  In this paper, we investigate the energy efficiency of conventional
collaborative compressive sensing (CCCS) scheme, focusing on balancing the
tradeoff between energy efficiency and detection accuracy in cognitive radio
environment. In particular, we derive the achievable throughput, energy
consumption and energy efficiency of the CCCS scheme, and formulate an
optimization problem to determine the optimal values of parameters which
maximize the energy efficiency of the CCCS scheme. The maximization of energy
efficiency is proposed as a multi-variable, non-convex optimization problem,
and we provide approximations to reduce it to a convex optimization problem. We
highlight that errors due to these approximations are negligible. Later, we
analytically characterize the tradeoff between dimensionality reduction and
collaborative sensing performance of the CCCS scheme -- the implicit tradeoff
between energy saving and detection accuracy, and show that the loss due to
compression can be recovered through collaboration which improves the overall
energy efficiency.
