Dynamic Frame Length Research Articles

Heart sound classification based on log Mel-frequency spectral coefficients features and convolutional neural networks

In view of the important role of heart sound signals in diagnosing and preventing congenital heart disease, a novel method about feature extraction and classification of heart sound signals was put forward in this study. Firstly, the heart sound signals were de-noised by using the wavelet algorithm. Subsequently, the improved duration-dependent hidden Markov model (DHMM) was used to segment the heart sound signal according to the heart cycle. Then, the dynamic frame length method was used to extract log Mel-frequency spectral coefficients (MFSC) features from the heart sound signal based on the heart cycle. Afterward, the convolution neural network (CNN) was used to classify the MFSC features. Finally, the majority voting algorithm was used to get the optimal classification results. In this paper, two-classification and multi-classification models were built. An accuracy of 93.89% for two-classification and an accuracy of 86.25% for multi-classification were achieved using the novel method.

Optimal data transmission in backscatter communication for passive sensing systems

Computational Radio Frequency IDentification (CRFID) is a device that integrates passive sensing and computing applications, which is powered by electromagnetic waves and read by the off-the-shelf Ultra High Frequency Radio Frequency IDentification (UHF RFID) readers. Traditional RFID only identifies the ID of the tag, and CRFID is different from traditional RFID. CRFID needs to transmit a large amount of sensing and computing data in the mobile sensing scene. However, the current Electronic Product Code, Class-1 Generation-2 (EPC C1G2) protocol mainly aims at the transmission of multi-tag and minor data. When a large amount of data need to be fed back, a more reliable communication mechanism must be used to ensure the efficiency of data exchange. The main strategy of this paper is to adjust the data frame length of the CRFID response dynamically to improve the efficiency and reliability of CRFID backscattering communication according to energy acquisition and channel complexity. This is done by constructing a dynamic data frame length model and optimizing the command set of the interface protocol. Then, according to the actual situation of the uplink, a dynamic data validation method is designed, which reduces the data transmission delay and the probability of retransmitting, and improves the throughput. The simulation results show that the proposed scheme is superior to the existing methods. Under different energy harvesting and channel conditions, the dynamic data frame length and verification method can approach the theoretical optimum.

Fast and Reliable Burst Data Transmission for Backscatter Communications.

Computational radio frequency identification (CRFID) sensors are able to transfer potentially large amounts of data to the reader in the radio frequency range. However, the existing EPC C1G2 protocol is inefficient when there are abundant critical and emergency data to be transmitted and cannot adapt to changing energy-harvesting and channel conditions. In this paper, we propose a fast and reliable method for burst data transmission by fragmenting large data packets into blocks and we introduce a burst transmission mechanism to optimize the EPC C1G2 communication procedure for burst transmission when there are critical and emergency data to be transmitted. In addition, we utilize erasure codes to reduce Acknowledgement (ACK) delay and to improve system reliability. Our results show that our proposed scheme significantly outperforms the current fixed frame length approach and the dynamic frame length and charging time adaptation scheme (DFCA) and that the goodput is close to the theoretically optimal value under different energy-harvesting and channel conditions.

Goodput optimization via dynamic frame length and charging time adaptation for backscatter communication

Computational radio frequency identification (CRFID) sensors present a new frontier for pervasive sensing and computing. They exploit ambient light or radio frequency (RF) for energy and use backscatter communication with an RFID reader for data transfer. Unlike conventional RFID tags that only transmit identifiers, CRFID sensors need to transfer potentially large amounts of data to a reader during each contact. Existing EPC Gen2 protocol is inefficient in dealing with a small number of CRFID sensors transferring a large amount of buffered data to the RFID reader and it has no specific design for adaptation to dynamic energy harvesting and channel conditions. In this article, we propose to adopt dynamic frame length and charging time for CRFID backscatter communication, aiming to adapt to the changing energy harvesting and channel conditions and improve the system goodput. First, optimal frame length and charging time that maximizes the goodput are obtained by solving the formulated goodput optimization problem. Then we propose a dynamic frame length and charging time adaptation scheme (DFCA) that increase or decrease the frame length and charging time at runtime based on the goodput measurement. Simulations show that our proposed DFCA scheme outperforms current fixed-frame-length approach and can converge to theoretically optimal under different energy harvesting and channel conditions.

Capture-Aware Estimation for Large-Scale RFID Tags Identification

How to estimate the number of passive radio frequency identification (RFID) tags and the occurrence probability of capture effect is very important for a dynamic frame length Aloha RFID system with capture effect. The estimation would relate to setting an optimal frame length, which makes tag identification achieve higher efficiency. Under large-scale tags identification environment, the number of tags may be much greater than an initial frame length. In this scenario, existing estimates do not work well. In this letter, we propose a novel estimation method for the large-scale tags identification. The proposed method could adjust the initial frame length matched to the number of tags from only the first several slots in the frame. The advantage of the proposed method is to work better even when the number of tags is much greater. Numerical results show that, the proposed method has lower estimation errors under the large-scale tag identification. After setting an optimal frame length from the estimated results of the proposed method, furthermore, we could obtain higher identification efficiency.

Beyond the limit: A fast tag identification protocol for RFID systems

This paper presents the design, experiment test and performance evaluation of FAST, a fast tag identification protocol in RFID systems. FAST includes a collision tolerant mechanism (CTM) that can identify tags in collision slots correctly. Each tag sends a randomly selected signature in its selected slot. When multiple tags select the same slot and a collision occurs, the reader can detect all the signatures correctly by exploiting the cross correlation. It then asks tags to send their tag IDs sequentially through a series of ACK commands, leading to no collision in the tag ID transmissions. By using CTM, all the tags in the collision slots can be identified successfully if the number of tags involved conforms to the signature detection limit. FAST also includes a dynamic frame length estimation mechanism to maximize the slot utilization so as to further improve the performance of tag identification. Theoretical analysis and experimental results from the USRP2 testbed demonstrate the feasibility of FAST. Simulation results show that FAST outperforms other protocols dramatically.

Channel-Slot Aggregation Diversity Based Slot Reservation Scheme for Cognitive Radio Ad Hoc Networks

In cognitive radio (CR) ad hoc networks, spectrum efficiency and energy efficiency are vitally important because spectrum availability is opportunistic in nature and mobile CR nodes usually have limited energy. Aiming to improve network throughput along with improving spectrum and energy efficiencies, this paper proposes a channel-slot aggregation diversity based slot reservation (CADSR) scheme by which each CR node can utilize multiple slots in different channels simultaneously and efficiently utilize the power control mechanism with only a single CR transceiver. The proposed scheme dynamically assigns channel-slots to CR nodes using the diversity technique according to the topology density of the network and the bandwidth requirement, allowing CR nodes to join and leave the network at any time in a distributed way. A dynamic frame length expansion and shrinking scheme has also been introduced that improves the slot utilization. Extensive simulation results show that the proposed mechanism achieves significant performance improvement in network throughput, energy efficiency, and end-to-end delay.

Capture-Aware Estimation for the Number of RFID Tags with Lower Complexity

Capture effect is very common in wireless communication systems. In a passive radio frequency identification (RFID) system, even though multiple tags backscatter their signals to a reader simultaneously, one of the tags will be successfully identified due to the capture effect. In this letter, we propose an algorithm which will optimize the identification efficiency of a dynamic frame length ALOHA RFID protocol under capture effect. The proposed algorithm estimates the number of tags and the probability of capture effect. From these parameters, an optimal frame length can be obtained. The advantage of the algorithm is that it does not need many steps to search an extreme value for the estimation. It thus reduces the computational complexity. Computer simulation results show that the proposed method's identification efficiency is almost identical to existing algorithms, but at lower computational complexity.

Medium Access Control with Dynamic Frame Length in Wireless Sensor Networks

Wireless sensor networks consist of sensor nodes which are expected to be battery-powered and are hard to replace or recharge. Thus, reducing the energy consumption of sensor nodes is an important design consideration in wireless sensor networks. For the implementation of an energy-efficient MAC protocol, a Sensor-MAC based on the IEEE 802.11 protocol, which has energy efficient scheduling, has been proposed. In this paper, we propose a Dynamic S-MAC that adapts dynamically to the network-traffic state. The dynamic S-MAC protocol improves the energy consumption of the S-MAC by changing the frame length according to the network-traffic state. Using an NS-2 Simulator, we compare the performance of the Dynamic S-MAC with that of the S-MAC protocol.

A Learning Automata-Based Cognitive Radio for Clustered Wireless Ad-Hoc Networks

In current wireless networks, the radio systems are regulated by a fixed spectrum assignment strategy. This policy partitions the whole radio spectrum into a fixed number of radio ranges, each exclusively assigned to a specific user. Such a spectrum assignment strategy leads to an undesirable condition under which some systems only use a small portion of the allocated spectrum while the others have very serious spectrum insufficiency. The learning automata-based cognitive radio which is proposed in this paper is a highly potential technology to address the spectrum scarcity challenges in wireless ad hoc networks. This paper proposes a learning automata-based dynamic frame length TDMA scheme for slot assignment in clustered wireless ad-hoc networks with unknown traffic parameters, where the intra-cluster communications are scheduled by a TDMA scheme, and a CDMA scheme is overlaid on the TDMA to handle an interference-free inter-cluster communication. In this method, each cluster-head is responsible for a collision-free slot assignment within the cluster and determines the input traffic parameters of its own cluster members. It then takes these traffic parameters into consideration for an optimal channel access scheduling in the cluster. The medium access control layer in each cluster is based on a time division multiple access (TDMA) scheme, in which each host is assigned a fraction of the TDMA frame proportional to its traffic load. The simulation experiments show the superiority of our proposed slot assignment algorithm over the existing methods in terms of the channel utilization, control overhead, and throughput, specifically, under bursty traffic conditions.

An efficient cluster-based CDMA/TDMA scheme for wireless mobile ad-hoc networks: A learning automata approach

In this paper, we design a dynamic frame length CDMA/TDMA scheme for clustered wireless ad hoc networks with unknown traffic parameters. In this scheme, the collision-free intra-cluster communications are organized by the cluster-heads using a TDMA scheme, and a CDMA scheme is overlaid on the TDMA to organize the interference-free inter-cluster communications. Therefore, to design such a scheme, we encounter three important problems, namely cluster formation, code assignment, and slot assignment. In this paper, we propose three algorithms to solve the addressed problems based on learning automata. In our scheme, by the proposed clustering algorithm, the wireless hosts are grouped into non-overlapping clusters. Then, by the proposed code assignment algorithm (considering the concept of code spatial reuse), an interference-free code is assigned to each cluster. Finally, by the slot assignment algorithm, each cluster member is assigned a fraction of TDMA frame proportional to its traffic load. The simulation results show that the proposed CDMA/TDMA scheme outperforms the existing methods in terms of almost all metrics of interest, specifically, under bursty traffic conditions.

An Accurate Tag Estimate Method for Improving the Performance of an RFID Anticollision Algorithm Based on Dynamic Frame Length ALOHA

In a radio-frequency identification (RFID) system, the dynamic frame length ALOHA protocol is widely adopted to solve the anticollision problem. Analysis for the anticollision problem can be divided into two primary parts. The concern of the first part is how to precisely estimate the number of tags. The other part involves determination of dynamic frame length to achieve maximum throughput or channel usage efficiency. In this paper, we present an accurate method for estimating tag quantity. This method is based on the maximum <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">posteriori</i> probability decision. We also derive the optimal frame length using radio channel efficiency. Simulation results indicate the tag estimate error of the proposed method is less than 4%. Use of our proposed tag estimate method together with optimal frame length can achieve close to the theoretical maximum throughput of the framed ALOHA algorithm.

Dynamic frame length channel assignment in wireless multihop ad hoc networks

A good channel assignment scheme in a multihop ad hoc network should not only guarantee successful data transmissions without collisions but also enhance the channel spatial reuse to maximize the system throughput. From the channel assignment schemes in time division multiple access (TDMA) slot assignment protocols developed in previous studies, we have found that these protocols do not have a convenient frame length shrink scheme after the expansion of the frame length. As the network size grows, the frame length expands quickly, particularly when we set the frame length as a power of two. A very long frame may result in poor channel utilization when it contains many unused slots. In this paper, we propose a dynamic frame length expansion and recovery method called dynamic frame length channel assignment (DFLCA). This strategy is designed to make better use of the available channels by taking advantage of the spatial reuse concept. In DFLCA, the increase in the spatial reuse is achieved by adding certain amount of control overhead. We show that the bandwidth saved due to the channel spatial reuse is larger than the additional bandwidth spent on the control overhead.

Nonlinear optimization for energy efficiency in IEEE 802.11a wireless LANs

Link-adaptation scheme has been recognized as an effective way to improve the performance of energy efficiency of the IEEE 802.11a wireless local-area networks (WLANs). In this paper, we propose a new link-adaptation scheme for energy efficiency by dynamically adjusting the data transmission rate according to network load and channel quality. We first give an overview of the IEEE 802.11a orthogonal frequency domain multiplexing (OFDM) physical layer and the distributed coordination function (DCF) of the IEEE 802.11 MAC. Then, based on the theoretical goodput analysis, we proposed a new method to enhance the energy efficiency via optimizing the goodput performance using nonlinear optimization with constraints. Despite the nonlinearity in the objective function and the constraints, we show that the energy efficiency optimization can be efficiently solved for global optimality through a convex optimization technique. Our simulation results show that our link-adaptation scheme enhances the energy efficiency as well as the goodput performance of an IEEE 802.11a wireless LAN through dynamic frame length control, contention window (CW) selection, and PHY rate selection, depending on the wireless channel condition. Moreover, the proposed scheme can be extended to address some similar problems in other kinds of networks, such as congestion control, admission control, and power control.

Dynamic Frame Length ALOHA

Adding frame structure to slotted ALOHA makes it very convenient to control the ALOHA channel and eliminate instability. The frame length is adjusted dynamically according to the number of garbled, successful, and empty timeslots in the past. Each terminal that has a packet to transmit selects at random one of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</tex> timeslots of a frame. Dynamic frame length ALOHA achieves a throughput (expected number of successful packets per timeslot) of 0.426 which compares favorably with the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1/e (\approx0.368)</tex> upper bound of ordinary slotted ALOHA.