Among the enabling technologies for 5G wireless networks, millimeter wave (mmWave) communication offers the chance to deal with the bandwidth shortage affecting wireless carriers. Radio signals propagating in the mmWave band experience considerable path loss, leading to poor link budgets. As a consequence, large directive gains are needed in order to communicate and therefore, beam alignment stages have to be considered during the initial phases of the communication. While beam alignment is considered essential to the performance of such systems, it is also a costly operation in terms of latency and resources in the massive MIMO (mMIMO) regime due to the large number of beam combinations to be tested. Therefore, it is desirable to identify methods that allow to optimally trade-off overhead for performance. Location-aided beam training has been proposed recently as a possible solution to this problem, exploiting long-term spatial information so as to focus the beam search on particular areas, thus reducing overhead. However, due to mobility and other imperfections in the estimation process, the spatial information obtained at the base station (BS) and the user (UE) is likely to be noisy, degrading beam alignment performance. In this paper, we introduce a robust beam alignment framework in order to exhibit resilience with respect to this problem. We first recast beam alignment as a decentralized coordination problem where BS and UE seek coordination on the basis of correlated yet individual measurements. We formulate the optimum beam alignment solution as the solution of a Bayesian team decision problem. We then propose a suite of algorithms to approach optimal designs with reduced complexity. The effectiveness of the robust beam alignment procedure, compared with classical designs, is then verified on simulation settings with varying location information accuracies.

No abstract

Using out-of-band (OOB) side-information has recently been shown to accelerate beam selection in single-user millimeter wave (mmWave) massive MIMO (m-MIMO) communications. In this paper, we propose a novel OOB-aided beam selection framework for a mmWave uplink multi-user system.In particular, we exploit spatial information extracted from lower (sub-6 GHz) bands in order to assist with an inter-user coordination scheme at mmWave bands. To enforce coordination, we propose an exchange protocol exploiting device-to-device (D2D) communications. In particular, low-rate beam-related information is exchanged between the mobile terminals. The decentralized coordination mechanism allows the suppression of the so-called co-beam interference which would otherwise lead to irreducible interference at the base station (BS) side, thereby triggering substantial spectral efficiency (SE) gains.

No abstract

No abstract