Massive multiple-input multiple-output technology has been considered a breakthrough in wireless communication systems. It consists of equipping a base station with a large number of antennas to serve many active users in the same time-frequency block. Among its underlying advantages is the possibility to focus transmitted signal energy into very short-range areas, which will provide huge improvements in terms of system capacity. However, while this new concept renders many interesting benefits, it brings up new challenges that have called the attention of both industry and academia: channel state information acquisition, channel feedback, instantaneous reciprocity, statistical reciprocity, architectures, and hardware impairments, just to mention a few. This paper presents an overview of the basic concepts of massive multiple-input multiple-output, with a focus on the challenges and opportunities, based on contemporary research.

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In order to keep and/orexpand its share of the wireless communication market and decrease churn, it is important for network operators to keep their users (clients) satisfied. The problem to be solved is how to increase the number of satisfied non-real time (NRT) and real time (RT) users in the downlink of the radio access network of an orthogonal frequency division multiple access system. In this context, the present work proposes a method to solve the referred problem using a unified radio resource allocation (RRA) framework based on utility theory. This unified RRA framework is particularized into two RRA policies that use sigmoidal utility functions based on throughput or delay and are suitable for NRT and RT services, respectively. It is demonstrated by means of system-level simulations that a step-shaped sigmoidal utility function combined with a channel-aware opportunistic scheduling criterion is effective toward the objective of user satisfaction maximization.

Abstract-In this work, we study the problem of allocating resources in a multi-service cellular network aiming at maximizing the total system rate while providing suitable Quality of Experience (QoE) to the network users. In our formulation, we try to satisfy at least a certain number of users per service plan, which is an important constraint from the mobile network operators' perspective. We manage to reformulate this nonlinear optimization problem as an Integer Linear Problem (ILP), that can be solved by standard methods. However, due to the exponentially high complexity to solve large instances of this problem, we propose and evaluate a suboptimal algorithm with a much lower complexity, called Rate Maximization under Experience Constraints (RMEC), whose main idea is to divide the problem into three smaller subproblems with reduced complexity. By means of computational simulations, we show that our proposed algorithm presents a near optimal performance and outperforms the state-of-art solution of the literature.

Abstract-Network-assisted single-hop device-to-device (D2D) communication can increase the spectral and energy efficiency of cellular networks by taking advantage of the proximity, reuse, and hop gains. In this paper we argue that D2D technology can be used to further increase the spectral and energy efficiency if the key D2D radio resource management algorithms are suitably extended to support network assisted multi-hop D2D communications. Specifically we propose a novel, distributed utility maximizing D2D power control (PC) scheme that is able to balance spectral and energy efficiency while taking into account mode selection and resource allocation constraints that are important in the integrated cellular-D2D environment. Our analysis and numerical results indicate that multi-hop D2D communications combined with the proposed PC scheme can be useful not only for harvesting the potential gains previously identified in the literature, but also for extending the coverage of cellular networks.

Radio Resource Allocation (RRA) in cellular systems is a relevant and difficult task that should assign the system resources in the most efficient manner while fulfilling different constraints such as Quality of Service (QoS). In wireless systems that employ Single Carrier-Frequency Division Multiple Access (SC-FDMA) as in Long Term Evolution (LTE) uplink, RRA is even more difficult since the frequency resources should be assigned in contiguous blocks of subcarriers to each terminal. In this work we study two important RRA problems in SC-FDMA: the total data rate maximization and the total data rate maximization with minimum user satisfaction constraints. We formulate them as optimization problems and show that the optimal solutions are not practical to be employed in real systems due to the high computational complexity. Therefore, we propose two efficient heuristic solutions for those problems. By simulation results, we show that both solutions are near optimal and subject only to small performance degradation compared to the complex and impractical optimal solutions.

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