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In Long Term Evolution (LTE) systems, the physical cell identity (PCI) assigned to a cell during network planning determines the set of sequences used by subscribers as de-modulation reference signals (DM RS) in the uplink (UL). A proper assignment of PCIs must prevent neighbor cells from using the same DM RS to avoid interference problems, thus ensuring adequate performance both in control and user data channels in the uplink. In this paper, a comprehensive analysis is carried out to quantify the impact of PCI planning on the performance of physical uplink control channel (PUCCH) in LTE. First, a novel analytical model that reflects the influence of PCI planning on interference and outage probability due to DM RS collisions in PUCCH is presented. Based on this model, PUCCH performance with several classical PCI planning schemes is evaluated with a static system-level simulator implementing a real network scenario. Simulated cases cover different PUCCH frame formats, different UL power control (PC) schemes and both regular and irregular traffic scenarios. Results show that a PCI plan constructed solely based on avoiding PCI collision/confusion and reference signals collisions in the downlink achieves near-optimal performance in terms of DM RS collisions in PUCCH, but, however, in extreme cases, DM RS collisions caused by neighbor cells sharing the same sequence might degrade PUCCH performance significantly. [ABSTRACT FROM AUTHOR]

Recent advances in mobile handsets have led to new trends in mobile broadband data consumption, with a huge increase of signaling traffic generated by always-connected devices. Thus, a proper planning of control channels in mobile networks is necessary to avoid network capacity problems and provide an appropriate quality of service to the end user. A key issue in network planning is the availability of a complete and accurate system model. In this paper, an analytical performance model for the Long Term Evolution (LTE) Physical Downlink Control Channel (PDCCH) is constructed based on queuing theory. Unlike previous works, the proposed model considers important network features, such as link adaptation, and can be tuned with available network performance statistics. Model assessment is carried out by comparing performance estimates with request-level simulations and real performance measurements taken from a live LTE network. Results show that the proposed model can predict the PDCCH load distribution in a live network accurately. [ABSTRACT FROM AUTHOR]

In the context of Long-Term Evolution (LTE), the next generation mobile telecommunication network, femtocells are lowpower base stations that efficiently provide coverage and capacity indoors. This paper presents a computationally efficient dynamic system-level LTE simulator for enterprise femtocell scenarios. The simulator includes specific mobility and traffic and propagation models for indoor environments. A physical layer abstraction is performed to predict link-layer performance with low computational cost. At link layer, two important functions are included to increase network capacity: Link Adaptation and Dynamic Scheduling. At network layer, other Radio Resource Management functionalities, such as Admission Control and Mobility Management, are also included. The resulting tool can be used to test and validate optimization algorithms in the context of Self-Organizing Networks (SON). [ABSTRACT FROM AUTHOR]