Linear programming-aided power allocation for large OCDMA networks

To provide a suitable operation in optical code division multiple access (OCDMA) networks, it is paramount to balance the powers received at the destination optical node. This work presents a solution strategy for the power allocation (PA) problem in OCDMA by rewriting it as a linear programming (LP) problem and applying two LP methods based on the Simplex method and the Interior Point method (IPM). Such LP methods proposed in the PA OCDMA context were compared with two methods available in the literature: a) hybrid ALPSO PA method, which is based on the particle swarm optimization (PSO) strategy combined with the augmented Lagrangian (AL) analytical method and the solver GUROBI; b) the high-complexity benchmark solution matrix inversion method (MIM), which is used to verify the quality of the Simplex and IPM solutions. Numerical result reveal the effectiveness and efficiency of both LP methods when compared with other competitive methods. Numerical results in terms of floating-point operations (FLOPS), normalized mean squared error (NMSE), convergence, and the evolution of the allocated power reveal the effectiveness and efficiency of both LP methods when compared with the literature methods, mainly under higher network dimensions (K >= 32 optical nodes), achieving better accuracy-complexity tradeoffs. For 32 <= K <= 512 users, the IPM has resulted in perfect feasibility (1' = 0) and little complexity, i.e., an order less in terms of Flops than Simplex, twice to five times less than MIM procedure, and at least four orders less complexity than the hybrid analytical-heuristic ALPSO method.