In this paper, we propose using spatial diversity via multiple node-disjointed lightpaths at the optical layer to achieve ultra-reliable communication with low delay between any source-destination pair in all-optical networks. Using a doubly stochastic point process model and a “genie-aided” receiver, we obtain an exponentially tight error probability bound for the lightpath diversity scheme under an independent lightpath failure model. Error probability of the proposed scheme can be designed to be significantly lower than that of a system without lightpath diversity, and system parameters (e.g., the number of lightpaths) can be optimized to achieve efficient utilization of a limited amount of transmitted optical energy. In particular, at the optimum operating point, each lightpath is allocated an optimum average number of signal photons per bit and is biased to have an effective error probability

if the decision is based on that path alone, where

is the lightpath failure probability. We also investigate the tradeoff between the error probability and the implementation complexity within the class of all “structured” receivers. We derive receiver architectures for both the optimal receiver, which has the best error performance but complicated receiver architecture, and the equal-gain-combining (EGC) receiver, which has suboptimum error performance but simpler receiver architecture. Closed-form error bounds for both receivers are obtained and compared with the “genie-aided” limit of the lightpath diversity scheme. Performance comparison shows that the simpler equal-gain-combing receiver provides similar performance as the optimal receiver in the regime of high signal-to-noise photon rate ratio (

, where

is the signal photon rate per path,

is the noise photon rate per path), and performs slightly worse than the optimal receiver in the low and medium signal-to-noise photon rate ratio regimes. It indicates that the simpler EGC receiver is preferred over the complicated optimum receiver in practical receiver design.