34 research outputs found

    Energy-Efficient Coordinated Multi-Cell Multigroup Multicast Beamforming with Antenna Selection

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    This paper studies energy-efficient coordinated beamforming in multi-cell multi-user multigroup multicast multiple-input single-output systems. We aim at maximizing the network energy efficiency by taking into account the fact that some of the radio frequency chains can be switched off in order to save power. We consider the antenna specific maximum power constraints to avoid non-linear distortion in power amplifiers and user-specific quality of service (QoS) constraints to guarantee a certain QoS levels. We first introduce binary antenna selection variables and use the perspective formulation to model the relation between them and the beamformers. Subsequently, we propose a new formulation which reduces the feasible set of the continuous relaxation, resulting in better performance compared to the original perspective formulation based problem. However, the resulting optimization problem is a mixed-Boolean non-convex fractional program, which is difficult to solve. We follow the standard continuous relaxation of the binary antenna selection variables, and then reformulate the problem such that it is amendable to successive convex approximation. Thereby, solving the continuous relaxation mostly results in near-binary solution. To recover the binary variables from the continuous relaxation, we switch off all the antennas for which the continuous values are smaller than a small threshold. Numerical results illustrate the superior convergence result and significant achievable gains in terms of energy efficiency with the proposed algorithm.Comment: 6 pages, 5 figures, accepted to IEEE ICC 2017 - International Workshop on 5G RAN Desig

    Cellular-Broadcast Service Convergence through Caching for CoMP Cloud RANs

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    Cellular and Broadcast services have been traditionally treated independently due to the different market requirements, thus resulting in different business models and orthogonal frequency allocations. However, with the advent of cheap memory and smart caching, this traditional paradigm can converge into a single system which can provide both services in an efficient manner. This paper focuses on multimedia delivery through an integrated network, including both a cellular (also known as unicast or broadband) and a broadcast last mile operating over shared spectrum. The subscribers of the network are equipped with a cache which can effectively create zero perceived latency for multimedia delivery, assuming that the content has been proactively and intelligently cached. The main objective of this work is to establish analytically the optimal content popularity threshold, based on a intuitive cost function. In other words, the aim is to derive which content should be broadcasted and which content should be unicasted. To facilitate this, Cooperative Multi- Point (CoMP) joint processing algorithms are employed for the uni and broad-cast PHY transmissions. To practically implement this, the integrated network controller is assumed to have access to traffic statistics in terms of content popularity. Simulation results are provided to assess the gain in terms of total spectral efficiency. A conventional system, where the two networks operate independently, is used as benchmark.Comment: Submitted to IEEE PIMRC 201

    Pilot-Aided Distributed Multi-Group Multicast Precoding Design for Cell-Free Massive MIMO

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    We propose fully distributed multi-group multicast precoding designs for cell-free massive multiple-input multiple-output (MIMO) systems with modest training overhead. We target the minimization of the sum of the maximum mean squared errors (MSEs) over the multicast groups, which is then approximated with a weighted sum MSE minimization to simplify the computation and signaling. To design the joint network-wide multi-group multicast precoders at the base stations (BSs) and the combiners at the user equipments (UEs) in a fully distributed fashion, we adopt an iterative bi-directional training scheme with UE-specific or group-specific precoded uplink pilots and group-specific precoded downlink pilots. To this end, we introduce a new group-specific uplink training resource that entirely eliminates the need for backhaul signaling for the channel state information (CSI) exchange. The precoders are optimized locally at each BS by means of either best-response or gradient-based updates, and the convergence of the two approaches is analyzed with respect to the centralized implementation with perfect CSI. Finally, numerical results show that the proposed distributed methods greatly outperform conventional cell-free massive MIMO precoding designs that rely solely on local CSI.Comment: Submitted to TW

    Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-art, Classification and Challenges

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    Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: i) transmitting distinct data streams to groups of users and ii) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: i) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding, ii) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area
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