We study the uplink control signaling in 3GPP-Long Term Evolution (LTE) systems. Specifically, we propose a precoding method that uses complex-field coding (CFC) to improve the performance of the ...PUCCH format 2 control signaling. In the case of perfect channel state information (CSI) at the receiver and with a single receive antenna, the proposed method offers significant gains compared to the coding currently used in 3GPP-LTE. However the gains are marginal with two receive antennas. In order to examine the impact of channel estimation errors, we also derive the optimal detector for the case of imperfect receiver CSI, both for conventional coding and for the proposed CFC method.
We discuss new space-time codes tailored to point-to-multipoint, or broadcast, communications using layered source coding. Our codes can be encoded (and decoded) differentially, and they are based ...entirely on phase-shift keying. We discuss design criteria for the codes, and the design of optimal and suboptimal receiver structures. We also discuss the relation between our codes and a differentially encoded Alamouti code. Finally, we illustrate how our codes can be used to improve the throughput of a broadcasting network.
This paper considers the uplink (UL) of a multicell Massive MIMO (multiple-input multiple-output) system with spatially correlated Rician fading channels. The channel model is composed of a ...deterministic line-of-sight (LoS) path and a stochastic non-line-of-sight (NLoS) component describing a spatially correlated multipath environment. We derive the statistical properties of the minimum mean squared error (MMSE) and least-square (LS) channel estimates for this model. Using these estimates for maximum ratio (MR) combining, rigorous closed-form UL spectral efficiency (SE) expressions are derived. Numerical results show that the SE is higher when using the MMSE estimator than the LS estimator, and the performance gap increases with the number of antennas. Moreover, Rician fading provides higher achievable SEs than Rayleigh fading since the LoS path improves the sum SE.
This paper investigates the joint data and pilot power optimization for maximum sum spectral efficiency (SE) in multi-cell Massive MIMO systems, which is a non-convex problem. We first propose a new ...optimization algorithm, inspired by the weighted minimum mean square error (MMSE) approach, to obtain a stationary point in polynomial time. We then use this algorithm together with deep learning to train a convolutional neural network to perform the joint data and pilot power control in sub-millisecond runtime, making it suitable for online optimization in real multi-cell Massive MIMO systems. The numerical result demonstrates that the solution obtained by the neural network is 1% less than the stationary point for four-cell systems, while the sum SE loss is 2% in a nine-cell system.
Abstract
Background: Mutational processes generate unique patterns of base substitutions generally referred to as mutational signatures. Mutational signatures can give insights into fundamental ...mutational processes underlying somatic mutations in tumors and have been shown to provide a starting point from which to evaluate therapeutic options. Neuroblastoma is clinically heterogeneous ranging from tendency of spontaneous regression to frequent formation of metastases. Earlier studies have identified several recurrent genetic alterations, including mutations in genes such as ALK and ATRX, as well as chromosomal rearrangements such as MYCN amplification, 11q deletion and 17 gain. Despite recent progress in the treatment of high-risk neuroblastoma, patients in this subgroup still have a poor prognosis, underscoring the need to further stratify patients in order to help inform clinical decision making.
Methods: Here, we sought to characterize high-risk patients and their underlying pattern of aberrations by conducting whole genome sequencing of 30 neuroblastoma patients. For each tumor/normal pair, the mutational landscape comprising single nucleotide and structural variants including copy number alterations was investigated. Non-negative matrix factorization was used to decompose single nucleotide variants to discover mutational signatures.
Results: De novo mutational signature analysis identified two mutational profiles (signature A and signature B) that were compared to known signatures of the pan-cancer study by Alexandrov et al. (2013). The landscape of signature A is closest to their signature 18 (0.97 cosine similarity) and revealed a strong bias towards C>A substitutions mainly found in neuroblastoma, and signature B is closest to signature 5 (0.82 cosine similarity) identified in most of the cancers. Out of 13 patients with a clear dominance of signature A, 12 patients were classified with MYCN amplification or 11q deletion. Furthermore, 5 out of 6 patients with a main contribution of signature B were metastasis or relapse cases.
Conclusions: Our results suggest that what is currently considered to be the typical neuroblastoma signature is mainly present in primary high-risk patients whereas the mutational landscape is altered in more advanced stages of the disease. To better understand the connection between the identified signatures and the high-risk subgroup, we are currently investigating the genome wide landscape of the observed C>A substitutions.
Citation Format: Susanne E. Reinsbach, Malin Larsson, Angela Martinez-Monleon, Rose-Marie Sjöberg, Niloufar Javanmardi, Anna Djos, Per Kogner, Susanne Fransson, Erik Larsson Lekholm, Tommy Martinsson. Identification of mutational signatures in high-risk neuroblastoma patients abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2246.
With the advances in virtual and augmented reality, gaming applications, and entertainment, certain indoor scenarios will require vastly higher capacity than what can be delivered by 5G. In this ...paper, we focus on massive MIMO for indoor environments. We provide a case study of the distributed deployment of the antenna elements over the walls of a room and not restricting the antenna separation to be half the wavelength. This is a new paradigm of massive MIMO antenna deployment, introduced in 1 under the name RadioWeaves. We investigate different antenna deployment scenarios in line of sight communication. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses caused by grating lobes and thus saves a lot on transmit power. Through simulations, we show that the RadioWeaves technology can provide high rates to multiple users by spending very little power at the transmitter compared to a co-located deployment.
Massive MIMO is the currently most compelling sub-6 GHz wireless access technology for 5G. Since its inception about a decade ago, it has evolved from a wild "academic" idea to one of the most ...vibrant research topics in the wireless communications community, as well as a main work item in 5G standardization. The concept is to equip base stations with arrays of many antennas that serve many terminals simultaneously, in the same time-frequency resource. The arrays have attractive form factors: in the 2 GHz band, a halfwave-length-spaced rectangular array with 200 dual-polarized elements is about 1.5 × 0.75 meters large. Massive MIMO operates in TDD mode and the downlink beamforming exploits the uplink-downlink reciprocity of radio propagation. Specifically, the base station array uses channel estimates obtained from uplink pilots transmitted by the terminals to learn the channel in both directions. This makes Massive MIMO entirely scalable with respect to the number of base station antennas. Base stations operate autonomously, with no sharing of payload data or channel state information with other cells. In this talk I will discuss the development of Massive MIMO over the last five years, and outline the most important research problems ahead.
The high hardware complexity of a massive MIMO base station, which requires hundreds of radio chains, makes it challenging to build commercially. One way to reduce the hardware complexity and power ...consumption of the receiver is to lower the resolution of the analog-to-digital converters (ADCs). We derive an achievable rate for a massive MIMO system with arbitrary quantization and use this rate to show that ADCs with as low as 3 bits can be used without significant performance loss at spectral efficiencies around 3.5 bpcu per user, also under interference from stronger transmitters and with some imperfections in the automatic gain control.
Objective: A thyroid rat model combining functional and anatomical information would be of great benefit for better modeling of thyroid physiology and for absorbed dose calculations. Our aim was to ...show that 124I-PET and CT small animal imaging are useful as a combined model for studying thyroid physiology and dose calculation. Methods: Seven rats were subjects for multiple thyroid 124I-imaging and CT-scans. S-values mGy/MBqs for different thyroid sizes were simulated. A phantom with spheres was designed for validation of performances of the small animal PET and CT imaging systems. Results: Small animal image-based measurements of the activity amount and the volumes of the spheres with a priori known volumes showed a good agreement with their corresponding actual volumes. The CT scans of the rats showed thyroid volumes from 34–70 mL. Conclusions: The wide span in volumes of thyroid glands indicates the importance of using an accurate volume-measuring technique such as the small animal CT. The small animal PET system was on the other hand able to accurately estimate the activity concentration in the thyroid volumes. We conclude that the combination of the PET and CT image information is essential for quantitative thyroid imaging and accurate thyroid absorbed dose calculation.
We consider soft MIMO detection for the case of block fading. That is, the transmitted codeword spans over several independent channel realizations and several instances of the detection problem must ...be solved for each such realization. We develop methods that adaptively allocate the computational resources to the detection problems of each channel realization, under a total per-codeword complexity constraint. Our main results are a formulation of the problem as a mathematical optimization problem and a greedy algorithm to approximate it in a computationally feasible fashion.
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