Sorry, you need to enable JavaScript to visit this website.

In this letter, we present a sequential closed-form
semiblind receiver for a one-way multihop amplify-and-forward
relaying system. Assuming Khatri–Rao space-time coding at each
relay, it is shown that the system with K relays can be modeled
by means of a generalized nested PARAFAC model. Decomposing
this model intoK + 1 third-order PARAFAC models, we develop
a closed-form semiblind receiver for jointly estimating the information
symbols and the individual channels, at the destination node.


Hybrid analog-digital beamforming has been shown to reduce hardware cost and power consumption in massive MIMO systems, at the expense of increased radiated power for given performance targets. To alleviate the above shortfall, in this paper we exploit the concept of constructive interference (CI) that has been shown to offer significant radiated power savings in fully-digital multi-user downlink MIMO systems. We explore analog beamforming design, and develop solutions specifically tailored for CI-based hybrid beamforming.


In this paper, we consider a multi-user massive MIMO network with hybrid beamforming architecture at the base station. The objective is to jointly perform user selection and design analog-digital hybrid beamformers in order to maximize a given utility function while satisfying various pertinent constraints. The problem is combinatorial and impractical to solve


To solve the problem of beam selection or capturing the highest possible signal power, we propose a sequential test that can adapt to the SNR operating point and speed up the selection procedure in terms of the number of required observations in comparison to a perfectly tuned fixed length test assuming genie knowledge.


We consider a two-way full-duplex (FD) multiple-input multiple-output (MIMO) communication system in which devices are equipped both with multi-tap analog interference cancellers and TX-RX beamforming capabilities, and propose a joint analog and digital algorithm to simultaneously maximize the rate and minimize the self-interference (SI) in such a system.


Cell-free massive MIMO system is a promising technology of 5G wireless communications that provide a user-centric coverage to the user by the basestation cooperation. Most prior works on the cell-free massive MIMO systems assume the time division duplexing (TDD) systems, although the frequency division duplexing (FDD) systems dominate the current wireless communications. In the FDD systems, CSI acquisition and feedback overhead are serious concerns when the number of antennas is large.


This paper considers the (NP-)hard problem of joint multicast beamforming and antenna selection. Prior work has focused on using Semi-Definite relaxation (SDR) techniques in an attempt to obtain a high-quality sub-optimal solution. However, SDR suffers from the drawback of having high computational complexity, as SDR lifts the problem to higher dimensional space, effectively squaring the number of variables.


The transceiver separations required for synthesizing full rank MIMO matrices in line of sight (LoS) geometries scale as the square root of the product of carrier wavelength
and range. The wavelengths at millimeter (mm) wave carrier frequencies are small therefore enable LoS spatial multiplexing with practical node form factors at ranges of 10-100 m, depending on the carrier frequency. However, such LoS MIMO links become frequency selective even with small geometric mismatches. Exact channel inversion in an


In this paper we consider Millimeter wave (mmWave) Massive MIMO systems where a large antenna array at the base station (BS) serves a few scheduled terminals. The high dimensional null space of the channel matrix to the scheduled terminals is utilized to broadcast system information to the non-scheduled terminals on the same time-frequency resource.