Optimal Time Allocation for Process Improvement and Growth for Entrepreneurs

Wireless energy transfer (WET) is a promising technique to prolong the lifetime of an energy-constrained wireless network. In this paper, we consider a two-hop communication system with multiple relay nodes powered by WET. To minimize the transmission time, we propose an optimal transmission scheme, in which the relay nodes adopt a “harvest-then-decode and forward” policy. The optimal transmission time allocation of the source and each relay node is calculated by a linear program under causality constraints on both data and energy arrivals. The analytical and simulation results reveal the relationship between the optimal time allocation and system parameters.

The increasing demand for data services has given rise to efficient utilization of available resources (e.g., energy) in modern wireless communication. In order to address the energy requirements a wireless powered communication network (WPCN) with separate energy source (ES) and access point (AP) is considered in this work. The transmitters here adopt harvest-then-transmit (HTT) protocol for transmission to AP. An optimal dynamic time allocation and scheduling policy is considered which maximizes the throughput of the system. The throughput maximization problem formulated is convex in nature and solved using convex optimization techniques. The fairness of proposed policy is compared with max-min policy which use harvest-or-transmit (HOT) protocol in terms of Jain's fairness index. Simulation results highlights the trade-off between throughput and fairness and show that the proposed policy is more reliable for the overcrowded scenario.

Generation and characterization of entanglement are crucial tasks in quantum information processing. A hypothesis testing scheme for entanglement has been formulated. Three designs were proposed to test the entangled photon states created by the spontaneous parametric down conversion. The time allocations between the measurement vectors were designed to consider the anisotropic deviation of the generated photon states from the maximally entangled states. The designs were evaluated in terms of the p-value based on the observed data. It has been experimentally demonstrated that the optimal time allocation between the coincidence and anti-coincidence measurement vectors improves the entanglement test. A further improvement is also experimentally demonstrated by optimizing the time allocation between the anti-coincidence vectors. Analysis on the data obtained in the experiment verified the advantage of the entanglement test designed by the optimal time allocation.

In this paper, we consider a full duplex wireless powered communication network where multiple users with RF energy harvesting capabilities communicate to a hybrid energy and information access point. An optimization framework is proposed with the objective of maximizing the sum throughput of the users subject to energy causality and maximum transmit power constraints considering a realistic energy harvesting model incorporating initial battery levels of the users. The joint optimization of power control, time allocation and scheduling is mathematically formulated as a mixed integer non linear programming problem which is hard to solve for a global optimum. The optimal power and time allocation and scheduling decisions are investigated separately based on the optimality analysis on the optimization variables. Optimal power and time allocation problem is proven to be convex for a given transmission order. Based on the derived optimality conditions, we propose a fast polynomial-time complexity heuristic algorithm. We illustrate that the proposed algorithm performs very close-to-optimal while significantly outperforming an equal time allocation based scheduling scheme.

In this paper, the buffer-constrained throughput performance of a multi-user wireless-powered communication (WPC) system is investigated, where energy harvesting follows a non-linear model. The investigation focuses on the buffer overflow performance of sending data in the downlink (DL) from the access point (AP) node to each user equipment (UE) node and that in the uplink from each UE node to the AP node, based on which the throughput performance on both directions when a buffer constraint is enforced is studied. Specifically, the buffer overflow probability at each node is analyzed, based on which the buffer-constrained throughput is studied. In addition, to ensure the throughput performance under the buffer constraint, the DL transmission power allocation policy and the required energy storage capacity at each UE are investigated. Also, the optimal channel time allocation policy is studied with the objective of maximizing the minimum buffer-constrained throughput guaranteed to each UE at the same time. To this aim, an optimization problem is first formulated and then a dichotomy-based time allocation algorithm combined with a one-dimensional search is proposed to solve this problem. The analysis and results, explicitly relating the throughput to the buffer constraint in addition to WPC characteristics, shed new light on the design and performance analysis of WPC systems.

In this paper, time-switching based wireless powered relay systems, where the source and destination jointly transfer energy to the relay, is studied. Given a certain transmission duration, there is a time trade-off between wireless energy transfer and information cooperative transmission. Although more time for energy harvesting causes more available power at the relay, it shrinks the duration of information transmission and may incur less system throughput. To obtain the optimal time allocation, we derive the information outage probability of the relay system. And then we solve the optimization problem of time allocation to achieve the maximum system throughput. Finally, simulation results verify our derived theoretical results. And it is also shown that the proposed time allocation scheme indeed achieves maximum average throughput.

In this paper, we investigate the optimal power and time allocation for a wireless relay network, called BCFR (Broadcasting Channel with Fixed Relay), where the relay node is limited by the half-duplex operation. Introducing a relay in two-node broadcasting channel for a node which has a link of bad quality or requires higher transmission rate enlarges the rate region with well-designed power and time allocation. Also, BCFR is a common component of many relay networks, in which either orthogonal or non-orthogonal transmission can be adopted at the information source node. In particular, for the non-orthogonal transmission, the layered transmission with superposition coding is applied at the source node. By deriving the optimal power and time-fraction allocation at each node of BCFR, we show that the non-orthogonal structure enhances the capacity region and achieves higher log-sum capacity than the orthogonal transmission.

In this paper, we characterize optimal resource allocation for the uplink and downlink of wireless powered cellular networks (WPCNs). In particular, we investigate a time-slotted WPCN, where a hybrid access point (HAP) is in charge of energy replenishing of M cellular users (CUs), along with transmission/reception of information to/from them. Unlike prior works, which give attention to information transmission in only one direction (either uplink or downlink), our work incorporates information transmission in both directions, along with energy transfer over the downlink. Besides harvesting energy explicitly from the HAP, each user opportunistically harvests the RF energy borne by the information sent by the HAP over the downlink to the remaining M−1 users, in order to boost its uplink throughput. Towards this objective, we formulate the total (uplink and downlink) sum throughput maximization problem to characterize the optimal time allocation for energy, downlink information, and uplink information slots, subject to time allocation constraints. Furthermore, we establish the convexity of the problem, and an efficient algorithm based on the gradient projection method is proposed. The obtained numerical results reveal valuable insights about the fairness-throughput trade-offs. Moreover, and among others, the network dynamics are introduced, which clarify how the optimal time allocation pattern is changed in accordance with the change of the users' placement, and the HAP's transmission power, in both energy and information slots.

In this paper, we proposed an optimal time allocation to maximize the total average transmission data of two-way relay system. First, we derived the average transmission data rate of two-way relay system by the probability of successful transmission and the target data rate. Next, based on the derived the average transmission data rate of two-way relay system, we proposed an optimal time allocation of each link as a closed form. The simulation result verifies that the proposed time allocation is optimal.

This study proposes an optimal time allocation scheme for two‐way relay channel (TWRC) using the physical‐layer network coding (PNC). In other words, this study analytically determines the optimal transmit time durations for the first and the second time slot, which maximise the achievable sum rate under a sum time constraint for a given squared magnitude of the channel coefficients and transmit power values. Numerical results show that the achievable sum rate for the proposed optimal time allocation is greater than or equal to that for equal time allocation.

1. Animals foraging for resources are under a variety of selective pressures, and separate optimality models have been developed predicting the optimal reproductive strategies they should adopt. 2. In most cases, the proximate behavioural mechanisms adopted to achieve such optimality goals have been identified. This is the case, for example, for optimal patch time and sex allocation in insect parasitoids. However, behaviours modelled within this framework have mainly been studied separately, even though real animals have to optimize some behaviours simultaneously. 3. For this reason, it would be better if proximate behavioural rules were designed to attain several goals simultaneously. Despite their importance, such multi-objective proximate rules remain to be discovered. 4. Based on experiments on insect parasitoids that simultaneously examine their optimal patch time and sex allocation strategies, it is shown here that animals can adopt multi-objective behavioural mechanisms that appear consistent with the two optimal goals simultaneously. 5. Results of computer simulations demonstrate that these behavioural mechanisms are indeed consistent with optimal reproductive strategies and have thus been most likely selected over the course of the evolutionary time.

A Dynamic decode-and-forward (DDF) relaying protocol with partial Channel state information at the transmitter (CSIT) for a three-node half-duplex single-antenna network, which consists of a single source destination pair and a relay, is proposed. A Diversity multiplexing trade off (DMT) analysis is presented, in which the DMT of the proposed protocol is derived in a closed form and an adaptive time allocation strategy is also developed to achieve the optimal performance. It is shown that time allocation with partial CSIT significantly improves the achievable DMT for DDF relaying. Moreover, unlike the existing DDF protocol with CSIT, which is performed with the assumption of long-term power constraint, the proposed protocol can be generalized to the practical scenarios where a strict short-term power constraint is often imposed on, due to the environmental safety and interference prevention.

We investigate resource allocation policies for time-division multiple access (TDMA) over fading channels in the power-limited regime. For frequency-flat block-fading channels and transmitters having full channel state information (CSI), we first minimize power under a weighted sum average rate constraint and show that the optimal rate and time allocation policies can be obtained by a greedy water-filling approach with linear complexity in the number of users. Subsequently, we pursue power minimization under individual average rate constraints and establish that the optimal resource allocation also amounts to a greedy water-filling solution. Our approaches not only provide fundamental power limits when each user can support an infinite-size capacity-achieving codebook (continuous rates), but also yield guidelines for practical designs where users can only support a finite set of adaptive modulation and coding modes (discrete rates).

In this paper, we consider wireless powered communication networks (WPCNs) where multiple users harvest energy from a dedicated power station and then communicate with an information receiving station in a time-division manner. Thereby, our goal is to maximize the weighted sum of the user energy efficiencies (WSUEEs). In contrast to the existing system-centric approaches, the choice of the weights provides flexibility for balancing the individual user EEs via joint time allocation and power control. We first investigate the WSUEE maximization problem without the quality of service constraints. Closed-form expressions for the WSUEE as well as the optimal time allocation and power control are derived. Based on this result, we characterize the EE tradeoff between the users in the WPCN. Subsequently, we study the WSUEE maximization problem in a generalized WPCN where each user is equipped with an initial amount of energy and also has a minimum throughput requirement. By exploiting the sum-of-ratios structure of the objective function, we transform the resulting non-convex optimization problem into a two-layer subtractive-form optimization problem, which leads to an efficient approach for obtaining the optimal solution. The simulation results verify our theoretical findings and demonstrate the effectiveness of the proposed approach.

In this paper, we study the Physical Layer Security (PLS) problems in intelligent reflecting surface (IRS) multiple-input single-output (MISO) communication systems. A novel transmission scheme aimming to minimize the system energy consumption is proposed by jointly optimizing the phase shift matrix at the IRS and the beamforming vectors at the base station (BS). Furthermore, the maximum secrecy capacity is obtained by designing the time allocation between channel training and information transmission. Theory analysis and numerical results validate that the time ratio value depends on the signal-to-noise ratio (SNR) at the intended receiver.KeywordsPhysical layer securityIntelligent reflecting surfaceSecrecy capacityTime allocation