Marcelo Eduardo Pellenz

An Analytical Model for Energy Efficiency of Error Control Schemes in Sensor Networks

This paper analyzes the energy efficiency of wireless sensor networks using different error control schemes. An analytical model is presented to evaluate the energy efficiency in Nakagami-ra fading channels. The model is applied to error control schemes of Bluetooth technology. Some custom error control schemes and adaptive techniques using different FEC and ARQ strategies are analyzed. Performance results are obtained through analysis for networks with different number of hops and fading channel conditions.

Error control coding in wireless sensor networks

Wireless Sensor Networks (WSN) are usually a set of battery-supplied small devices. One of the main challenges in deploying WSN is to improve energy-efficiency and lifetime of the nodes while keeping communication reliability. Transmissions over the wireless channel may experience many impairments, like random noise and fading, increasing the bit error rate at reception, causing several retransmissions, and consuming extra energy from the node. In order to minimize the harmful effects of the radio channel, error control strategies using packet retransmission and error correcting codes are commonly utilized. In this work we investigate the trade-off between transmission and processing energy consumption in a sensor node employing convolutional codes. Through this study we can identify and select the appropriate complexity of the error control code to be used in each sensor node, in order to maximize the network lifetime.

Hybrid ARQ scheme based on recursive convolutional codes and turbo decoding

We propose a hybrid ARQ scheme using recursive convolutional codes and the turbo principle. In the first transmission the system encodes the data through a systematic recursive convolutional encoder. In the second transmission data is interleaved prior to being encoded by a recursive convolutional encoder. Then, from the second transmission on the receiver operates as a turbo decoder. The proposed method is compared with a popular scheme known in the literature. It is shown that, while spending the same energy for transmission, the proposed scheme presents both smaller FER and decoding complexity.

Using Cognitive Radio for Improving the Capacity of Wireless Mesh Networks

We propose the application of the overlay cognitive radio model to the communication of links within a wireless mesh networks. Based on the communication paradigm proposed by Jovicic and Viswanath, it is possible to have two concurrent transmissions in a given interference region. As as result, considerable network capacity gains are achieved. For the simple case of a network with a chain topology, the gains are as high as 33%.

An Efficient Distributed Algorithm for Constructing Spanning Trees in Wireless Sensor Networks

Monitoring and data collection are the two main functions in wireless sensor networks (WSNs). Collected data are generally transmitted via multihop communication to a special node, called the sink. While in a typical WSN, nodes have a sink node as the final destination for the data traffic, in an ad hoc network, nodes need to communicate with each other. For this reason, routing protocols for ad hoc networks are inefficient for WSNs. Trees, on the other hand, are classic routing structures explicitly or implicitly used in WSNs. In this work, we implement and evaluate distributed algorithms for constructing routing trees in WSNs described in the literature. After identifying the drawbacks and advantages of these algorithms, we propose a new algorithm for constructing spanning trees in WSNs. The performance of the proposed algorithm and the quality of the constructed tree were evaluated in different network scenarios. The results showed that the proposed algorithm is a more efficient solution. Furthermore, the algorithm provides multiple routes to the sensor nodes to be used as mechanisms for fault tolerance and load balancing.

Lightweight Data Compression in Wireless Sensor Networks Using Huffman Coding

This paper presents a lightweight data compression method for wireless sensor networks monitoring environmental parameters with low resolution sensors. Instead of attempting to devise novel ad hoc algorithms, we show that, given general knowledge of the parameters that must be monitored, it is possible to efficiently employ conventional Huffman coding to represent the same parameter when measured at different locations and time periods. When the data collected by the sensor nodes consists of integer measurements, the Huffman dictionary computed using statistics inferred from public datasets often approaches the entropy of the data. Results using temperature and relative humidity measurements show that even when the proposed method does not approach the theoretical limit, it outperforms popular compression mechanisms designed specifically for wireless sensor networks.

Brief survey on full-duplex relaying and its applications on 5G

This paper gives an brief survey on full-duplex relaying. First, we discuss the importance of full-duplex communications and its major drawback, known as self-interference. We provide a overview of the state-of-the-art on self-interference cancellation techniques from antenna design to digital cancellation. Then, we assess current developments in full-duplex relaying, some promising protocols and we discuss some of the performance analysis carried out so far. Finally, we discuss the importance of full-duplex, more specifically full-duplex relaying, on 5G networks.

Optimizing the Code Rate of Energy-Constrained Wireless Communications With HARQ

Retransmissions due to decoding errors have a big impact on the energy budget of low-power wireless communication devices, which can be reduced by using hybrid automatic repeat request (HARQ) techniques. Nevertheless, this reduction comes at the cost of extra energy consumption introduced by the added computational load. No complete analysis of the tradeoff between retransmissions reduction and baseband consumption of low-power communications over fading channels has been reported so far. In this paper, we study the energy efficiency achievable by HARQ schemes when the code rate of the error-correcting code is optimized. For this purpose, we develop an energy consumption model that focuses on simple HARQ (S-HARQ) and Chase combining (HARQ-CC) transmissions, which are studied under fast-fading and block-fading scenarios with Nakagami-m fading. The retransmission statistics are analyzed, and expressions for the expected number of transmission trials are derived. Using this framework, it is shown that transmission schemes with high diversity gain are the most efficient choice for long range transmissions, which in our case correspond to HARQ-CC and codes with low code rate. On the other hand, schemes with good multiplexing capabilities are optimal for short link distances, which in our analysis correspond to S-HARQ and high code rates. It is also shown that HARQ-CC can effectively extend the transmission range of a low-power communication device.

Throughput performance of parallel and repetition coding in incremental decode-and-forward relaying

The throughput performance of cooperative repetition and parallel coding in incremental decode-and-forward is investigated. Four transmission methods are considered: parallel coding with and without distributed space-time coding (PC-ST and PC, respectively); and repetition coding with and without Chase combining at the destination (RC and SC, respectively). The analysis is based on the mutual information seen at the receiver for each scheme. Exact expressions for the outage probability and throughput for all methods are derived. Both ad-hoc and infra-structured relaying scenarios are investigated. Results show that SC can perform very close to RC, PC and PC-ST in terms of throughput, specially in the case of infra-structured relaying or adequate power and rate allocation. The conclusion is that SC would be a better option in practice, since it requires a simpler receiver than PC-ST, PC, and RC.

An efficient polling strategy for Bluetooth piconets using channel state information

Bluetooth is an emerging technology for personal wireless communications and is being applied in many scenarios. We investigate the data scheduling policy for Bluetooth piconets. In general the performance evaluation of most piconet scheduling algorithms recently proposed do not consider the packet losses in the wireless channel. However in environments with high interference or mobility, the channel conditions can mitigate the performance of the polling strategies. We propose a new piconet scheduling algorithm based on the estimated channel state information. The channel is modeled using the Nakagami-m distribution. The channel quality estimation is based on the received signal-to-noise ratio (SNR) and on the Nakagami fading parameter m. These two metrics are used by the scheduling algorithm to define the best polling strategy. Simulation results demonstrate the good algorithm performance for different traffic conditions.