Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the wide-spread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model. Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the wide-spread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model.

The spectrum scarcity problem can be tackled by promoting a more efficient use of the radio spectrum. Spectrum sharing techniques like TV White Spaces (TVWS), Licensed Shared Access (LSA), and Spectrum Access System (SAS), are adequate solutions for this problem and there exist already regulation and standardization efforts worldwide. To evaluate the coexistence between primary and secondary spectrum users, a Long Term Evolution (LTE) multi-cell simulator has been designed, which employs a generic spectrum sharing technique, Dynamic Spectrum Access (DSA), in order to obtain additional network capacity. As a way to bring attention and confidence of the telecommunications sector regarding the benefits that this technology may bring, the analysis is done in terms of interference suffered by incumbents (primary users) and capacity by secondary users. Results have confirmed the unfeasibility of co-channel coexistence for moderate distances between the cordless camera service (incumbent) and LTE network (secondary user) due to high interference. However, for adjacent bands, a gain of 40% in the secondary users’ capacity is possible following more restrictive interference protection requirements and 30% gain with the smaller frequency separation between primary and secondary operating frequencies.

Remote and rural area connectivity is a true challenge that can be alleviated by allowing shared spectrum access in bands below 1 GHz. Spectrum sensing can provide benefits when used together with the database approach for realizing spectrum sharing. Energy detection (ED) is very suitable in cooperative sensing because of its low computational complexity and it does not need prior knowledge about the signal and noise. In this work, cooperative sensing using the window-based (WIBA) ED method is studied to maximize signal detection distance in a rural area scenario with a dedicated channel model. Based on the required individual user detection probabilities, cooperative signal detection distances in kilometers are explored using both OR and k-out-of-n -rules. The results are compared to that of the localization algorithm based on double-thresholding (LAD) method. Computer simulations using a rural area channel model show that the detection distance difference is tens of kilometers. Furthermore, it was found that the signal detection distance improvement can be even five-fold when using the cooperative sensing approach. Thus the proper use and design of cooperative sensing can help in rural area connectivity.

Researches in Power Control (PC) schemes are fundamental to provide efficient algorithms and understand their behavior in Device-to-Device (D2D) scenario. The aim of the current study is to investigate Open Loop Power Control (OLPC), Closed Loop Power Control (CLPC) and indicate Soft Dropping Power Control (SDPC) like an alternative PC scheme to D2D communications underlaying a cellular network. We briefly review PC schemes, suggest a new point of dynamic offset compensation factor σ setting the issue in CLPC and evaluate its performance in terms of spectral and power efficiency. Results demonstrate that SDPC keeps a reasonable spectral efficiency and provides a gain of 70 % in power efficiency in relation Long Term Evolution (LTE) PC schemes for cellular communications, and the factor σ = 0.8 can modify the behavior of CLPC because increases the Signal to Interference-plus-Noise Ratio (SINR) of the worst users.

For systems with reuse factor less than one, the co- channel interference can drastically reduce the gain of primary networks, which limits the whole system performance. This paper exploits the selection of Downlink (DL) or Uplink (UL) band to be reused by a Device-to-Device (D2D) link. The band selected by the method is based on a radio distance metric, such as received power. Despite being a simple concept, results have shown that band selection can effectively mitigate the interference caused by D2D communications in a Long Term Evolution (LTE) network. Therefore, the coexistence of cellular and D2D communication modes becomes possible in time, frequency, and space.

Device-to-Device (D2D) communication is seen as a promising technology to increase the capacity of current wireless systems without extra electromagnetic spectrum bands. However, before starting a D2D communication, Mobile Stations (MSs) must be aware of their neighbors, through a discovery process. While operating in cellular networks, such process may benefit from the network-assistance. In this paper, we propose a method based on the available network power measures to improve the discovery process. Results show that our proposal is less complex but still outperforms traditional methods when considering the time to detect all neighbors.

Device-to-Device (D2D) communications underlying cellular networks are a way to increase the network capacity and potentially save the battery lifetime of closely located physical devices. However, D2D communications can generate significant interference to the cellular network when the same resources are shared by both systems. Therefore, the design of Power Control (PC) schemes is required to keep the interference under control, get energy-efficient transmissions and protect cellular devices. In this work, we investigated operating points of the Soft Dropping Power Control (SDPC) and Open-Loop Power Control (OLPC) schemes for energy efficiency of cellular and D2D communications in uplink OFDMA systems. Results indicate that the SDPC performs better for cellular links and OLPC provides higher gains for D2D links in terms of energy efficiency. While high values of pathloss compensation factor α have been widely used in OLPC studies for the LTE standard, α ∊ {0.4, 0.5} has provided high energy efficiency gains for D2D links. Also, by properly setting the parameters of the OLPC applied to D2D links in uplink and considering the most favorable scenario for sharing resources in all cells, the minimum cost for having spectral efficiency gains for D2D communications represents an impact of 11 % on the system spectral efficiency of cellular communications.

The expected performance improvements of next-generation mobile radio access networks (RANs) can be achieved, e.g., by a flexible deployment of different types of radio access points (RAPs), such as intelligent relay nodes (RNs). To facilitate a cost-vs.-performance assessment of different deployment options, this paper presents a classification of different RAN cost components. Then, a method for deployment cost optimization is introduced which allows a comparison of the cost effectiveness of different RAN deployments by calculating optimum densities of different RAP types, based on a multi-dimensional iso-performance map. This method is first derived in theory and then demonstrated for two different deployment scenario examples.