A Stochastic Geometric Analysis of Device-to-Device Communications Operating over Generalized Fading Channels

Device-to-device (D2D) communications are now considered as an integral part of future 5G networks which will enable direct communication between user equipment (UE) without unnecessary routing via the network infrastructure. This architecture will result in higher throughputs than conventional cellular networks, but with the increased potential for co-channel interference induced by randomly located cellular and D2D UEs. The physical channels which constitute D2D communications can be expected to be complex in nature, experiencing both line-of-sight (LOS) and non-LOS (NLOS) conditions across closely located D2D pairs. As well as this, given the diverse range of operating environments, they may also be subject to clustering of the scattered multipath contribution, i.e., propagation characteristics which are quite dissimilar to conventional Rayeligh fading environments. To address these challenges, we consider two recently proposed generalized fading models, namely $\kappa-\mu$ and $\eta-\mu$, to characterize the fading behavior in D2D communications. Together, these models encompass many of the most widely encountered and utilized fading models in the literature such as Rayleigh, Rice (Nakagami-$n$), Nakagami-$m$, Hoyt (Nakagami-$q$) and One-Sided Gaussian. Using stochastic geometry we evaluate the rate and bit error probability of D2D networks under generalized fading conditions. Based on the analytical results, we present new insights into the trade-offs between the reliability, rate, and mode selection under realistic operating conditions. Our results suggest that D2D mode achieves higher rates over cellular link at the expense of a higher bit error probability. Through numerical evaluations, we also investigate the performance gains of D2D networks and demonstrate their superiority over traditional cellular networks.Comment: Submitted to IEEE Transactions on Wireless Communication

Multiscale X ray study of Bacillus subtilis biofilms reveals interlinked structural hierarchy and elemental heterogeneity

Biofilms are multicellular microbial communities that encase themselves in an extracellular matrix ECM of secreted biopolymers and attach to surfaces and interfaces. Bacterial biofilms are detrimental in hospital and industrial settings, but they can be beneficial, for example, in agricultural as well as in food technology contexts. An essential property of biofilms that grants them with increased survival relative to planktonic cells is phenotypic heterogeneity, the division of the biofilm population into functionally distinct subgroups of cells. Phenotypic heterogeneity in biofilms can be traced to the cellular level; however, the molecular structures and elemental distribution across whole biofilms, as well as possible linkages between them, remain unexplored. Mapping X ray diffraction across intact biofilms in time and space, we revealed the dominant structural features in Bacillus subtilis biofilms, stemming from matrix components, spores, and water. By simultaneously following the X ray fluorescence signal of biofilms and isolated matrix components, we discovered that the ECM preferentially binds calcium ions over other metal ions, specifically, zinc, manganese, and iron. These ions, remaining free to flow below macroscopic wrinkles that act as water channels, eventually accumulate and may possibly lead to sporulation. The possible link between ECM properties, regulation of metal ion distribution, and sporulation across whole, intact biofilms unravels the importance of molecular level heterogeneity in shaping biofilm physiology and developmen

A Queueing Theoretic Approach to Decoupling Inventory

This paper investigates the performance of different hybrid push-pull systems with a decoupling inventory at the semi-finished products and reordering thresholds. Raw materials are ‘pushed’ into the semi-finished product inventory and customers ‘pull’ products by placing orders. Furthermore, production of semi-finished products starts when the inventory goes below a certain level, referred to as the threshold value and stops when the inventory attains stock capacity. As performance of the decoupling stock is critical to the overall cost and performance of manufacturing systems, this paper introduces a Markovian model for hybrid push-pull systems. In particular, we focus on a queueing model with two buffers, thereby accounting for both the decoupling stock as well as for possible backlog of orders. By means of numerical examples, we assess the impact of different reordering policies, irregular order arrivals, the set-up time distribution and the order processing time distribution on the performance of hybrid push-pull systems

EVS Throughput Improvement

This paper covers the background, methods, and results of the Environmental Services (EVS) Throughput Improvement project at Northwestern Medicine’s Kishwaukee Hospital. Patient throughput at hospitals is closely related to the experience of its patients. At Kishwaukee hospital, increased demand for inpatient services resulted in high occupancy rates and thereby undesirable patient throughput patterns. The project addresses patient throughput related problems at the hospital by seeking to improve the EVS bed turnaround process. This process is defined as the time from when the EVS system is notified that a bed is ready for turnaround, to the time that the room is prepared for the next patient. The primary objective of the project is to reduce the cycle time of the process. The project considers improvements to the scheduling, communication, and standardization of this process by delivering data supported process improvements, industry best practices, and tools for improved communication and feedback. The project succeeds in sustainably reducing the cycle time for the bed turnaround process. Additionally, the project analyzes the effects of factors related to patient throughput using an ARENA discrete event simulation model. The factors analyzed are the bed turnaround time, the patient discharge time, and the number of hospital beds.B.S. (Bachelor of Science

An Adaptive Transmission Scheme for Two-Way Relaying with Asymmetric Data Rates

In this paper, we address the problem of asymmetric data rates in two-way communication systems. In particular, we propose an adaptive transmission scheme that combines network coding (NC) and opportunistic user selection (OUS) with a threshold that determines which transmission mode to use. The underlying system model comprises two source nodes communicating with each other through a relay node. The source nodes are assumed to have different data rate requirements; therefore, they employ different modulation schemes. As per the proposed scheme, if the end-to-end (E2E) signal-to-noise ratio (SNR) of both users are above a specified threshold, both sources transmit over orthogonal channels, and the relay node uses hierarchical modulation and NC to relay the combined signals to both sources in the third time slot. Otherwise, the user with the better E2E SNR transmits, whereas the other user remains silent. The advantage of the proposed scheme is that it compromises between throughput and reliability. That is, when both users transmit, the throughput improves, whereas when the better user transmits, multiuser diversity is achieved. Assuming asymmetric channels, we derive exact closed-form expressions for the E2E bit error rate (BER), access probability, and throughput for this scheme and compare its performance with existing schemes. We also investigate the asymptotic performance of the proposed scheme at high SNRs where we derive the achievable diversity order for both users. We show through analytical and simulation results that the proposed scheme improves the overall system throughput, the fairness between the two users, and the transmission reliability. This all comes while achieving full spatial diversity for both users.Scopu

Adaptive Network Coding over Cognitive Relay Networks

We consider network coded cooperation for cognitive relay networks. The primary system comprises multiple sources and multiple destinations, whereas the secondary system comprises multiple sources, multiple relays and a single destination. We derive a closed form expression for the end-to-end outage probability for the secondary system while assuming the presence of interference constraints between the two sub-systems. Based on the diversity order analysis, we propose a framework for adaptive network coding. The proposed scheme involves using a small encoding set size for low link quality and a large encoding set for good link quality. Having a small set size increases the probability of having relay cooperation, which comes at the expense of some loss in coding gain, whereas using a large encoding set size decreases the probability of having relay cooperation, but achieves some network coding gains. Therefore, there is a fundamental trade-off between the probability of relay cooperation and the achievable network coding gains. Using numerical results, we show that the proposed adaptive network coding achieves up to 5 dB gain at target outage 10^−3 as compared to conventional fixed network coding schemes.Qatar National Research Fund NPRP 09-126-2-05

Successful therapy of collagen-induced arthritis with TNF receptor-IgG fusion protein and combination with anti-CD4.

We have previously shown that anti-tumour necrosis factor (TNF) monoclonal antibody (mAb) ameliorates established collagen-induced arthritis and that the efficacy of this form of treatment can be enhanced by concurrent anti-CD4 treatment. Here we assess the efficacy of a human p55 TNF receptor-IgG fusion protein (p55-sf2), given alone or with anti-CD4 mAb. TNF receptor-IgG fusion protein (100 micrograms) suppressed paw swelling and limb recruitment in established arthritis and reduced the incidence of erosions in the proximal interphalangeal joints from 92% to 50%, which was comparable to 41% erosions using anti-TNF mAb. Methylprednisolone acetate (4.2 mg/kg/week) reduced clinical signs of inflammation in a manner comparable to TNF blockade but had little effect on the incidence of erosions. Co-administration of anti-CD4 and TNF receptor-IgG led to an even greater therapeutic effect than TNF receptor-IgG alone, with the incidence of erosions being reduced from 100% to 17%. Serological analyses showed that the beneficial effects of anti-CD4 and TNF receptor-IgG could be partly explained by the ability of anti-CD4 to prevent a neutralizing antibody response. These results confirm the importance of TNF in destructive inflammatory arthritis and demonstrate the feasibility of therapeutically targeting TNF with a form of TNF receptor. Finally, the findings confirm the beneficial effects of TNF-targeted therapy coupled with anti-CD4 therapy

Priority-Based Zero-Forcing in Spectrum Sharing Cognitive Systems

We consider a spectrum sharing scenario between cognitive radio (CR) users and a licensed primary user (PU), in which the PU is not able to successfully transmit data to its destined receiver. The cognitive base station (CBS) in the vicinity of the primary network, offers its help to transmit the primary data. In return, the CR system is able to share the spectrum with the primary system. We formulate an opportunistic spectrum sharing approach that determines the transmit beamforming weights in order to maximize the overall throughput of the CRs while guaranteeing the quality-of-service (QoS) of the PU. By applying algorithms based on zero-forcing beamforming (ZFB) along with optimal power allocation, the proposed approach is able to achieve cognitive and primary systems requirements

Opportunistic Spectrum Sharing in Relay-Assisted Cognitive Systems With Imperfect CSI

In this paper, we consider spectrum sharing between cognitive radio (CR) users and a licensed primary user (PU) to enhance the spectrum efficiency. In the considered scenario, the PU is not able to successfully transmit data to the intended receiver. In this case, the cognitive base station (CBS) in the vicinity of the primary network offers its help to transmit the primary data. In return, the CR system shares the spectrum with the primary system. In particular, we formulate an opportunistic spectrum sharing approach that determines the optimal beamforming weights at the CBS to maximize the overall worst throughput of the CRs while guaranteeing a certain quality of service (QoS) for the PU. Various formulations of beamforming are proposed, which consider different relaying scenarios, including robust designs that are applicable with imperfect channel state information (CSI) at the PU. The original optimization problems are nonconvex and do not have any closed-form solutions. However, using a convex optimization approach, we transform them into convex forms and find approximate solutions using semidefinite programming (SDP) along with randomization techniques. We consider different examples that demonstrate the efficiency of the proposed approach