.png){kind=icon}
.png){kind=icon}
Return
Signal Alignment: Enabling Physical Layer Network Coding for MIMO Networking
.png){kind=icon}
PRE
AI
DOI：10.1109/TWC.2013.050313.121454.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We apply signal alignment (SA), a wireless communication technique that enables physical layer network coding (PNC) in multi-input multi-output (MIMO) wireless networks. Through calculated precoding, SA contracts the perceived signal space at a node to match its receive capability, and hence facilitates the demodulation of linearly combined data packets. PNC coupled with SA (PNC-SA) has the potential of fully exploiting the precoding space at the senders, and can better utilize the spatial diversity of a MIMO network for higher system degrees-of-freedom (DoF). PNC-SA adopts the idea of 'demodulating a linear combination' from PNC. The design of PNC-SA is also inspired by recent advances in IA, though SA aligns signals not interferences. We study the optimal precoding and power allocation problem of PNC-SA, for SNR (singal-to-noise-ratio) maximization at the receiver. The mapping from SNR to BER is then analyzed, revealing that the DoF gain of PNC-SA does not come with a sacrifice in BER. We then design a general PNC-SA algorithm in larger systems, and demonstrate general applications of PNC-SA, and show via network level simulations that it can substantially increase the throughput of unicast and multicast sessions, by opening previously unexplored solution spaces in multi-hop MIMO routing.
Keywords:
Network coding
physical layer letwork coding
interference alignment
signal alignment
MIMO networks
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
10.7
Papers:
1.3W
Citations:
5.3W