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Microseismic monitoring has been used in geo-energy related activities, such as shale-gas exploitation, mining, deep geothermal exploitation, geotechnical and structural engineering, for detecting and locating fractures, rock failures and micro-earthquakes. The success of microseismic monitoring depends on reliable detection and location of the recorded microseismicity. Multichannel coherence migration (MCM) is a detection and location waveform migration-based approach which does not require phase picking, identification and association and performs well on noisy data. Its caveat is a high computational cost, which impedes its application of MCM on large data sets or for real-time monitoring. To address this issue, we propose an improved approach, the multichannel coherence migration grid search (MCMgs), by introducing an adaptive grid optimization technique. Based on results from synthetic and real data, we show that MCMgs reduces the computation time up to 64 times. In addition, MCMgs generates multiple maximum coherence values with various grid sizes instead of a single (maximum) coherence value that links to a single gridpoint and size, thus resulting in more accurate locations. Our simulation results on different deployment geometries demonstrate that MCMgs is effective even with a small number of recordings available—a minimum of seven. We conduct a sensitivity analysis to assess how the detectability of events is affected by the spatial arrangement of the deployed monitoring array. If a limited number of seismometers are available for deployment, our analysis favours a patch array deployment geometry. We show that 12 seismometers deployed at a patch array geometry can have similar detection and localization capability as a large rectangular array of more than 100 seismometers but at a much lower computational and deployment cost. [ABSTRACT FROM AUTHOR]

The authors propose two practical power- and bandwidth-efficient systems based on amplify-and-forward and decode-and-forward schemes to address the problem of information exchange via a relay. The key idea is to channel encode each source's message by using a high-performance non-binary turbo code based on partial unit memory codes to enhance the bit-error-rate performance, then reduce the energy consumption and increase spectrum efficiency by using network coding (NC) to combine individual nodes' messages at the relay before forwarding to the destination. Two simple and low complexity physical layer NC schemes are proposed based on combinations of received source messages at the relay. The authors also present the theoretical limits and numerical analysis of the proposed schemes. Simulation results under additive white Gaussian noise confirm that the proposed schemes achieve significant bandwidth savings and fewer transmissions over the benchmark systems which do not resort to NC. Theoretical limits for capacity and signal-to-noise ratio behaviour for the proposed schemes are derived. This study also proposes a cooperative strategy that is useful when insufficient combined messages are received at a node to recover the desired source messages, thus enabling the system to retrieve all packets with significantly fewer retransmission request messages. [ABSTRACT FROM AUTHOR]

In this paper we introduce a novel linear precoding technique. The approach used for the design of the precoding matrix is general and the resulting algorithm can address several optimization criteria with an arbitrary number of antennas at the user terminals. We have achieved this by designing the precoding matrices in two steps. In the first step we minimize the overlap of the row spaces spanned by the effective channel matrices of different users using a new cost function. In the next step, we optimize the system performance with respect to specific optimization criteria assuming a set of parallel single- user MIMO channels. By combining the closed form solution with Tomlinson-Harashima precoding we reach the maximum sum-rate capacity when the total number of antennas at the user terminals is less or equal to the number of antennas at the base station. By iterating the closed form solution with appropriate power loading we are able to extract the full diversity in the system and reach the maximum sum-rate capacity in case of high multi-user interference. Joint processing over a group of multi-user MIMO channels in different frequency and time slots yields maximum diversity regardless of the level of multi-user interference. [ABSTRACT FROM PUBLISHER]

Real-time multimedia multicast over wireless networks is an exciting application that has generated a lot of interest recently. Its main challenge lies in the stringent bandwidth and time-delay requirements of real-time multimedia and severe impairments of the wireless channels. We develop a network-aware cross-layer design for multimedia multicast over heterogeneous wireless-wireline networks, that leverages the knowledge on network information theory, multimedia processing, error control, and networking. In particular, the encoded multimedia data are broadcast to multiple Internet servers over a wireless radio link. Each server merely compresses the signal it has received using distributed source coding by exploiting mutual correlation among signals received at different servers. The receiver collects bitstreams from the servers before performing joint decoding. We provide an algorithm for optimal nonuniform scalar quantizer design at the server side that minimizes the required rate under the decoder bit error rate constraint. For scalable multimedia codes, we develop a joint source-channel coding scheme which combines error-protection at the base station and distributed source coding at the servers. Our experimental results show significant performance improvements over conventional solutions due to spatial diversity and distributed source coding gains. [ABSTRACT FROM PUBLISHER]