M. Mauricio Lara

Frame/Training Sequence Synchronization and DC-Offset Removal for (Data-Dependent) Superimposed Training Based Channel Estimation

Over the last few years there has been growing interest in performing channel estimation via superimposed training (ST), where a training sequence is added to the information-bearing data, as opposed to being time-division multiplexed with it. Recent enhancements of ST are data-dependent ST (DDST), where an additional data-dependent training sequence is also added to the information-bearing signal, and semiblind approaches based on ST. In this paper, along with the channel estimation, we consider new algorithms for training sequence synchronization for both ST and DDST and block (or frame) synchronization (BS) for DDST (BS is not needed for ST). The synchronization algorithms are based on the structural properties of the vector containing the cyclic means of the channel output. In addition, we also consider removal of the unknown dc offset that can occur due to using first-order statistics with a non-ideal radio-frequency receiver. The subsequent bit error rate (BER) simulations (after equalization) show a performance not far removed from the ideal case of exact synchronization. While this is the first synchronization algorithm for DDST, our new approach for ST gives identical results to an existing ST synchronization method but with a reduced computational burden. In addition, we also present analysis of BER simulations for time-varying channels, different modulation schemes, and traditional time-division multiplexed training. Finally, the advantage of DDST over (conventional, non semi-blind) ST will reduce as the constellation size increases, and we also show that even without a BS algorithm, DDST is still superior to conventional ST. However, iterative semiblind schemes based upon ST outperform DDST but at the expense of greater complexity

On the MAC/Network/Energy Performance Evaluation of Wireless Sensor Networks: Contrasting MPH, AODV, DSR and ZTR Routing Protocols

Wireless Sensor Networks deliver valuable information for long periods, then it is desirable to have optimum performance, reduced delays, low overhead, and reliable delivery of information. In this work, proposed metrics that influence energy consumption are used for a performance comparison among our proposed routing protocol, called Multi-Parent Hierarchical (MPH), the well-known protocols for sensor networks, Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Zigbee Tree Routing (ZTR), all of them working with the IEEE 802.15.4 MAC layer. Results show how some communication metrics affect performance, throughput, reliability and energy consumption. It can be concluded that MPH is an efficient protocol since it reaches the best performance against the other three protocols under evaluation, such as 19.3% reduction of packet retransmissions, 26.9% decrease of overhead, and 41.2% improvement on the capacity of the protocol for recovering the topology from failures with respect to AODV protocol. We implemented and tested MPH in a real network of 99 nodes during ten days and analyzed parameters as number of hops, connectivity and delay, in order to validate our simulator and obtain reliable results. Moreover, an energy model of CC2530 chip is proposed and used for simulations of the four aforementioned protocols, showing that MPH has 15.9% reduction of energy consumption with respect to AODV, 13.7% versus DSR, and 5% against ZTR.

A new approach to achieve multiple packet reception for ad hoc networks

An algorithm for the recovery of multiple packets is proposed in this paper. The algorithm exploits the fact that every transmitter sends an implicit training sequence along with the information to accomplish multiple user equalization and interference suppression in the challenging scenario of an asynchronous random access ad hoc network. The proposed method has the advantage of allowing the transmission of complex data over time-dispersive multipath channels. A simulation example is presented that corroborates the interference suppression capabilities of the algorithm.

An efficient Multi-Parent Hierarchical routing protocol for WSNs

Wireless sensor networks (WSNs) nodes are commonly designed to work with limited resources of memory, energy and processing. The routing protocol is one of the key components of WSNs and its features impact network performance significantly. We present an efficient Multi-Parent Hierarchical (MPH) routing protocol for wireless sensor networks; its main goal is to achieve reliable delivery of data in a single sink scenario while keeping low overhead, reduced latency and low energy consumption. The main features of MPH are self-configuration, hierarchical topology, persistence according to link quality, and source routing from sink to nodes. Network performance simulations of the MPH routing protocol are carried out and compared with two popular protocols, AODV, DSR and with the well-known algorithm ZTR (Zigbee Tree Routing). Results show that for the single sink scenario, the MPH protocol has an energy saving of 35% against AODV and DSR protocols and 8% compared with ZTR. MPH has 27% less overhead compared with AODV and DSR. And MPH presents a 10% increase in packet delivery compared with AODV, DSR and ZTR. Finally, we present a real WSN built based on the MPH protocol, which works satisfactorily, providing an experimental demonstration of the capabilities of the protocol.

Impact of the cell size and the propagation model parameters on the performance of microcellular networks

The effects of cell radius reduction and path loss model parameters on the performance of microcellular networks are studied. The performance is measured in terms of the average co-channel interference probability and reuse efficiency. The influence of reuse distance, cell size, traffic intensity, break point distance of the dual path loss law characteristics of microcells, and standard deviation of log-normal shadowed local mean on the performance parameters are investigated. Also, capacity increase due to cell radius reduction combined with dynamic channel assignment strategies (DCA) is evaluated. Our main contribution is the observation that the system performance is extremely sensitive to the propagation model parameters and depends strongly on the cell size and reuse factor. As it is expected, analytical and simulation results show that reducing the cell radius increases the cells Erlang capacity per unit area. However, this cell radius reduction implies an increase in the co-channel interference level and then a higher reuse factor may be required to keep the quality of service. On the other hand, it is shown that the system capacity increase due to the cell radius reduction is much greater in microcellular systems with DCA than in those with fixed channel assignment.

Symbol-Blanking Superimposed Training for Orthogonal Frequency Division Multiplexing systems

While the single-carrier concept of superimposed training (ST) for channel estimation has already been applied to the very popular Orthogonal Frequency Division Multiplexing (OFDM), its single-carrier enhancement (Data dependent superimposed training (DDST)) cannot be so combined with OFDM. That is because the inherent structure of OFDM means that certain input symbols will now be permanently lost (or nulled) with DDST. So here for the first time, we propose a DDST-like approach that can now be applied to OFDM — Symbol-Blanking Superimposed Training (SBST). We show that by the simple expedient of combining (prior to transmission) these nulled symbols with symbols at other subcarriers and proposing two new receiver detection algorithms, the performance of SBST can very closely approach the traditional pilot tone assisted modulation (PTAM) of OFDM — but without the concomitant reduction in data rate associated with PTAM

Carrier Frequency Offset Estimation using Data-Dependent Superimposed Training

rdquoWe address the problem of carrier frequency offset (CFO) estimation within the Data Dependent Superimposed Training (DDST) framework for channel estimation. A CFO estimator was recently developed for DDST, which uses two different data dependent training sequences, one for CFO estimation and other for channel estimation. Here, we propose a CFO estimation scheme which combines the estimates using both the data-dependent training sequences to improve the performance. Finally, simulations are presented that verify the theoretical developments.

On the Fade Duration Distribution in Nakagami Fading Channels

During almost fifty years the fade duration distribution (FDD) of random signals has been an open research topic. However, for Nakagami fading channels, and in general for the great majority of non-Gaussian processes, closed form general solutions are still unknown. In this paper we apply an orthogonal series expansion that allows to characterize the FDD. Our results show that the FDD in Nakagami wireless channels can be approximated, for both asymptotic and non-asymptotic threshold levels (C), by a simple closed form function: the Gamma distribution. This approximation is validated in different ways. We show how it is possible to compute (a priori) the parameters of the approximate Gamma distribution through the analytical fade statistics. We also examine the influence of different autocorrelation functions on the FDD.

On the second order statistics of SIR in wireless Nakagami channels

The second order statistical properties of the signal to interference ratio (SIR), namely the autocovariance function, are relevant for several studies in wireless communication channels. Formally, the autocovariance function of SIR can be obtained from its two-dimensional probability density function (PDF). However, for the traditional types of fading channels, the analytical two dimensional PDFs of SIR are rather scarce, and it is possible to say that they are either unavailable or have too complex forms. Moreover, this approach does not allow to see how the covariances of the desired signal and the interference participate in the covariance of SIR. In this paper, we show how these inconveniences can be bypassed allowing and exact analysis of the autocovariance function of SIR in Nakagami fast fading channels. The paper focuses on the efficiency of the derived analytical expression and a detailed discussion about the relevant cases.

Computational complexity of narrow band and wide band channel simulators

Some questions such as: is it convenient to simulate channel realizations with the sum of sinusoids or with the filtering approach, are addressed in this work in order to provide a guide on which algorithms and in what situations should be used in the development of channel simulators. The conclusions presented are gathered from the comparison of the methods proposed in the literature to simulate narrowband and wideband separable channels. The comparisons are performed from the point of view of computational complexity and two metrics of approximation error. We also discuss the properties inherent to the algorithms that could determine if the proposals are suitable for channel simulation, such as synthesis complexity and their capability to approximate the conditions encountered in real channels.