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In this paper, we study a RAN resource-slicing problem for energy-efficientcommunication in an orthogonal frequency division multiple access (OFDMA) basedmillimeter-wave (mmWave) downlink (DL) network consisting of enhanced mobilebroadband (eMBB) and ultra-reliable low-latency communication (URLLC) services.Specifically, assuming a fixed set of predefined beams, we address an energyefficiency (EE) maximization problem to obtain the optimal beam selection,Resource Block (RB), and transmit power allocation policy to serve URLLC andeMBB users on the same physical radio resources. The problem is formulated as amixed-integer non-linear fractional programming (MINLFP) problem consideringminimum data rate and latency in packet delivery constraints. By leveraging theproperties of fractional programming theory, we first transform the formulatednon-convex optimization problem in fractional form into a tractable subtractiveform. Subsequently, we solve the transformed problem using a two-loop iterativealgorithm. The main resource-slicing problem is solved in the inner looputilizing the difference of convex (DC) programming and successive convexapproximation (SCA) techniques. Subsequently, the outer loop is solved usingthe Dinkelbach method to acquire an improved solution in every iteration untilit converges. Our simulation results illustrate the performance gains of theproposed methodology with respect to baseline algorithms with the fixed andmixed resource grid models.

Energy Efficient RAN Slicing and Beams Selection for Multiplexing of Heterogeneous Services in 5G mmWave Networks