We investigate and solve the rate balancing problem in the downlink for a multiuser Multiple-Input-Multiple-Output (MIMO) system. In particular, we adopt a transceiver structure to maximize the worst-case rate of the user while satisfying a total transmit power constraint. Most of the existing solutions either perform user Mean Squared Error (MSE) balancing or streamwise rate balancing, which is suboptimal in the MIMO case. The original rate balancing problem in the downlink is complicated due to the coupled structure of the transmit filters. This optimization problem is here solved in an alternating manner by exploiting weighted MSE uplink/downlink duality with proven convergence to a local optimum. Simulation results are provided to validate the proposed algorithm and demonstrate its performance improvement over unweighted MSE balancing.
Caching popular contents at the edge of the network can positively impact the performance and future sustainability of wireless networks in several ways, e.g., end-to-end access delay reduction and peak rate increase. In this paper, we aim at showing that non-negligible performance enhancements can be observed in terms of network interference footprint as well. To this end, we consider a full-duplex small-cell network consisting of non-cooperative cache-aided base stations, which communicate simultaneously with both downlink users and wireless backhaul nodes. We propose a novel static caching model seeking to mimic a geographical policy based on local files popularity and calculate the corresponding cache hit probability. Subsequently we study the performance of the considered network in terms of throughput gain with respect to its cache-free half-duplex counterpart. Numerical results corroborate our theoretical findings and highlight remarkable performance gains when moving from cache-free to cache-aided full-duplex small-cell networks.
In this paper, we consider the problem of user rate balancing in the downlink of multi-cell multi-user (MU) Multiple-Input-Multiple-Output (MIMO) systems with partial Channel State Information at the Transmitter (CSIT). With MIMO leading to multiple streams per user, user rate balancing involves both aspects of balancing and sum rate optimization. We linearize the problem by introducing a rate minorizer and by formulating the balancing operation as constraints leading to a Lagrangian, allowing to transform rate balancing into weighted sum minimization with Perron Frobenius theory. We provide original analytical expressions for the Lagrange multipliers for the multiple power constraints which can also handle the case in which some power constraints are satisfied with inequality, as can arise in a multi-cell scenario. We introduce two partial CSIT formulations. One is based on the ergodic rate Mean Squared Error (EMSE) relation, the other involves an original rate minorizer in terms of the received interference plus noise covariance matrix, in the partial CSIT case applied to the Expected Signal and Interference Power (ESIP) rate. The simulation results exhibit the improved performance of the proposed techniques over naive partial CSIT beamforming based on perfect CSIT algorithms, and in particular illustrate the close to optimal performance of the ESIP approach.
Abstract-Caching at the edge is a promising technique to cope with the increasing data demand in wireless networks. This paper analyzes the performance of cellular networks consisting of a tier macro-cell wireless backhaul nodes overlaid with a tier of cache-aided small cells. We consider both static and dynamic association policies for content delivery to the user terminals and analyze their performance. In particular, we derive closedform expressions for the area spectral efficiency and the energy efficiency, which are used to optimize relevant design parameters such as the density of cache-aided small cells and the storage size. By means of this approach, we are able to draw useful design insights for the deployment of highly performing cache-aided tiered networks.
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