  User cooperation based multi-hop wireless communication networks (MH-WCNs) as
the key communication technological component of mobile social networks (MSNs)
should be exploited to enhance the capability of accumulating data rates and
extending coverage flexibly. As one of the most promising and efficient user
cooperation techniques, network coding can increase the potential cooperation
performance gains among selfishly driven users in MSNs. To take full advantages
of network coding in MH-WCNs, a network coding transmission strategy and its
corresponding channel estimation technique are studied in this paper.
Particularly, a $4-$hop network coding transmission strategy is presented
first, followed by an extension strategy for the arbitrary $2N-$hop scenario
($N\geq 2$). The linear minimum mean square error (LMMSE) and
maximum-likelihood (ML) channel estimation methods are designed to improve the
transmission quality in MH-WCNs. Closed form expressions in terms of the mean
squared error (MSE) for the LMMSE channel estimation method are derived, which
allows the design of the optimal training sequence. Unlike the LMMSE method, it
is difficult to obtain closed-form MSE expressions for the nonlinear ML channel
estimation method. In order to accomplish optimal training sequence design for
the ML method, the Cram\'{e}r-Rao lower bound (CRLB) is employed. Numerical
results are provided to corroborate the proposed analysis, and the results
demonstrate that the analysis is accurate and the proposed methods are
effective.
