Hua An Zhao

FFT based automatic species identification improvement with 4-layer neural network

In this paper, an automatic species identification system has been developed. Recoded data was segmented, processed, features taken out, and identified by an automatic operation. A feature quantity method based on FFT with derivative of frequency band power making use of 4-layer neural network is proposed. Comparison of the results with the 4-layer neural network has been performed on wild bird species identification based on sound data which has proved promising.

Nearest neighbor relay selection with adaptive modulation for improved throughput and scalability of cooperative wireless networks

Cooperative communication is establishing itself as a viable means of performance enhancement for wireless networks. It provides diversity by emulating multi-input and multi-output (MIMO) system for devices that are spatially too small to harbor multiple antennas. Since mobility and easy handling require terminal miniaturization, cooperative communication is required to fill the gap for MIMO. Conventional cooperative protocols such as amplify-and-forward (AF) and decode-and-forward (DF) attain diversity gain at the cost of reduced spectral efficiency which as a result brings about reduced throughput. In addition, relay selection mechanisms play important role in attaining the required performance. In this paper, adaptive modulation is applied to improve the throughput performance of AF wireless cooperative strategy. Furthermore, a relay selection mechanism known as Nearest Neighbor Selection (NNS) is suggested for scalable implementation of wireless cooperation among users. The source and relay respond to the channel state information (CSI) obtained from the destination as a feedback to change the M-ary Quadrature Amplitude Modulation (M-QAM) types. Operating regions for each modulation type are determined by bit error rate (BER) constraint set by the destination which makes use of maximal ratio combining (MRC) of the signals received from the source and relay. Simulation results show that modulation adaptive cooperation performs better than the non adaptive counterpart in overall throughput and NNS is a promising approach for user scalability of adaptive cooperation.

An improved detection algorithm based on Lattice reduction for MIMO system

Lattice reduction (LR) is a powerful technique for improving the performance of linear MIMO detection methods. The efficient LR algorithms can largely improve the performance of the linear detectors (LDs). However, there are two problems involved in the LR-aided detection algorithms. One is that, the reduced basis is still not orthogonal, and most existing LR-aided algorithms devote to find a near orthogonal matrix. The other one is that the original constellation is no longer the feasible set of the detected symbol, and the elements of the new symbol vector are correlated. In this paper, an improved LR-aided algorithm (ILRA) considering the feasible set of the new symbol has been proposed. We verify that the feasible set is the integer set in a polyhedron. Eliminating the integer constraint, we simplify the detection to a convex optimization problem. Finally, we get the new detected symbol by solving the convex optimization problem. The simulation results show that our algorithm can achieve significant performance gain over the previous LR-aided LDs, especially in the low-order QAM system.

Optimum power allocation based adaptive modulation for cooperative wireless networks

Cooperative communication is becoming a viable means of performance enhancement for wireless networks. It provides diversity by emulating multi-input and multi-output (MIMO) system for devices that are spatially too small to harbor multiple antennas. Conventional cooperative protocols such as amplify-and-forward (AF) and decode-and-forward (DF) attain diversity gain at a cost of reduced spectral efficiency which becomes a cause for reduced throughput. To fight this reduction in throughput different approaches can be implemented. In this paper, adaptive modulation in conjunction with optimal power allocation is applied both at the source and the relay. In the process, the bit error rate (BER) at the destination, after performing optimal power allocation, is used as a constraint to determine the operating SNR regions of different M-QAM modulation types to be applied by the source and relay. Experimental results on AF strategy show that adaptive modulation with optimal power allocated BER as a constraint has better performance over the equal power allocated counterpart. The spectral efficiency and throughput performance differences become even higher when channel conditions worsen.

Adaptive modulation for cooperative wireless communication systems

Cooperative wireless communication network provides diversity by emulating multi-input and multi-output (MIMO) system for devices that are spatially too small to harbor multiple antennas. Since mobility and easy handling require terminal miniaturization, cooperative communication is required to fill the gap for MIMO. Conventional cooperative protocols such as amplify-and-forward (AF) and decode-and-forward (DF) attain diversity gain at the cost of reduced spectral efficiency which as a result brings about reduced throughput. In this paper, adaptive modulation is applied to improve the throughput performance of AF wireless cooperative strategy. The source and relay respond to the channel state information (CSI) obtained from the destination as a feedback to change M-QAM types. Simulation results show that modulation adaptive cooperation performs better than the non adaptive counterpart in overall throughput.

Relay selection and power allocation in parallel and non-parallel OFDM relay networks

This paper focuses on relay selection, subcarrier selection and power allocation (PA) in two-hop multi-relay networks in frequency-selective (FS) fading channel. The multiple relays adopt amplify-and-forward (AF) protocol and are subject to an aggregate power constraint. In order to maximize the instantaneous information rate of the system, both parallel mode (all the relays transmit signals simultaneously) and non-parallel mode (the relays transmit signals sequentially) are analyzed. In the parallel mode, compared with some other previous optimal PA work, our proposed optimal subcarrier selection (OSS) scheme and optimal relay selection (ORS) scheme both can get a better performance in terms of the instantaneous information rate and have a lower complexity. In the non-parallel mode, though our OSS scheme gets a little worse performance than the previous optimal scheme in terms of the rate, it has a much lower complexity. Thus, as for the non-parallel mode our OSS scheme is more suitable for some real-time transmissions. The simulations are also provided to validate the proposed schemes.

A nearest neighbor search algorithm for LR-LD on high SNR

The faster decoding algorithm is still required in multiple-input multiple-output (MIMO) wireless communication technology. Lattice reduction (LR) technique can improve the performance of linear MIMO detection methods. LLL (Lenstra-Lenstra-Lovasz) algorithm is one of the LR techniques and it has being extensively used for better basis of channel matrix by removing noise. LR-aided detection algorithms involve two problems. The first problem is that the reduced basis is still non-orthogonal and most algorithms are devoted for finding a near orthogonal matrix. The second problem is that the feasible set of the detected symbol cannot be found without huge operation. In this paper, we propose a new algorithm which considers unknown transformed symbol to search the neighboring points on transformed basis of the channel matrix. This paper mainly focuses on the second problem to resolve the poor accuracy particularly in high signal-to-noise ratio (SNR). Our proposed algorithm can achieve better BER performance with low complexity and it is proven by simulations.

Low outage probability throughput improvement for cooperative wireless networks by utilizing channel state information

Cooperative communications is an attractive feature for the upcoming high speed wireless networks. It provides diversity for devices that are incapable of harboring multiple antennae by emulating multiple-input-multiple-output (MIMO) system providing virtual antenna array. There are different strategies of cooperation already such as amplify-and-forward (AF) and decode-and-forward (DF). Although the implementation of these strategies is simple, their utilization of the channel state information (CSI) for performance improvement is generally poor. As a result, alternative strategies are required to improve the throughput while keeping the outage and bit error rate (BER) low. In this paper an approach, based on previously existing strategies, called CSI directed estimate and forward (CDEF) strategy is proposed to improve throughput at low outage probability. It will be shown that this new strategy attains better BER and outage performances compared to AF and DF. Simulation results also show that it has better throughput performance at low outage probability as well.

CSI assisted and modulation adaptive wireless cooperation for increased spectral efficiency

Cooperative communications is a very important mechanism to provide diversity for devices that are incapable of harboring multiple antennae by emulating MIMO system. Different strategies of cooperation exist such as amplify-and-forward (AF) and decode-and-forward (DF). Although cooperation is a viable means of fighting multi path fading, it inherently induces a reduction in spectral efficiency which is against the need for increased data rate of wireless networks. In this paper, adaptive modulation is applied on existing cooperative protocols (AF and DF) as an approach to compensate for spectral efficiency loss while cooperating. In addition, an approach based on the previously existing ones called CSI directed estimate and forward (CDEF) strategy that utilizes CSI better and results in better BER performance with improved spectral efficiency is proposed. Simulation results also confirm the improvements, highlighting a promising approach to satisfy high data rate demands by current and future wireless networks.

Wavelet transform digital sound processing to identify wild bird species

The application of digital signal processing for detection and preservation of different species has been progressing rapidly. In this paper, one such better approach as applied to wild bird species is presented. Feature extraction is done by first performing wavelet transform on sampled bird sounds. After which frequency conversion and determination of mean value that determine the strength of the frequency ingredient is obtained; furthermore, the uniqueness of the modulation spectrum is used as an additional input for the detection mechanism of the birdcalls frequency. The obtained feature quantities then become input to the neural network to simplify classification of nocturnal wild bird species.