This article focuses on the issue of cooperative spectrum sensing (CSS) in a mobile energy-harvesting cognitive radio network (EH-CRN), where secondary transmitters (STs) are powered by the radio-frequency (RF) signal emitted from primary transmissions. Only the STs with sufficient energy participate in CSS, and send their local sensing decisions to a fusion center (FC), which makes a final decision on the state of the spectrum by a general k-out-of-M(k) fusion rule. The target of this article is to develop an optimal CSS strategy in terms of final decision threshold k that maximizes the expected achievable throughput of the EH-CRN, subject to a collision constraint and an energy causality constraint. We first show that the EH-CRN can be divided into an energy-deficit state and a spectrum-deficit state depending on the final decision threshold. The final decision threshold has a negative correlation with the number of STs participating in CSS in the energy-deficit state, and has no impact on that in the spectrum-deficit state. We then derive the collision probability and the expected achievable throughput of the EH-CRN, both of which are indicated to be determined by the active probability of a ST, the state of the spectrum, and the spectrum access opportunity. By tackling the tradeoff between the active probability and spectrum access opportunity introduced by the final decision threshold, we derive the optimal final decision threshold that maximizes the expected achievable throughput of the EH-CRN while protecting primary transmissions to a predefined extent. Extensive numerical simulations are conducted to illustrate the performance versus the final decision threshold. One of the main findings indicates that the optimal range of final decision threshold in the energy-deficit state could be acquired by the number of reporting received at the FC.

Trend of dense deployment of 802.11 WLANs makes it urgent to design effective and efficient channel access schemes. IEEE 802.11ax standard for the next generation WLAN introduces the orthogonal frequency division multiple access (OFDMA) mechanism that supports downlink and uplink multi-user transmissions over multiple resource units (RUs). In this paper, we, integrating the multi-user transmissions with the target wake time (TWT) mechanism, propose the Scheduling Channel Access with TWT (SCAT) scheme. The SCAT wakes up stations (STAs) no more than the number of RUs in each target beacon so that the channel can be accessed on schedule without contention. Additionally, we develop a mathematical model to derive the throughput and delay arising from sleeping (DAFS) under the SCAT, which are used to formulate the throughput maximization problem (TMP) subject to delay constraint. Then, the TMP is solved by the genetic algorithm in which a tree is chosen as a chromosome. The solution to the TMP enables the SCAT to assign the optimal listen intervals and the next target beacons to the STAs so that the maximum throughput is achieved. Simulation results show the SCAT outperforms the existing schemes in throughput, channel utilization, and energy efficiency.

With the promising technology of far-field wireless power transfer, wearable devices are able to harvest radio frequency (RF) energy from RF-based chargers and thus operate continuously. Rational planning of the quantity and positions of the chargers provides an effective way to improve the recharging efficiency and save the charger deployment budget. Existing work on RF-based charger placement mainly considers the situation where the devices are static, or adopt very simple mobility model. In this paper, we consider wireless charging service provision for wearable devices worn by users in a 2-D area, with users having a specific stay-move behavior pattern characterized by the trajectories, stay points and stay time distribution. Based on this mobility pattern, we formulate the problem as how to find a charger placement to minimize the charging service budget, subject to the power non-outage probability requirement of the wearable devices. We further transform this problem to several equivalent problems for easier tractability and prove that it is NP-complete. Both greedy heuristic and particle swarm optimization (PSO)-based solutions are proposed to solve the problem with certain approximation ratio. Finally, performances of the proposed solutions are compared with exhaustive search and existing point provisioning algorithm through extensive simulations. Simulation results show that both greedy heuristic and PSO-based solutions outperform the baseline algorithms, while PSO-based solution requires least number of chargers and thus is the most cost-effective.

Radio-frequency (RF) energy harvesting is one of the promising technologies in wireless networks. This paper considers wireless powered communication networks (WPCNs) where one hybrid access point (H-AP) coordinates RF energy/information transmissions to/from a set of nodes. For the important type of WPCNs where the nodes have throughput requirement, we aim to minimize H-AP's energy consumption (EC) via jointly optimizing the time allocation of energy/information transmissions and H-AP's transmission power while satisfying node throughput requirement. More specifically, the half-duplex WPCN is considered firstly. We prove that H-AP's energy transmission power must be the maximum allowed value to achieve the minimal EC, then show that the problem is convex under this condition and finally design an algorithm applying golden section search and bisection search jointly to efficiently obtain the optimal time allocation. Secondly, the full-duplex WPCN is considered. Its EC minimization problem is proved convex. However, due to the hardness of solving it directly, we turn to solve the feasibility problem (FP) for a given EC per unit time. We construct a convex optimization problem based on this FP and design a dual subgradient algorithm for finding its optimal solution which indicates whether this FP is feasible. The minimal EC per unit time and its corresponding optimal solution are found by using the bisection search method. Simulation results show that, the EC-minimized schemes are able to greatly reduce H-AP's EC as compared to the baseline schemes.

To achieve a long run-time for battery-operated portable electronic devices that incorporate wireless transceivers, efficient power management of the radio is a critical requirement. The power management function of IEEE 802.11 wireless local area networks (WLANs) allows stations (STAs) to operate in the doze mode so that their power consumption is significantly reduced. Hence, efficient algorithms to manage when and how often a STA enters and exits doze mode are crucial to battery-operated STAs. We address this problem by developing a novel model for stochastic analysis of timer-based power management in infrastructure IEEE 802.11 WLANs. Based on this model, the probabilities that a STA is active, idle, or dozing are derived, and the power consumption of the STA, number of frames buffered, and average delay per frame are obtained. These results enable an efficient power management algorithm that optimizes the idle timer and doze duration at the STA and the frame buffer at the access point. Moreover, similar statistics for the basic power management method in the IEEE 802.11 standard are derived as a special case of the proposed timer-based power management scheme. Numerical results are presented to demonstrate the effectiveness of the proposed algorithms.