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We introduce a new robust, outage minimum, millimeter wave (mmWave) coordinated multipoint (CoMP) beamforming scheme to combat the random path blockages typical of mmWave systems. Unlike state-of-the-art methods, which are of limited applicability in practice due to their combinatorial nature which leads to prohibitive complexity, the proposed method is based on a stochastic-learning-approach, which learns crucial blockage patterns without resorting to the well-known worstcase optimization framework. Simulation results demonstrate the superior performance of the proposed method both in terms of outage probability and effective achievable rate.

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We propose a new signal spreading-based non-orthogonal multiple access (NOMA) schemes that exploits the frame-theoretic design principles to enable the efficient concurrence of multiple users in both downlink (DL) and uplink (UL). In contrast to many other NOMA schemes, the proposed method does not require built-in sparsity on the usage of resources by any individual users, hence referred to as massively concurrent non-orthogonal multiple access (MC-NOMA). Instead, MC-NOMA leverages frames as vectorized ensembles of the individual complex-valued waveform signatures, optimized for low mutual coherence so as to minimize the multi-user interference. A theoretical analysis of the MC-NOMA is offered, which reveals that it can theoretically reach the capacity of the multi-user MIMO channel and outmatches the state of the art in terms of maximum achievable rate over discrete constellations. A detailed description of both the frame-based transmitter design and a newly developed low-complexity efficient decoder is given, which, via simulations, are used to demonstrate that MC-NOMA outperforms the well-established NOMA schemes, such as sparse-coded multiple access (SCMA) and pattern division multiple access (PDMA).INDEX TERMS Frame theory, massively-concurrent non-orthogonal multiple access, multiuser detection, non-orthogonal communications, tree search decoding.

The purpose of our study was to investigate the validity of a spatial resolution measuring method that uses a combination of a bar-pattern phantom and an imageaveraging technique, and to evaluate the spatial resolution property of iterative reconstruction (IR) images with middle-contrast (50 HU) objects. We used computed tomography (CT) images of the bar-pattern phantom reconstructed by the IR technology Adaptive Iterative Dose Reduction 3D (AIDR 3D), which was installed in the multidetector CT system Aquilion ONE (Toshiba Medical Systems, Otawara, Japan). The contrast of the bar-pattern image was set to 50 HU, which is considered to be a middle contrast that requires higher spatial resolution clinically. We employed an image-averaging technique to eliminate the influence of image noise, and we obtained averaged images of the bar-pattern phantom with sufficiently low noise. Modulation transfer functions (MTFs) were measured from the images. The conventional wire method was also used for comparison; in this method, AIDR 3D showed MTF values equivalent to those of filtered back projection. For the middle-contrast condition, the results showed that the MTF of AIDR 3D decreased with the strength of IR processing. Further, the MTF of AIDR 3D decreased with dose reduction. The imageaveraging technique used was effective for correct evaluation of the spatial resolution for middle-contrast objects in IR images. The results obtained by our method clarified that the resolution preservation of AIDR 3D was not sufficient for middle-contrast objects.

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