Massive MIMO is considered a key technology for 5G. Various studies analyze the impact of the number of antennas, relying on channel properties only and assuming uniform antenna gains in very large arrays. In this paper, we investigate the impact of mutual coupling and edge effects on the gain pattern variation in the array. Our analysis focuses on the comparison of patch antennas versus dipoles, representative for the antennas typically used in massive MIMO experiments today. Through simulations and measurements, we show that the finite patch array has a lower gain pattern variation compared with a dipole array. The impact of a large gain pattern variation on the massive MIMO system is that not all antennas contribute equally for all users, and the effective number of antennas seen for a single user is reduced. We show that the effect of this at system level is a decreased rate for all users for the zero-forcing MIMO detector, up to 20% for the patch array and 35% for the dipole array. The maximum ratio combining on the other hand, introduces user unfairness.

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Massive MIMO (MaMIMO) is a technology of primary interest for sub-6 GHz operation in the next generation cellular systems. While MaMIMO is most often linked to macrocell scenarios, where a single cell serves many users distributed over a large area, network densification will also result in scenarios where many users are served by a MaMIMO base station (BS) that is nearby. A key question is how to scale up MaMIMO: should we add more antennas to a given cell, or create multiple smaller and distributed cells that can cooperate? This paper documents the measured performance of a very dense MaMIMO system for an indoor-to-outdoor propagation environment. The impact of the number of antennas, and the distribution of the antenna elements is experimentally verified for a simplified linear deployment of the BSs. Concretely, we serve 12 closely located users with 16, 32 or 64 antennas. We compare a centrally positioned collocated array and two distributed arrays with their uplink throughput in a licensed 2.6 GHz band. The experimental results show that 12 users can be served with only 32 antennas for the distributed topology, which is effectively only 16 antennas per MaMIMO BS. For the specific case analyzed in our measurement campaign, with the centralized deployment, 64 antennas are needed to obtain good performance, while distributing the antenna elements in two sub-arrays improves total performance and fairness between the users.

The aim of this study was to evaluate the risk factors and elucidate the clinical characteristics of cancer-associated ischemic stroke to differentiate it from conventional ischemic stroke in China and East Asia. Between June 2012 and June 2016, a retrospective analysis was performed on 609 stroke patients with cancer. They were divided into 3 groups: cancer-stroke group (CSG, 203 cases), stroke group (SG, 203 cases), and cancer group (CG, 203 cases). The d-dimer levels and diffusion-weighted imaging lesion (DWI) pattern were compared to an age- and sex-matched control group. The most common cancer types were colorectal cancer (20.2%) and lung cancer (18.72%). The average d-dimer level in stroke patients and cancer patients were 0.34 and 1.50 mg/L, respectively. The descending levels of d-dimer from cancer types were lung cancer (2.06 mg/L), pancreas (1.74 mg/L), gastric (1.61 mg/L), among others. Univariate analysis of the CSG and the others shows there were significant differences in the prevalence of the levels of d-dimer and DWI pattern, hypertension, diabetes mellitus, and thrombus. CSG has a unique pathological characteristic including high plasma d-dimer levels and multiple vascular lesions. The results show that d-dimer and DWI can be used as diagnostic index in clinical practice.

Massive MIMO promises unprecedented spectral efficiency as values exceeding 140 b/s/Hz have already been demonstrated in the lab for a single cell. In this paper, based on measurements obtained in a distributed Massive MIMO testbed, we compare the spectral efficiency, area spectral efficiency, and capacity of two adjacent cells under different levels of cooperation and the impact of co-channel interference. This is the first Massive MIMO measurement based analysis of the performance of spectrum and infrastructure sharing, showing that in fully cooperative systems (sharing infrastructure and spectrum) there is an improvement of the area spectral efficiency by 50% and a sixfold of capacity in comparison with a scenario without sharing, i.e. conventional two-cells planning. In comparison to the scenario where only spectrum is shared, the infrastructure and spectrum sharing case also increases the area spectral efficiency by two and the overall capacity by four. In addition, the use of M-MMSE increases the performance of the system in 43% in relation to RZF, for this particular scenario when co-channel interference is considered.

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