Channel Estimation Techniques for Quantized Distributed Reception in MIMO Systems

The Internet of Things (IoT) could enable the development of cloud multiple-input multiple-output (MIMO) systems where internet-enabled devices can work as distributed transmission/reception entities. We expect that spatial multiplexing with distributed reception using cloud MIMO would be a key factor of future wireless communication systems. In this paper, we first review practical receivers for distributed reception of spatially multiplexed transmit data where the fusion center relies on quantized received signals conveyed from geographically separated receive nodes. Using the structures of these receivers, we propose practical channel estimation techniques for the block-fading scenario. The proposed channel estimation techniques rely on very simple operations at the received nodes while achieving near-optimal channel estimation performance as the training length becomes large.Comment: Proceedings of the 2014 Asilomar Conference on Signals, Systems & Computer

Fault Tolerance using Modified Hausdroff Distance Method

In wireless sensor and actor networks (WSANs), fault detection is of prime importance where an unexpected failure should be properly identified by the network system. Since the sensor nodes are prone to failure, fault tolerance should be seriously considered in many sensor network applications. In this paper, we propose Fault Tolerance using Modified Hausdroff Distance Method (FTMHD).The nodes are randomly deployed in an M*N area. The actor node verifies whether it receives correct data from node or not. The Modified Hausdroff Distance (MHD) is used to determine lower and upper bound of correct data range to be detected by the nodes. The proposed FTMHD has better sampling fraction and compression ratio compared to existing technique