Commodity RFID tags backscatter stored electronic product code (EPC) to the reader, but do not have sensing capability. Existing works have made much effort on designing RFID-based sensing platform. But most of them either need intricate hardware design or rely on modification of the tag, which increases the cost or constrains the sensing capability. In this paper, we design a self-jamming identification and sensing platform (SJISP) consisting of SJISP nodes and a commodity RFID reader. A subtle design of the SJISP node is the adoption of a jammer radio module with the same frequency as the reader, controlled by the micro control unit (MCU) to decide whether to interfere with the query process of the RFID reader. The RFID tag is not readable if the jammer is turned on to generate interference signals. Otherwise, it is readable when the jammer is turned off. The sensing data is thus modulated by switching the jammer on and off for transmitting bit 0 and bit 1, respectively. The reader demodulates the data through the compatible EPC UHF Gen2 air interface protocol. To further save the energy of the SJISP node, we propose a prefix codebook based data delivery scheme, which leverages the difference of energy consumption (DEC) between transmitting bit 0 and bit 1. Our proposed scheme can save more than 50$\%$of the energy than common communication without codebook. Experimental results based on our prototyped system show that the designed SJISP can achieve an average packet reception rate (PRR) of over 99$\%$and is quite robust to environmental disturbance. Our designed platform provides a low-cost and compatible solution to extend the sensing capability of RFID system. A demo application with a temperature sensor and a light sensor embedded in two SJISP nodes respectively are developed to demonstrate how SJISP applies in real world scenario.

With the explosive growth in mobile users carrying various devices such as smart phones and portable computers, wireless local area networks (WLANs) are densely deployed. The IEEE 802.11ax standard, targeting at the next generation WLAN and scheduled to be published in this year, addresses the challenges arising from dense WLAN deployment. In the near future, coexistence of the 802.11ax WLANs and the long term evolution (LTE) system will be popular. It is significant to design a mobile user allocation scheme to assign each mobile user in the common coverage of the LTE system and the 802.11ax WLANs to the LTE system or the 802.11ax WLANs, so that total throughput in the coexistence area is improved. In this paper, we present a throughput aware user distribution (TAUD) scheme. The TAUD scheme maximizes the total throughput by separating the mobile users in the coexistence area of an 802.11ax WLAN and the LTE systems into two groups with each connecting the LTE system or the 802.11ax WLAN. The numeric results show that the proposed scheme can improve throughput considerably.

Abstract As a contention‐free channel access protocol, Time Division Multiple Access (TDMA) is widely applied in Energy Harvesting Wireless Sensor Networks (EH‐WSNs) due to ease of implementation. TDMA scheduling in EH‐WSNs faces the problem of low channel utilization since time slots assigned to some nodes may not be used by them due to shortage of energy or data. It is important to design TDMA scheduling schemes that enhance channel utilization. In this paper, the Fixed Frame Size Scheme (FFSS) and the Adaptive Frame Size Scheme (AFSS) are proposed to improve channel utilization of EH‐WSNs. The FFSS aims at the optimal TDMA slot assignment for the TDMA scheduling with fixed frame size, and the AFSS considers the TDMA with variable frame size and targets both the optimal frame size and the optimal slot assignment. The optimization problems maximizing channel utilization are formulated for the FFSS and the AFSS, respectively, which take the upcoming energy and data into account. The optimization problems are transformed into assignment‐like problems and solved by the Hungarian‐based algorithm in polynomial time. Simulation results indicate that the proposed FFSS and AFSS can considerably improve channel utilization in the EH‐WSNs compared with the existing TDMA scheduling schemes.

Energy harvesting wireless sensor networks (EH-WSNs) intend to support sustainable operations. It is important to design a high-throughput data delivery scheme that adapts to the fluctuation in harvested energy in the EH-WSN nodes. In this article, the optimal superframe and data buffer scheme (OSDBS) is investigated to improve the throughput of IEEE 802.15.4 beacon-enabled EH-WSNs. A stochastic model is developed for OSDBS, which leads to the characterization of network throughput and packet delay. The OSDBS achieves the maximum throughput through setting the optimal superframe and buffer sizes of the nodes, which are the solution of the formulated optimization problem that maximizes the network throughput with consideration of energy-harvesting rate and data arrival rate. The simulation results show the OSDBS significantly outperforms the existing schemes in terms of throughput.

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.

In the energy‐harvesting wireless sensor networks (EH‐WSNs) with Time division multiple access (TDMA), it is challenging to assign time slots to the nodes because energy shortage causes some nodes unable to transmit in their time slots, resulting in the inefficiency in slot usage and the increase of the data packet delay. To overcome this problem, the slot assignment in TDMA is required to consider energy packet arrivals, where an energy packet is defined as the amount of energy that suffices for one transmission. In this study, the authors investigate the EH‐WSN with hybrid energy sources, in which the nodes harvest energy from the fixed inter‐arrival time (FIAT) and the random inter‐arrival time (RIAT) energy sources. After deriving the slot‐hitting ratios (SHRs) of energy packet arrivals for both FIAT and RIAT energy sources, they propose the SHR‐based TDMA (SHR‐TDMA) scheme. Then, they derive the delay arising from the awaiting slot (DAFAS) and formulate the DAFAS minimisation problem for the SHR‐TDMA. Solution to the DAFAS minimisation problem makes the slots optimally assigned according to the characteristics of the energy packet arrivals at the nodes. The simulation results show that the SHR‐TDMA outperforms the existing TDMA schemes in terms of DAFAS.

In the battery‐free wireless sensor network (BF‐WSN) that harvests radio signal energy, data delivery suffers from a longer delay arising from the energy‐harvesting period. It is significant to develop an energy‐efficient, low‐delay, and reliable data gathering scheme for the BF‐WSN. The goodput‐maximised data delivery scheme (GDDS) is proposed to reliably collect time‐constrained data in the IEEE 802.15.4‐based BF‐WSN. Under the GDDS, the sink's operation period consists of multiple data gathering cycles with each incorporating three phases: charging the nodes, assigning channel occupation time for the nodes, and receiving packets from the nodes. The scheme of accumulating correct data blocks (SACDB) is used in the third phase for the sink to gather data from the nodes. The authors develop an analytical model for the SACDB, from which they derive the time and the energy consumed in transmitting a packet. Then, they derive the goodput and the energy efficiency under the proposed GDDS. The GDDS aims at maximising the goodput by optimising the charging period, the number of data blocks, and the maximum number of transmission trials under the constraint on data gathering time. Simulation results show the GDDS outperforms the existing schemes in terms of the goodput and energy efficiency.

The common backscatter communications (ComBC), widely applied in wireless powered networks such as the RFID systems, exhibit the shortcoming that only a few bits are backscattered at a time due to energy limitation. It is significant to improve energy efficiency in backscatter communications so more data can be delivered within one backscatter. In this article, the energy-efficient dual-codebook based backscatter communications (DBBC) is proposed, which adopts two prefix codebooks shared by the sender and the receiver over a backscatter communication link. With the DBBC, the sender backscatters codewords from which the receiver decodes the original data. Using Energy Consumption Disparity (ECD) between backscattering bits 1 and 0 in the existing backscatter communications, we formulate the optimization problem minimizing energy consumption over the link for the DBBC. Mapping a prefix codebook into a binary tree and performing pruning and expanding operation (PEO) on binary trees, we obtain the solution to the optimization problem, which includes the two energy-efficient codebooks and the other two key parameters for the DBBC. The experiments on wireless identification sensing platform (WISP) show that, under the proposed DBBC, the sender can backscatter data 83% more than the ComBC with the same energy without sacrificing throughput.

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.

Cognitive radio and energy harvesting techniques have provided significant benefits in terms of spectrum reuse and lifetime prolongation for conventional wireless networks. We are thus motivated to consider the energy harvesting cognitive radio networks (CRNs) consisting of multiple primary users (PUs) and secondary users (SUs). We introduce two cooperation modes: the energy cooperation mode and joint cooperation mode. In the energy cooperation mode, there only exists energy cooperation between PUs and SUs, i.e., the SU transmits its own packets by using the energy harvested from primary signals. In the joint cooperation mode, the SU relays primary packets by using the energy harvested from primary signals. In each cooperation mode of three representational scenarios (the CRN with one pair of PUs and one pair of SUs, the CRN with two pairs of PUs and one pair of SUs, and the CRN with one pair of PUs and two pairs of SUs) and the general scenario, we exploit the optimal time allocation between PUs and SUs, and balance the tradeoff between energy harvesting and packet transmission to obtain the maximum total achievable throughput. To be specific, we first formulate the throughput maximization problems as non-linear optimization problems, and then prove them as convex problems by monotonicity analysis. Moreover, we obtain the closed-form optimal solution in the energy cooperation mode. We prove the existence of the optimal solution in the joint cooperation mode, obtain the upper and lower bounds, and provide numerical analysis for the optimal solution. Finally, we highlight the benefits of information cooperation and the impact of multi-user gain on the maximum of the total achievable throughput.

RF Energy harvesting technology has been proved one of the effective approaches for powering battery-free wearable devices in wireless body area networks. However, excessive electromagnetic radiation is harmful to human body. In this paper, we consider real-time healthcare scenario where wearable devices worn by mobile users collect their physiological data in real time and multiple wireless chargers are deployed for energy provision. Our goal is to minimize the maximal radiation degree among mobile users while maintaining normal work of wearable devices via adaptive power control of wireless chargers. We first discrete the users' moving trajectories and transform the stubborn problem into a docile one. Then we propose a distributed algorithm with interaction of wireless chargers, wearable devices and base station to solve it. Our proposed real-time power control scheme achieves an approximation ratio of (1+e) in general case. Furthermore, one special case is discussed. Simulation results reveal that our scheme is efficient and the maximal radiation degree among users can be reduced by almost 20\% as compared to the baseline scheme.

The next generation of wireless local area network (WLAN) adopts IEEE 802.11ax standard to be published in 2019, which provides the orthogonal frequency division multiple access (OFDMA) mechanism. The Uplink OFDMA-based Random Access (UORA) in the 802.11ax standard enables multiple users to randomly pick resource units (RUs) to transmit uplink data simultaneously. Under the UORA, access point (AP) dynamically announces some eligible random access RUs in the trigger frame so that the associated mobile stations (STAs) can contend for these RUs. Only when the picked OFDMA-based random access backoff (OBO) counter is no more than the number of eligible random access RUs, can a STA randomly select a RU to transmit. An unsuccessful transmission forces the STA to double its OFDMA contention window (OCW) size, which causes the STA to endure a longer delay for retransmission(s). In this paper, we propose the probability complementary transmission scheme (PCTS) to mitigate the delay for retransmissions. We define the complementary probability for the PCTS, with which the STA performs complementary transmission without backoff. In addition, we formulate the optimization problem that maximizes the throughput. The solution of the optimization problem is applied in the design of the PCTS so that the maximal throughput is gained. Simulation results show that the PCTS outperforms the existing schemes in terms of throughput and packet delay.

Orthogonal Frequency Division Multiple Access (OFDMA) introduced in IEEE 802.11ax amendment promises to improve spectral efficiency by grouping subcarriers into resource units (RUs). It is important to design RU assignment to improve throughput for the OFDMA-based WLAN. In this paper, we present the High Throughput RU Assignment Scheme (HiTRAS) and formulate the optimization problem maximizing network throughput for the HiTRAS. The solution of the optimization problem leads to the optimal RU assignment that allocates RUs to multiple mobile stations (STAs) so that the STAs can transmit their uplink traffic simultaneously and thus high throughput is gained. The simulation results show that the HiTRAS outperforms the existing schemes in terms of throughput.

When deploying radio frequency (RF)-powered sensor networks for mission-critical applications such as security surveillance, it is often required to maximize or guarantee the quality of surveillance. Both placing and scheduling the charging/working modes of sensors are of key importance in order to continuously ensure a satisfying quality of surveillance. Traditionally, sensor placement and scheduling have been considered separately. The first decision regards where to place the sensors, and then when to activate them. In this paper, we study simultaneous sensor placement and charging/working scheduling problem for fusion-based detection in RF-powered sensor networks. The problem is formulated as a constrained optimization problem and proved to be NP-complete. Two greedy heuristic algorithms, joint optimization greedy algorithm with fixed fusion radius (JOGA-FFR) and joint optimization greedy algorithm with dynamic fusion radius (JOGA-DFR) based on fixed and dynamic fusion radiuses, respectively, are presented to solve the problem. We validate our approaches through extensive numerical simulations as well as simulations based on real data traces collected from a vehicle detection experiment. The results show that, our proposed algorithms always outperform two-stage greedy algorithm (TSGA), an algorithm that optimizes sensor placement and scheduling separately, in all the simulation scenarios, and are near optimal in small-scale networks. Besides, JOGA-DFR outperforms JOGA-FFR under certain specific sensing model settings, but more often has a comparable performance with JOGA-FFR. JOGA-FFR is thus more recommended for its lower complexity.

Recently, the newly emerging wireless powered communication network (WPCN) has drawn significant interests, where the network nodes are powered by the energy harvested from the radio-frequency (RF) signal. This paper focuses on the widely studied WPCN, where one hybrid sink (H-sink) coordinates the wireless energy/information transmissions to/from a set of one-hop nodes powered by the harvested RF energy only, and aims to minimize the network-throughput constrained H-sink's energy provision (EP). Specifically, we investigate the performance of two important MAC protocols: time-division multiple access (TDMA) and non-orthogonal multiple access (NOMA). For both the TDMA-based WPCN (T-WPCN) and NOMA-based WPCN (N-WPCN), we first formulate the EP minimization problems as the non-linear optimization problems, then transform them into convex problems, and finally propose an efficient algorithm, which jointly uses the golden-section search and bisection search methods to determine the optimal time allocation of H-sink's energy transfer and each node's information transmission as well as the optimal H-sink's transmit power. Furthermore, for the scenarios where the circuit power is negligible, we first prove that the optimal H-sink's transmit power is the maximum allowable value, then prove theoretically that the NOMA and TDMA achieve the same EP, and also present a more efficient algorithm for the EP minimization problem. Simulation results demonstrate that the TDMA outperforms NOMA when the circuit power is non-negligible because the circuit energy consumption of NOMA accounts for a large percentage of the total energy consumption.

Envisioning the potentials of energy harvesting technology and the improved spectrum reuse by joint utilization of overlay and underlay modes, this paper studies the throughput performance of a novel cognitive radio network (CRN) scenario with a mobile energy-harvesting secondary transmitter (ST). The hybrid overlay-underlay scheme allows the secondary users to access the spectrum even when the primary signal is detected. We are the first to partition the unit area into three parts for secondary users: overlay mode area, underlay mode area, and harvesting zone. Then, we propose a metric to classify the CRN into the spectrum-limited state and the energy-limited state, and accordingly maximize the throughput through the monotonicity analysis of throughput and collision probability. The secondary throughput is maximized under the energy constraint and collision constraint. Moreover, we quantitatively discuss the impacts of underlay mode transmission on the classification of network states and the corresponding optimal spectrum sensing, respectively. We find that with a relatively small detection threshold, ST transmits the considerable amount of packets in underlay mode, while it transmits few packets in overlay mode. Theoretical results are validated by simulations, and our findings shed light on the design and operation of mobile energy-harvesting CRNs.

This paper characterizes the throughput and delay performance of Cognitive Radio Networks (CRNs), where both primary and secondary networks coexist in a unit torus. Specifically, the primary network consists of static primary nodes (PNs) of density n, which have a higher priority to access the spectrum. In contrast, the secondary network consists of mobile secondary nodes (SNs) of density m = nβwithβ≥ 1, which move according to a hybrid random walk mobility model and have opportunistic access to the spectrum without affecting primary packet transmissions. Motivated by the fact that cooperation between primary and secondary nodes leads to possible improvement on the performance of CRNs, as well as the fact that the heterogeneous moving regions of secondary nodes will bring about further improvement, we propose a novel hierarchical cooperative scheduling mechanism, where secondary nodes serve as relays for primary packet transmissions by exploiting their mobility heterogeneity and geographic information. Our findings include: (i) For the primary network, stronger mobility heterogeneity of secondary nodes leads to better delay performance of the primary network, and meanwhile the delay scaling can be significantly reduced to Θ (n√(β/(4 log n)) log3/2n) when a near-optimal per-node throughput of Θ(1/log n) is obtained. (ii) For the secondary network, we also adopt a similar hierarchical cooperative scheduling mechanism, and obtain a near-optimal per-node throughput of Θ (1/log m) with the delay scaling of Θ(m1-(1√logm)). (iii) The delay of secondary source-destination pairs is determined by the moving region of destinations and has no relation with sources. Our work provides deeper understandings of the cooperation, heterogeneous mobility, and geographic information on the performance of CRNs, and sheds light on designing more efficient CRNs.

In the Internet of Things, wireless sensor networks (WSNs) are widely deployed. In recent years, wirelessly powered WSNs or battery‐free WSNs (BF‐WSNs), in which the nodes harvest energy from radio signals in the environment, have been emerging to support sustainable operation for WSNs. It is significant to design an energy‐efficient data delivery scheme for the BF‐WSNs. In this study, the authors propose the prefix code based scheme (PCBS) to save energy in data delivery by making use of the energy consumption disparity (ECD) between transmitting/receiving bit 0 and bit 1 in the existing non‐modulation baseband transmission or carrier‐modulation based passband transmission. The authors formulate an optimisation problem and use genetic algorithm to find its solution so that the energy‐efficient prefix codebook is obtained. The codebook dilutes the ECD by containing the energy‐consuming bit as few as possible, and the PCBS maps each m ‐bit data block into a prefix codeword in the codebook to conduct energy‐efficient transmission at the transmitter and vice versa at the receiver. Both the experiments on wireless identification sensing platform and the simulations demonstrate that the proposed PCBS outperforms the existing schemes in terms of energy saving.

Narrowband Internet of Things (NB-IoT) is a new cellular technology introduced by the third generation partnership (3GPP) providing low-power and wide-area coverage for IoT. In this paper, we consider the scenario that NB-IoT is deployed in an heterogeneous network and the quality of the direct link from the NB-IoT user equipment (TIE) to the serving base station (BS) cannot satisfy the quality of service requirement for transmission of vital sensing data. Thereupon, device-to-device (D2D) communication is adopted as a routing extension to NB-IoT systems, and thus, enables two-hop routes between NB-IoT TIE and the serving BS via a set of D2D relays. As the candidate TIE relays work in duty cycle to save energy, we derive a model to select a set of TIE relays and perform opportunistic D2D communication according to a working schedule. Two optimization problems are formulated aiming at achieving optimal expected delivery ratio (EDR) and expected two-hop delay, respectively. Dynamic programming-based algorithms are proposed to solve the optimization problems and obtain the optimal working schedule of the relays. Simulation results demonstrate that our proposed maxEDR and minEED algorithms improves the system performance compared with other state-of-the-art algorithms.

Recently, the newly emerging wireless powered communication network (WPCN) has drawn significant interests, where network nodes are powered by the energy harvested from the radio-frequency (RF) signal. This paper studies the WPCN where one hybrid sink (H-sink) coordinates the wireless energy/information transmissions to/from a set of one-hop nodes powered by the harvested RF energy only. The transmission completion time (TCT) minimization for the uplink (UL) transmissions of a given number of bits per node is considered. First, we prove that the harvest-then-transmit (HTT) transmission strategy is one of the transmission strategies able to achieve the minimal TCT, where all nodes first harvest the RF energy broadcast by the H-sink in the downlink and then send their independent information to the H-sink in the UL by time-division multiple access. Then for the HTT transmission, we prove that in order to achieve the minimal TCT, each node must transmit with constant power and consume all available energy, which helps to simplify the considered TCT minimization problem to be the optimization of time allocated for the H-sink's wireless energy transfer and the nodes' wireless information transmissions, and we formulate the optimal time allocation problem as a nonlinear optimization problem. Finally, we prove that it is a convex optimization problem. Due to the inexistence of explicit closed-form expressions of optimal time allocations to minimize TCT, one efficient algorithm is presented to obtain the optimal time allocations. Simulation results show that, compared with the available transmission strategies, the designed TCT-minimized transmission achieves a significantly smaller TCT.

Battery-Free Wireless Sensor Networks (BF-WSNs) have become increasingly useful for many applications and how to ensure timely information exchange between nodes in IP networks and those in BF-WSNs is indispensable. The 6LoWPAN protocol is usually used to deliver IPv6 packets over IEEE 802.15.4 based WSNs, and has resolved the size mismatching problem between IPv6 packets and 802.15.4 Medium Access Control (MAC) frames by using packet fragmentation scheme to break an IPv6 packet into multiple small pieces with each fitted into a single 802.15.4 MAC frame. Unfortunately, IPv6 packets in BF-WSNs may suffer from intolerable delay for timely reassembling back to IPv6 packets. In this paper, we present a Latency Aware IPv6 Packet Delivery (LAID) scheme to reduce such IPv6 packet latency while maintaining high packet delivery ratio. Our LAID considers charging time, data rate, and the Maximum Number of Transmission Trials (MNTT) used in the IEEE 802.15.4 MAC layer so that the minimum latency can be achieved by optimizing the pairing of data rate and MNTT. In addition, we apply network coding to improve packet delivery reliability. Our analysis shows that the proposed LAID significantly outperforms existing schemes with fixed data rates in terms of IPv6 packet latency.

In Battery-Free Wireless Sensor Network (BF-WSN), nodes are powered by the energy harvested from ambience instead of batteries. The nodes may frequently suffer from insufficient energy so that they need to alternate normal operation (such as transmitting/receiving, etc.) with harvesting energy. This brings in extra packet delay for the nodes to deliver data to the sink(s). Therefore, delivering data with shorter delay is a critical concern for BF-WSN nodes. In this paper, we first define the weight of wireless link that takes into account interference among links, balancing data load among the subtrees of the data gathering tree, and energy harvesting rate (EHR) of the nodes. Then, using the defined weight, we present the heuristic algorithm to build data gathering tree by letting the wireless link with a smaller weight join the tree prior to the ones with greater weights so that the wireless links either tending towards interference with the other ones, bringing in unbalance data load in the subtrees, or having smaller EHR are deferred to join the tree, thus reducing packet delay. Simulation results show the proposed data gathering scheme outperforms the existing scheme in terms of the delay per packet reaching the sink.

It is critical to design energy-efficient communication technologies for wireless nanosensor networks (WNSNs) as nanosensors are highly energy-constrained. This paper focuses on WNSNs adopting the on-off keying (OOK) modulator. So far, some existing low-weight (LW) codes with low average codeword weight (ACW) map source symbols into different codewords with fewer high bits so as to greatly reduce the transmission energy at the transmitter. However, the transmission energy reduction is achieved at the price of large reception energy at the receiver as the codeword lengths of LW codes are large, incurring their ineffectiveness in most scenarios. To remedy the problem, we design the fixed-length minimum-communication-energy (F-MCE) code and variable-length minimum-communication-energy (V-MCE) code to minimize the total energy consumption at the transmitter and receiver for point-to-point communication in OOK-based WNSNs. Specifically, the code design problems are formulated as integer nonlinear programming (INLP) problems, and the F-MCE and V-MCE codes are obtained by solving the INLP problems. The F-MCE and V-MCE codes are applicable in more scenarios than the LW code. Extensive experimental results show that the V-MCE always outperforms the LW code regarding the energy saving, while the F-MCE code achieves energy saving no less than that of the existing LW codes.

IEEE 802.11 infrastructure wireless local area network (WLAN) is increasingly popular, in which access points (APs) are applied. In a WLAN with an AP connected to the Internet, the communication between any two nodes is relayed by the AP, i.e., the AP serves all the nodes in the WLAN, which degrades throughput. In this paper, we propose a novel network coding scheme called MPOF that is able to encode multiple packets from different data flows and take data rates of links into account so that throughput is improved.

In Wireless Sensor Network (WSN), nodes are usually powered by battery and the wireless links of the nodes suffer from packet loss. It is extremely significant to develop an energy-efficient reliable data gathering scheme for WSN applications. In this paper, the Enhanced Reed-Solomon (E-RS) code, together with the intra-segment coding and the inter-segment coding, are designed. The E-RS code based data gathering scheme called the E-RS scheme is presented that adopts the intra-segment coding or the inter-segment coding. The Overall Energy Consumption (OEC) of the E-RS scheme is derived and minimized in the Optimization Problem (OP) with the constraint of data gathering ratio. The OP is able to find the optimal number of segments each carrying original information symbols, the maximum number of retransmissions in IEEE 802.15.4 Medium Access Control (MAC) layer, and the redundant degree of the E-RS code, so that the E-RS scheme achieves the minimum energy consumption while keeping data gathering ratio over a preset threshold.

It is significant to repair (or rebuilt) the damaged storage node in the distributed storage system (DSS). Recently, the network coding technique is applied to DSS to decrease the repair bandwidth. In practice, in addition to repair bandwidth, repair time is usually one of the key concerns in the DSS, which has not been investigated in the existing DSSs in which network coding is applied. In this paper, we propose the minimum-time repair (MTR) scheme, which is able to achieve the lower bound of repair time while considerably decreasing repair bandwidth. Numerical results show that MTR outperforms some available node recovery approaches in terms of repair time.

Wireless nano-sensor networks (WNSNs), which consist of nano-sensors a few hundred nanometers in size with the capability to detect and sense new types of events in nano-scale, are promising for many unique applications such as air pollution surveillance. The nano-sensors of WNSNs are highly energy-constrained, which makes it essential to develop energy-efficient communication techniques in such networks. In this paper, we focus on WNSNs employing on-off keying (OOK) modulation, whereby transmission energy minimization corresponds to the minimization of average codeword weight (ACW). We formulate an integer nonlinear programming problem to construct prefix-free codes with minimum ACW under the constraint of average codeword length (ACL) so as to minimize the transmission energy consumption while guaranteeing the throughput larger than a preset desired value. In addition, two efficient algorithms, called binary tree based weight decreasing (BT-WD) algorithm and binary tree based length decreasing (BT-LD) algorithm, are presented for constructing low-ACW prefix-free codes. The effectiveness of the proposed algorithms is verified through simulations and comparisons with the exhaustive search method. Compared with the available fixed-length low-weight codes, the designed prefix-free variable-length codes allow us to not only control the throughput more flexibly but also achieve lower transmission energy consumption in the scenarios with low or medium bit error rates.

Wireless nanosensor networks (WNSNs), which consist of a lot of nanosensors with size of just a few hundred nanometers and are able to detect and sense new types of events at the nanoscale, are promising for a lot of unique applications like intrabody drug delivery systems, air pollution surveillance, etc. One important feature of WNSNs is that the nanosensors are highly energy-constrained, which makes it essential to develop energy efficient protocols for different layers of such networks. This paper focuses on a WNSN with on-off keying (OOK) modulation and explores the problem of transmission energy minimization in it. We first propose a general minimum transmission energy (MTE) coding scheme, which maps m-bit symbols into n-bit codewords with the least number of high-bits and thus results in the lowest energy consumption per symbol for any given m and n. We further determine the optimal setting of symbol length m and codeword length n in the MTE coding scheme so as to achieve the minimum energy consumption per data bit, which serves as the lower bound of transmission energy consumption in such WNSNs. Numerical results are provided to demonstrate the efficiency of the MTE coding scheme.

In a Wireless Sensor Network (WSN), energy saving is a key issue for prolonging its runtime. Usually, a real-time application of WSN requires that data be collected within a delay constraint. There exists a tradeoff between energy saving and delay satisfaction. In this paper, a Tree-based Energy and Delay Aware Scheme (TEDAS) is proposed, which is able to maximize the lifetime of WSN while delay bound is satisfied. Based on Expected Transmission Count (ETX) of link, the TEDAS initially creates the Minimum ETX Spanning Tree (MEST) of the WSN and then the MEST is gradually improved by the proposed Adjusting Tree Algorithm (ATA) so that the optimal data gathering tree is obtained. In addition, the lifetime optimization problem (LOP) is developed for the ATA to maximize network lifetime. Moreover, the complexity of the ATA is O(N3), where N is the number of the nodes in the WSN. Simulation results show that the proposed TEDAS outperforms some existing schemes in terms of network lifetime and the volume of valid data.

In 6LoWPAN protocol, in order to deliver an IPv6 packet in the IEEE 802.15.4 based wireless personal area network (WPAN), an IPv6 packet is divided into multiple fragments, with each being incorporated in an IEEE 802.15.4 MAC frame, such that the size of each frame is no more than the Maximum Transmission Unit (MTU) of the frame. Usually, retransmission is used to reliably deliver an IPv6 packet to the destination node in the WPAN with lossy links. To improve the end-to-end packet delivery rate (PDR) of the mesh-under routing (MUR) presented in the 6LoWPAN protocol, we present a network coding based mesh-under routing (NC-MUR) scheme. The main idea underlying NC-MUR is that, the source node generates an encoded frame in addition to the M non-coded frames derived from the IPv6 packet, and then the M+1 fragments are delivered to the destination so that the destination can recover the IPv6 packet so long as any M fragments among them are received. Theoretical analyses show that NC-MUR outperforms MUR in terms of PDR and energy consumption in the cases where fragment error rate is moderate or high.

It is crucial to save power and prolong the runtime of mobile stations (STAs) in wireless local area networks (WLANs). In an infrastructure WLAN, a STA cannot be connected until it is associated with an access point (AP), which is responsible for buffering frames for all the associated STAs operating in the power saving mode. Hence, efficient memory utilization is critical for an AP to accommodate as many power-saving STAs as possible. The basic power management (BPM) scheme introduced in the IEEE 802.11 standard achieves power saving by allowing STAs not engaging in data delivery to operate in doze mode, but it does not consider the efficient use of the memory in the AP. To tradeoff power consumption for memory usage, we present an AP-priority timer-based power management (APP-TPM) scheme and develop a novel model for stochastic analysis of the proposed scheme. Based on this model, the probability distributions of the numbers of frames buffered at the AP and the average numbers of frames buffered at the AP are obtained. Moreover, a power-aware buffer management scheme (PBMS), which is based on the derived statistics, is proposed to accommodate as many STAs as possible given a fixed amount of memory in the AP while maintaining low power consumption. Simulation results show that the proposed scheme performs better than BPM in terms of memory usage in the AP.

In an IEEE 802.11 based mobile ad hoc network (MANET), a network node accesses a common wireless channel through the distributed coordinate function (DCF), which is provided at the medium access control (MAC) layer of the IEEE 802.11 standard. The binary exponential backoff (BEB) algorithm, which uses slotted contention windows, plays an important role in the DCF. This paper develops a mathematical model for analyzing the performance of the BEB algorithm, which takes into account the packet loss probability of a wireless link. Based on the developed mathematical model, we derive the backoff probability distribution of a node, the average number of backoffs of a node, the average size of a contention window, and the average packet delay. Moreover, we attempt to find the optimal value of the initial contention window size, to which a node resets its contention window size after a successful transmission, in order to avoid the oscillation of the contention window size and thus maximize the utilization of the wireless channel.

Nodes in a wireless sensor network (WSN) are usually powered by batteries. Hence, it is important to efficiently expend the battery energy of each node in the WSN so that both runtime of the nodes and the lifetime of the WSN are prolonged. An event-driven energy-conserving scheme, called adaptive power-saving scheme (APS), is proposed. APS is able to adapt the sleep duration of a node to traffic variations. We have implemented APS based on TelosW motes, TinyOS, and NesC language. Experimental results show that APS outperforms the fixed time scheme (FTS) in terms of energy consumption and packet loss ratio.

The deployment strategy for achieving differentiated coverage and probabilistic connectivity in wireless sensor networks is studied in this paper. A novel solution based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed. Simulation results show that NSGA-II based strategy can meet the desired coverage requirements and maintain connectivity in a probabilistic manner with a relatively small number of sensors. In addition, for the applications in which the coverage requirement varies in some subareas, a local genetic operation is more time efficient and needs less variation in the original disposal than a renewed global optimization.

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.

Location management (LM) is an important function in a personal communication network to track movements of mobile terminals (MTs) for call delivery. It is well-known that the total signaling cost of a distance-based LM scheme is the lowest among dynamic location management schemes for PCS networks. In this paper, we derive the joint probability distribution of two random variables: the moving distance of an MT and the number of location updates resulting from the moving distances exceeding the distance threshold. As special cases, the probability distributions of an MT's moving distances and the number of location updates during an LM interval are obtained. These statistics are generally applicable to irregular cell topologies and general cell residence time distributions. Based on the derived statistics, the optimal distance thresholds for distancebased LM schemes with blanket paging and sequential paging are solved analytically. Numeric results show that our optimized distance-based LM scheme outperforms some well-known LM schemes in total LM cost.

It is well-known that, among dynamic location management schemes, the lowest total signaling cost is achieved by the distance-based scheme, which invokes a location update when the moving distance of a mobile terminal measured in number of cells exceeds a predefined distance threshold. The cost performance of the distance-based scheme is highly dependent on the distance threshold, as the paging cost increases and location update cost decreases with the distance threshold. Hence, how to choose a suitable distance threshold is critical for a distance-based scheme to be effectively and efficiently applied. In this paper, a fuzzy distance-based location management scheme (FDLMS) is proposed, which employs a fuzzy logic controller to dynamically adjust the distance threshold for each mobile terminal so that optimal or near-optimal cost performance can be obtained regardless of mobile terminals' changing mobility and traffic patterns. Simulation results are presented to compare the cost of FDLMS with that of distance-based schemes with different fixed distance thresholds.

The total signaling cost of distance-based location management scheme, which is the lowest among dynamic location management schemes for PCS networks, can be further reduced by a sequential paging strategy that pages first the cells in which the mobile is most likely located. To enable this strategy, we derive the probability distribution of a mobile's moving distances between the last location update and the next call arrival. An efficient and effective sequential paging scheme is presented, which guarantees that a mobile can be located during the first paging step with a probability equal to or better than a predefined value. The features of the proposed model include flexible cell topologies, general cell residence time, and full use of mobile's moving pattern

Location management, which consists of location updating and location query, is a challenging topic in mobile communication. The location query of the basic location management scheme (basic scheme for short) used in personal communication services (PCS) networks, such as GSM, IS-41 and so forth, in many countries, requires to page all the cells of a location area (LA) simultaneously. Obviously, this scheme is likely to waste the system's channel resource and processing resource enormously, since the LA is constituted by many cells while the mobile only resides in one cell. This paper proposed a new location management scheme (cell layered scheme for short) that layered all the cells of each LA and paged the cells one layer after another in order of the probabilities from large to small. In addition, both the probability of the mobile residing in each layer and the average number of cell layers paged by the cell layered scheme, are derived. Generally, the cost of the location management of the cell layered scheme is less than that of the basic scheme. Furthermore, the cell layered scheme makes it possible to make efficient use of the limited frequency spectrum efficiently.