Jiening Zhan

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Linear receivers are often used to reduce the implementation complexity of multiple-antenna systems. In a traditional linear receiver architecture, the receive antennas are used to separate out the codewords sent by each transmit antenna, which can then be decoded individually. Although easy to implement, this approach can be highly suboptimal when the(More)
The Compute-and-Forward approach has been proven to be very beneficial for communication over Gaussian networks. While the theoretical results are promising, it is still not completely understood how to best apply this scheme in practice. The objective of this work is to provide a low complexity scheme suitable for Compute-and-Forward. The scheme is based(More)
We propose a new framework for MIMO decoding based on a recently developed technique for reliably conveying linear equations over wireless channels. Each transmit antenna sends an independent data stream using the same linear code. As a result, any integer combination of the codewords is itself a codeword. Each receive antenna observes a random(More)
In many network communication scenarios, a relay in the network may only need to recover and retransmit an equation of the transmitted messages. In previous work, it has been shown that if each transmitter employs the same lattice code, the interference structure of the channel can be exploited to recover an equation much more efficiently than possible with(More)
Linear receivers are often used in multiple-antenna systems due to ease of implementation. However, traditional linear receivers such as the Decorrelator and the linear minimummean squared error (MMSE) receiver often have a significant performance loss compared to the optimal joint maximum likelihood (ML) receiver. In previous work, we proposed the(More)
We show that the recently proposed integer-forcing linear receiver provides an attractive approach to the problem of mitigating external interference in MIMO channels. The integer-forcing receiver proceeds by first decoding a set of full rank integer linear combinations of the data streams. The resulting full rank equations are then inverted to find the(More)
In the linear function computation problem, multiple source nodes communicate across a relay network to a single destination whose goal is to recover a linear function of the original source data. For the case when the relay network is a deterministic network, a duality relation is established between the linear function computation problem and the(More)
Based on the recent compute-and-forward technique , a novel communication strategy is proposed under which functions of the channel state information are forwarded along the network. Those functions are chosen such that on the one hand, they can be efficiently forwarded, and on the other hand, they are maximally useful to the final decoder of the message.(More)