS density during the uplink phase. We also find that connection probability is an increasing function of m 0 value. Secrecy probability is insensitive to m 0 value, while it is an increasing function of BS density during both downlink and uplink phases.

Orthogonally Precoded Massive MIMO for High Mobility Scenarios

Massive multiple-input multiple-output (MIMO) systems are of high interest for ultra-reliable low-latency communication (URLLC) links. They provide channel hardening, i.e. reduced channel variations, due to the large number of transmit antennas which exploit spatial diversity by beam-forming. Massive MIMO requires channel state information (CSI) on the base station side. For time-varying vehicular communication channels the CSI acquired during the uplink phase will be outdated for the following downlink phase, leading to reduced spatial channel hardening. We investigate a combination of massive MIMO with general orthogonal precoding (OP) to compensate this effect. OP uses two-dimensional precoding sequences in the time-frequency domain and provides channel hardening by exploiting time- and frequency diversity. We show that the combination of massive MIMO and OP is beneficial for time-varying communication channels. While the spatial channel hardening of massive MIMO decreases, the time-frequency channel hardening of OP increases with larger time-variance of the communication channel. An iterative receiver algorithm for massive MIMO with OP as well as a detailed analysis of the channel hardening effect is presented. We demonstrate a BER reduction by more than one order of magnitude for a velocity of 50 km/h = 16.6 m/s using the orthogonal frequency division multiplexing (OFDM) based 5G new radio (NR) physical layer.

Throughput of Wireless-Powered Based Multiuser System with Large-Scale Distributed Antennas

This paper investigates energy harvesting based multiuser system with large-scale distributed antennas, where a large number of remote antenna units (RAUs) are evenly separated across multiple circles. An efficient wireless energy and information transmission protocol is proposed. To save the signaling and the radio frequency chains overheads, the RAU with the shortest distance towards a user equipment (UE) is employed for the downlink wireless energy transfer (WET). In the uplink phase, we analyze the probability of wireless information transmission (WIT) of UEs. Then, linear zero-forcing detection and minimum-mean-square error are used to separate the data information among all the UEs that satisfy the requirement of WIT. The asymptotic throughput for an arbitrary UE is derived in closed-form. The time fraction used for the WET is optimized through maximizing the asymptotic throughput. Numerical and simulation results are given to verify the theoretical analysis, and bring to light the time fraction planning and the RAUs deployment for the system.

Sum-Rate Maximization Methods for Wirelessly Powered Communication Networks in Interference Channels

In this paper, we study a wireless powered communication network (WPCN) in a general $N$ -user interference channel (IFC), where a hybrid access-point (H-AP) in each cell supports its corresponding user. In this multi-cell environment, the H-AP first sends the energy signal to charge users in the downlink (DL) phase, while in the subsequent uplink (UL) phase, each user transmits its information signal to the corresponding H-AP utilizing the previously harvested energy. For the WPCN in this IFC scenario, cross-link interference occurs due to asynchronous time allocation of the DL and the UL among $N$ cells which significantly affects the overall performance. To handle the interference issue efficiently, we jointly optimize the DL and UL time allocation of each cell as well as the transmit power allocation at the H-APs and the users so that the weighted sum-rate of UL information transmission is maximized. To tackle non-convexity of the weighted sum-rate maximization problem, we propose an iterative algorithm where the time allocation and the transmit power are updated based on the weighted minimum mean square error criteria and the gradient projection method, respectively. Furthermore, we consider two simple protocols where the DL time allocation of each cell is synchronized and present resource allocation method, respectively. In simulation results, we verify that the proposed algorithm for the asynchronous protocol outperforms conventional schemes.