With the severe spectrum shortage in conventional cellular bands, millimeter wave (mmW) frequencies between 30 and 300 GHz have been attracting growing attention as a possible candidate for next-generation micro- and picocellular wireless networks. The mmW bands offer orders of magnitude greater spectrum than current cellular allocations and enable very high-dimensional antenna arrays for further gains via beamforming and spatial multiplexing. This paper uses recent real-world measurements at 28 and 73 GHz in New York, NY, USA, to derive detailed spatial statistical models of the channels and uses these models to provide a realistic assessment of mmW micro- and picocellular networks in a dense urban deployment. Statistical models are derived for key channel parameters, including the path loss, number of spatial clusters, angular dispersion, and outage. It is found that, even in highly non-line-of-sight environments, strong signals can be detected 100-200 m from potential cell sites, potentially with multiple clusters to support spatial multiplexing. Moreover, a system simulation based on the models predicts that mmW systems can offer an order of magnitude increase in capacity over current state-of-the-art 4G cellular networks with no increase in cell density from current urban deployments.

http://apps.fcc.gov/ecfs/document/view;NEWECFSSESSION=ThTmVg1SGvsFqgxGKYfckQC26BmBGYLH2jpL5z0dMms1j21m5YTC!-1110365353!-349327291?id=60001013324

Millimeter Wave Channel Modeling and Cellular Capacity Evaluation

Device-to-device (D2D) communication as an underlaying cellular network empowers user-driven rich multimedia applications and also has proven to be network efficient offloading eNodeB traffic. However, D2D transmitters may cause significant amount of interference to the primary cellular network when radio resources are shared between them. During the downlink (DL) phase, primary cell UE (user equipment) may suffer from interference by the D2D transmitter. On the other hand, the immobile eNodeB is the victim of interference by the D2D transmitter during the uplink (UL) phase when radio resources are allocated randomly. Such interference can be avoided otherwise diminish if radio resource allocated intelligently with the coordination from the eNodeB. In this paper, we formulate the problem of radio resource allocation to the D2D communications as a mixed integer nonlinear programming (MINLP). Such an optimization problem is notoriously hard to solve within fast scheduling period of the Long Term Evolution (LTE) network. We therefore propose an alternative greedy heuristic algorithm that can lessen interference to the primary cellular network utilizing channel gain information. We also perform extensive simulation to prove the efficacy of the proposed algorithm.

Efficient resource allocation for device-to-device communication underlaying LTE network

The use of multiple antennas at base stations is a key component in the design of cellular communication systems that can meet high-capacity demands in the downlink. Under ideal conditions, the gai ...

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Optimal Resource Allocation in Coordinated Multi-Cell Systems

The deployment of modern mobile systems has faced severe challenges due to the current spectrum scarcity. The situation has been further worsened by the development of different wireless technologies and standards that can be used in the same frequency band. Furthermore, the usage of smaller cells (e.g. pico, femto and wireless LAN), coexistence among heterogeneous networks (including amongst different wireless technologies such as LTE and Wi-Fi deployed in the same frequency band) has been a big field of research in the academy and industry. In this paper, we provide a performance evaluation of coexistence between LTE and Wi-Fi systems and show some of the challenges faced by the different technologies. We focus on a simulator-based system- level analysis in order to assess the network performance in an office scenario. Simulation results show that LTE system performance is slightly affected by coexistence whereas Wi-Fi is significantly impacted by LTE transmissions. In coexistence, the Wi-Fi channel is most often blocked by LTE interference, making the Wi-Fi nodes to stay on the LISTEN mode more than 96% of the time. This reflects directly on the Wi-Fi user throughput, that decreases from 70% to ≈100% depending on the scenario. Finally, some of the main issues that limit the LTE/Wi-Fi coexistence and some pointers on the mutual interference management of both the systems are provided.

Performance Evaluation of LTE and Wi-Fi Coexistence in Unlicensed Bands

Low-power base stations such as femtocells are one of the candidates for high-data-rate provisioning in local areas, such as residences, apartment complexes, business offices, and outdoor hotspot scenarios. Unfortunately, the benefits are not without new challenges in terms of interference management and efficient system operation. Due to the expected large number of user-deployed cells, centralized network planning becomes impractical, and new scalable alternatives must be sought. In this article we propose a fully distributed and scalable solution to the interference management problem in local areas, basing our study case on LTE-Advanced. We present extensive network simulation results to demonstrate that a simple and robust interference management scheme, called autonomous component carrier selection, allows each cell to select the most attractive frequency configuration; improving the experience of all users and not just the few best ones, while overall cell capacity is not compromised.

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Autonomous component carrier selection: interference management in local area environments for LTE-advanced

In this paper we propose a modification to Shannon capacity bound in order to facilitate accurate benchmarking of UTRAN long term evolution (LTE). The method is generally applicable to wireless communication systems, while we have used LTE air-interface technology as a case study. We introduce an adjusted Shannon capacity formula, where we take into account the system bandwidth efficiency and the SNR efficiency of LTE. Separating these issues, allows for simplified parameter extraction. We show that the bandwidth efficiency can be calculated based on system parameters, while the SNR efficiency is extracted from detailed link level studies including advanced features of MIMO and frequency domain packet scheduling (FDPS). We then use the adjusted Shannon capacity formula combined with G-factor distributions for macro and micro cell scenarios to predict LTE cell spectral efficiency (SE). Such LTE SE predictions are compared to LTE cell SE results generated by system level simulations. The results show an excellent match of less that 5-10% deviation.

Wei Na

Papers

LTE Capacity Compared to the Shannon Bound