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This paper studies the application of Beam Hopping (BH) as a key enabler to provide high level of flexibility to manage scarce on-board resources, particularly power, based on the irregular and time variant traffic requests/demands distributed within the coverage of a satellite multibeam system. However, while high throughput full frequency reuse pattern is employed among beams, the performance of BH is significantly degraded due to the generated inter-beam interference, and applying precoding is essential. In this context, we propose Joint Precoding and BH (J-PBH) in a multibeam system.

We consider the forward link of a multibeam satellite system with
high spectral reuse and the novel low-complexity transmission and
detection strategies from [1]. More specifically, we study the impact
of a time offset between the antenna beams that cooperate to
simultaneously serve a given user. Assuming Gaussian signaling,
we provide closed-form expressions for the achievable rate region.
It is demonstrated that, in the absence of timing information at the
gateway, this region is not affected by a time offset. Our numerical

We consider a bi-directional Full-Duplex (FD) Multiple-Input Multiple-Output (MIMO) communication system in which nodes are capable of performing transitter (TX)- Receiver (RX) digital precoding/combining and multi-tap analog cancellation, and have individual Signal-to-Interference-plus- noise Ratio (SINR) requirements. We present an iterative algorithm for the TX powers minimization that includes closed- form expressions for the TX/RX digital beamformers at each algorithmic iteration step.

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.