There is a growing interest in energy efficient or so-called "green" wireless communication to reduce the energy consumption in cellular networks. Since today's wireless terminals are typically equipped with multiple network access interfaces such as Bluetooth, Wi-Fi, and cellular networks, this paper investigates user terminals cooperating with each other in transmitting their data packets to the base station (BS), by exploiting the multiple network access interfaces, called inter-network cooperation. We also examine the conventional schemes without user cooperation and with intra-network cooperation for comparison. Given target outage probability and data rate requirements, we analyze the energy consumption of conventional schemes as compared to the proposed inter-network cooperation by taking into account both physical-layer channel impairments (including path loss, fading, and thermal noise) and upper-layer protocol overheads. It is shown that distances between different network entities (i.e., user terminals and BS) have a significant influence on the energy efficiency of proposed inter-network cooperation scheme. Specifically, when the cooperating users are close to BS or the users are far away from each other, the inter-network cooperation may consume more energy than conventional schemes without user cooperation or with intra-network cooperation. However, as the cooperating users move away from BS and the inter-user distance is not too large, the inter-network cooperation significantly reduces the energy consumption over conventional schemes.
In this letter, we consider an intelligent reflecting surface (IRS)-aided wireless relaying system, where a decode-and-forward relay (R) is employed to forward data from a source (S) to a destination (D), aided by M passive reflecting elements. We consider two practical IRS deployment strategies, namely, single-IRS deployment where all reflecting elements are mounted on one single IRS that is deployed near S, R, or D, and multi-IRS deployment where the reflecting elements are allocated over three separate IRSs which are deployed near S, R, and D, respectively. Under the line-of-sight (LoS) channel model, we characterize the capacity scaling orders with respect to an increasing M for the IRS-aided relay system with different IRS deployment strategies. For single-IRS deployment, we show that deploying the IRS near R achieves the highest capacity as compared to that near S or D. While for multi-IRS deployment, we propose a practical cooperative IRS passive beamforming design which is analytically shown to achieve a larger capacity scaling order than the single-IRS deployment (i.e., near R or S/D) when M is sufficiently large. Numerical examples are provided, which validate our theoretical results.
Radio-frequency (RF) enabled wireless energy transfer (WET), as a promising solution to provide cost-effective and reliable power supplies for energy-constrained wireless networks, has drawn growing interests recently. To overcome the significant propagation loss over distance, employing multi-antennas at the energy transmitter (ET) to more efficiently direct wireless energy to desired energy receivers (ERs), termed energy beamforming, is an essential technique for enabling WET. However, the achievable gain of energy beamforming crucially depends on the available channel state information (CSI) at the ET, which needs to be acquired practically. In this paper, we study the design of an efficient channel acquisition method for a point-to-point multiple-input multiple-output (MIMO) WET system by exploiting the channel reciprocity, i.e., the ET estimates the CSI via dedicated reverse-link training from the ER. Considering the limited energy availability at the ER, the training strategy should be carefully designed so that the channel can be estimated with sufficient accuracy, and yet without consuming excessive energy at the ER. To this end, we propose to maximize the net harvested energy at the ER, which is the average harvested energy offset by that used for channel training. An optimization problem is formulated for the training design over MIMO Rician fading channels, including the subset of ER antennas to be trained, as well as the training time and power allocated. Closed-form solutions are obtained for some special scenarios, based on which useful insights are drawn on when training should be employed to improve the net transferred energy in MIMO WET systems.
This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users periodically. The UAV employs the radio frequency (RF) wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send independent information to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory design, jointly with the wireless resource allocation optimization, to maximize the system throughput. In particular, we aim to maximize the uplink common (minimum) throughput among all ground users over a finite UAV's flight period, subject to its maximum speed constraint and the users' energy neutrality constraints. The resulted problem is nonconvex and thus difficult to be solved optimally. To tackle this challenge, we first consider an ideal case without the UAV's maximum speed constraint, and obtain the optimal solution to the relaxed problem. The optimal solution shows that the UAV should successively hover above a finite number of ground locations for downlink WPT, as well as above each of the ground users for uplink communication. Next, we consider the general problem with the UAV's maximum speed constraint. Based on the above multilocation-hovering solution, we first propose an efficient successive hover-and-fly trajectory design, jointly with the downlink and uplink wireless resource allocation, and then propose a locally optimal solution by applying the techniques of alternating optimization and successive convex programming (SCP). Numerical results show that the proposed UAV-enabled WPCN achieves significant throughput gains over the conventional WPCN with fixed-location AP.
We observe deterministic chaos in a simple network of electronic logic gates that are not regulated by a clocking signal. The resulting power spectrum is ultrawide band, extending from dc to beyond 2 GHz. The observed behavior is reproduced qualitatively using an autonomously updating Boolean model with signal propagation times that depend on the recent history of the gates and filtering of pulses of short duration, whose presence is confirmed experimentally. Electronic Boolean chaos may find application as an ultrawide-band source of radio waves.
In order to sample precisely the state transition time when simulating non-Markovian system,a new sampling method named Approximate Sampling for Residual Distribution(ASRD) method is put forward,in which several uniform distributions are used to approach general residual life distributions. The approach-coefficient d is used to adjust sampling precision and efficiency. Another method named Forced Transitions(FT) based ASRD(FT-ASRD) simulation method is brought forward to simulate high-reliable non-Markovian systems. FT-ASRD uses FT strategy to get the unreliability parameter. Several examples show that,when 5≤d≤10,FT-ASRD is more efficient and has lower relative error compared with crude simulation methods.
This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users periodically. The UAV employs the radio frequency (RF) wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send independent information to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via periodic trajectory design, jointly with the transmission resource allocation optimization, to improve the system performance. In particular, we aim to maximize the uplink common (minimum) throughput among all ground users over a finite UAV's flight period, subject to its maximum speed constraint and the users' energy neutrality constraints. The resulting problem is non-convex and thus difficult to be solved optimally. To tackle this challenge, we first consider an ideal case without the maximum UAV speed constraint, and obtain the optimal solution to the relaxed problem. The optimal solution shows that the UAV should successively hover above a finite number of ground locations for downlink WPT, as well as above each of the ground users for uplink communication. Next, based on the above multi-location-hovering solution, we propose a successive hover-and-fly trajectory, jointly with the downlink and uplink power allocations, to find an efficient suboptimal solution to the problem with the maximum UAV speed constraint. Numerical results show that the proposed UAV-enabled WPCN achieves significant common throughput gain over the conventional WPCN with a fixed-location AP.
In this communication, we introduce a mode-controlled ground radiation antenna comprised of a resonance-controlled ground plane and a nonradiating feeding slot for wideband applications in mobile devices. A 110 mm × 50 mm ground plane for 850-MHz operation is studied as a test case. The resonant frequency of the ground plane is lowered by adding metal loads at the top and bottom intended for strong coupling with a miniature feeding slot located at one end, so that the ground plane is resonant as a half wavelength dipole-type radiator. The metal loads can be the structures of strips, plates, or wires, and they can take the form of broken metal rims or frames with cuts or gaps in smartphones. In addition, the metal loads are connected to the ends of the ground plane by lumped elements (inductors and/or capacitors) for easy control of the resonance mode and compact design. Equivalent circuit model and corresponding equations are provided for theoretical analysis. The impedance bandwidth based on 3:1 VSWR is 210 MHz (from 760 to 970 MHz), with an average efficiency of 77%. Geometrical characteristics of the metal loads are shown to be important parameters for the antenna performance.
In this paper, we investigate the performance of a distributed space-time coding based hybrid satellite- terrestrial cooperative network (DSTC-HSTCN), where both the satelliterelay and satellite-destination links undergo the Shadowed-Rician fading, whereas the relay-destination link follows the Rayleigh fading. In particular, we address the problem in a downlink distributed Alamouti coded satellite system with a single fixed terrestrial relay. By assuming that amplify-and-forward (AF) protocol is adopted at the terrestrial relay, we first derive the analytical expressions for the joint probability density function (PDF) and moment generating function (MGF) of the signal to noise ratio (SNR) for the cooperatively encoding phase. Then, based on the Meijer-G functions, we present an approximated yet accurate method to evaluate the outage probability and symbol error rate (SER) of the considered networks. Finally, Simulation results are provided to demonstrate the validity of the theoretical analysis.
No abstract is provided for this article.
This paper studies the newly emerging wireless powered communication network (WPCN) in which one hybrid access point (H-AP) with constant power supply coordinates the wireless energy/information transmissions to/from distributed users that do not have energy sources. A "harvest-then-transmit" protocol is proposed where all users first harvest the wireless energy broadcast by the H-AP in the downlink (DL) and then send their independent information to the H-AP in the uplink (UL) by time-division-multiple-access (TDMA). First, we study the sum-throughput maximization of all users by jointly optimizing the time allocation for the DL wireless power transfer versus the users' UL information transmissions given a total time constraint based on the users' DL and UL channels as well as their average harvested energy values. By applying convex optimization techniques, we obtain the closed-form expressions for the optimal time allocations to maximize the sum-throughput. Our solution reveals "doubly near-far" phenomenon due to both the DL and UL distance-dependent signal attenuation, where a far user from the H-AP, which receives less wireless energy than a nearer user in the DL, has to transmit with more power in the UL for reliable information transmission. Consequently, the maximum sum-throughput is achieved by allocating substantially more time to the near users than the far users, thus resulting in unfair rate allocation among different users. To overcome this problem, we furthermore propose a new performance metric so-called common-throughput with the additional constraint that all users should be allocated with an equal rate regardless of their distances to the H-AP. We present an efficient algorithm to solve the common-throughput maximization problem. Simulation results demonstrate the effectiveness of the common-throughput approach for solving the new doubly near-far problem in WPCNs.
This paper considers the use of energy harvesters, instead of conventional time-invariant energy sources, in wireless cooperative communication. For the purpose of exposition, we study the classic three-node Gaussian relay channel with decode-and-forward (DF) relaying, in which the source and relay nodes transmit with power drawn from energy-harvesting sources. Assuming a deterministic energy-harvesting model under which the energy arrival time and the harvested energy amount are known prior to transmission, the throughput maximization problem over a finite horizon of N transmission blocks is investigated for the delay-constrained (DC) case (for which only one-block decoding delay is allowed at the destination). By exploiting the structures of the optimal source and relay power profiles, we show that the joint source and relay power allocation over time is necessary to achieve the maximum throughput, and propose an efficient forward two-dimensional search algorithm to compute the optimal power profiles.
In multiple-input single-output (MISO) wireless power transfer (WPT) via magnetic resonant coupling, multiple transmitters are deployed to enhance the efficiency of power transfer to a single receiver by jointly adapting their source currents/voltages so as to constructively combine the induced magnetic fields at the receiver, a technique known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">magnetic beamforming</i> . In practice, since the transmitters (power chargers) are usually at fixed locations and the receiver (e.g., mobile phone) is desired to be freely located in a target region for wireless charging, its received power can fluctuate significantly over locations even with adaptive magnetic beamforming applied. To achieve uniform power coverage, the transmitters need to be optimally placed in the region such that a minimum charging power can be achieved for the receiver regardless of its location, which motivates this paper. First, we derive the optimal magnetic beamforming solution in closed form for a distributed MISO WPT system with fixed locations of the transmitters and receiver to maximize the deliverable power to the receiver subject to a given sum-power constraint at all transmitters. By applying adaptive magnetic beamforming based on this optimal solution, we then jointly optimize the locations of all transmitters to maximize the minimum power deliverable to the receiver over a given one-dimensional (1D) region. Although the formulated problem is nonconvex, we propose an iterative algorithm for solving it efficiently. Extensive simulation results are provided that show the significant performance gains by the proposed design with optimized transmitter locations and magnetic beamforming as compared to other benchmark schemes with nonadaptive and/or heuristic transmitter current allocation and node placement. Last, we extend the node placement problem to the case of 2D region, and propose efficient designs for this case.
This paper studies a new unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system, where a UAV-mounted mobile energy transmitter (ET) is dispatched to deliver wireless energy to a set of on-ground energy receivers (ERs). We investigate how the UAV should optimally exploit its mobility via trajectory design to maximize the energy transferred to all ERs during a finite period. First, we consider the maximization of the sum energy received by all ERs by optimizing the UAV's trajectory subject to its maximum speed constraint. We obtain its optimal solution, which shows that the UAV should hover at one single fixed location during the whole period. However, the sum-energy maximization incurs a "near-far" fairness issue. To overcome this issue, we consider a different problem to maximize the minimum received energy among all ERs. We first consider an ideal case by ignoring the UAV's maximum speed constraint, and show that the relaxed problem can be optimally solved via the Lagrange dual method. Then, for the general case with the UAV's maximum speed constraint considered, we propose a new successive hover-and-fly trajectory motivated by the optimal trajectory in the ideal case, and obtain efficient trajectory designs by applying the successive convex programing (SCP).
This paper presents a novel perspective on Chinese construction professionals’ adjusting process to new technical contexts. Through a series of semi-structured interviews, the study identified the mental process, checkpoints, operational process, and reflection as the key components of the adjusting process. Additionally, the research found that technical cognition played a crucial role in supporting the adjusting process, while motivators such as ‘being competent in the job position,’ ‘monetary incentives,’ ‘positional incentives,’ and ‘making good use of their own advantage’ acted as drivers for the process. Based on the findings, the paper proposes an explanatory model that demonstrates the relationships between the adjusting process, technical cognition, and motivators. This study sheds light on international professional adjustment and could inform international project management approaches and further research on Chinese construction professionals’ performance improvement.
