In this letter, we consider the problem of joint selection of transmitters and receivers in a distributed multi-input multi-output radar network for localization. Different from previous works, we consider a more mathematically challenging but generalized situation that the transmitting signals are not perfectly orthogonal. Taking Cramér Rao lower bound as performance metric, we propose a scheme of joint selection of transmitters and receivers (JSTR) aiming at optimizing the localization performance under limited number of nodes. We propose a bi-convex relaxation to replace the resultant NP hard non-convex problem. Using the bi-convexity, the surrogate problem can be efficiently resolved by nonlinear alternating direction method of multipliers. Simulation results reveal that the proposed algorithm has very close performance compared with the computationally intensive but global optimal exhaustive search method.