Optical code division multiple access (CDMA)-based networks are an interesting alternative to support various traffic types of multimedia applications with highly variable performance targets. Generally, multilength codes are designed to support multirate services, while the multiweight codes are designed to support differentiated quality of service (QoS) for multimedia applications. However, existing optical orthogonal codes (OOCs) are limited to single class or multiclass with restricted weight and length properties. Therefore, there exists a lack of flexibility in the existing OOCs to support arbitrary rate and QoS. This paper presents a proposal of generation procedure and performance analysis of joint multiweight multilength strict OOCs. The approach used in this paper is to apply a methodology strongly relying on developed analytical theory that is supported by computer optimization, because it has turned out that it is mathematically intractable to construct unconstraint joint multilength multiweight OOCs using pure algebraic techniques. The generated code set fulfills the conditions of strictly OOCs, namely, the maximum nonzero shift autocorrelation and the maximum cross correlation constraints of one. The mark position difference (MPD) approach is used to generate in a flexible way the multiclass code set. The MPD results in the simple evaluation of multiclass code set cardinality. Furthermore, the multiple-access interference (MAI) in a multiclass OOC system is evaluated by modeling the interference per class as a Poisson distribution to simplify performance evaluation with acceptable accuracy.

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The trials and rollout of the fifth generation (5G) network technologies are gradually intensifying as 5G is positioned as a platform that not only accommodates exploding data traffic but also unlocks a multitude use cases, services and deployment scenarios. However, the need for hyperdense 5G deployments is revealing some of the limitations of planning approaches that hitherto proved adequate for pre-5G systems. The hyperdensification envisioned in 5G networks not only adds complexity to network planning and optimization problems, but underlines need for more realistic data-driven approaches that consider cost, varying demands and other contextual attributes to produce feasible topologies. Furthermore, the quest for network programmability and automation including the 5G radio access network (RAN), as manifested by network slicing technologies and more flexible RAN architectures, are also among other factors that influence planning and optimization frameworks. Collectively, these deployment trends, technological developments and evolving (and diverse) service demands point towards the need for more holistic frameworks. This article proposes a data-driven multiobjective optimization framework for hyperdense 5G network planning with practical case studies used to illustrate added value compared to contemporary network planning and optimization approaches. Comparative results from the case study with real network data reveal potential performance and cost improvements of hyperdense optimized networks produced by the proposed framework due to increased use of contextual data of planning area and focus on objectives that target demand satisfaction.

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