Link Quality Control Mechanism for Selective and Opportunistic AF Relaying in Cooperative ARQs: A MLSD Perspective

Incorporating relaying techniques into Automatic Repeat reQuest (ARQ) mechanisms gives a general impression of diversity and throughput enhancements. Allowing overhearing among multiple relays is also a known approach to increase the number of participating relays in ARQs. However, when opportunistic amplify-and-forward (AF) relaying is applied to cooperative ARQs, the system design becomes nontrivial and even involved. Based on outage analysis, the spatial and temporal diversities are first found sensitive to the received signal qualities of relays, and a link quality control mechanism is then developed to prescreen candidate relays in order to explore the diversity of cooperative ARQs with a selective and opportunistic AF (SOAF) relaying method. According to the analysis, the temporal and spatial diversities can be fully exploited if proper thresholds are set for each hop along the relaying routes. The SOAF relaying method is further examined from a packet delivery viewpoint. By the principle of the maximum likelihood sequence detection (MLSD), sufficient conditions on the link quality are established for the proposed SOAF-relaying-based ARQ scheme to attain its potential diversity order in the packet error rates (PERs) of MLSD. The conditions depend on the minimum codeword distance and the average signal-to-noise ratio (SNR). Furthermore, from a heuristic viewpoint, we also develop a threshold searching algorithm for the proposed SOAF relaying and link quality method to exploit both the diversity and the SNR gains in PER. The effectiveness of the proposed thresholding mechanism is verified via simulations with trellis codes.Comment: This paper has been withdrawn by the authors due to an improper proof for Theorem 2. To avoid a misleading understanding, we thus decide to withdraw this pape

Enabling Work-conserving Bandwidth Guarantees for Multi-tenant Datacenters via Dynamic Tenant-Queue Binding

Today's cloud networks are shared among many tenants. Bandwidth guarantees and work conservation are two key properties to ensure predictable performance for tenant applications and high network utilization for providers. Despite significant efforts, very little prior work can really achieve both properties simultaneously even some of them claimed so. In this paper, we present QShare, an in-network based solution to achieve bandwidth guarantees and work conservation simultaneously. QShare leverages weighted fair queuing on commodity switches to slice network bandwidth for tenants, and solves the challenge of queue scarcity through balanced tenant placement and dynamic tenant-queue binding. QShare is readily implementable with existing switching chips. We have implemented a QShare prototype and evaluated it via both testbed experiments and simulations. Our results show that QShare ensures bandwidth guarantees while driving network utilization to over 91% even under unpredictable traffic demands.Comment: The initial work is published in IEEE INFOCOM 201

Demonstration of Einstein-Podolsky-Rosen Steering with Enhanced Subchannel Discrimination

Einstein-Podolsky-Rosen (EPR) steering describes a quantum nonlocal phenomenon in which one party can nonlocally affect the other's state through local measurements. It reveals an additional concept of quantum nonlocality, which stands between quantum entanglement and Bell nonlocality. Recently, a quantum information task named as subchannel discrimination (SD) provides a necessary and sufficient characterization of EPR steering. The success probability of SD using steerable states is higher than using any unsteerable states, even when they are entangled. However, the detailed construction of such subchannels and the experimental realization of the corresponding task are still technologically challenging. In this work, we designed a feasible collection of subchannels for a quantum channel and experimentally demonstrated the corresponding SD task where the probabilities of correct discrimination are clearly enhanced by exploiting steerable states. Our results provide a concrete example to operationally demonstrate EPR steering and shine a new light on the potential application of EPR steering.Comment: 16 pages, 8 figures, appendix include

MARS: Message Passing for Antenna and RF Chain Selection for Hybrid Beamforming in MIMO Communication Systems

In this paper, we consider a prospective receiving hybrid beamforming structure consisting of several radio frequency (RF) chains and abundant antenna elements in multi-input multi-output (MIMO) systems. Due to conventional costly full connections, we design an enhanced partially-connected beamformer employing low-density parity-check (LDPC) based structure. As a benefit of LDPC-based structure, information can be exchanged among clustered RF/antenna groups, which results in a low computational complexity order. Advanced message passing (MP) capable of inferring and transferring data among different paths is designed to support LDPC-based hybrid beamformer. We propose a message passing enhanced antenna and RF chain selection (MARS) scheme to minimize the operational power of antennas and RF chains of the receiver. Furthermore, sequential and parallel MP for MARS are respectively designed as MARS-S and MARS-P schemes to address convergence speed issue. Simulations have validated the convergence of both the MARS-P and the MARS-S algorithms. Owing to asynchronous information transfer of MARS-P, it reveals that higher power is required than that of MARS-S, which strikes a compelling balance between power consumption, convergence, and computational complexity. It is also demonstrated that the proposed MARS scheme outperforms the existing benchmarks using heuristic method of fully-/partially-connected architectures in open literature in terms of the lowest power and highest energy efficiency

Abstracting Imperfect Information Away from Two-Player Zero-Sum Games

In their seminal work, Nayyar et al. (2013) showed that imperfect information can be abstracted away from common-payoff games by having players publicly announce their policies as they play. This insight underpins sound solvers and decision-time planning algorithms for common-payoff games. Unfortunately, a naive application of the same insight to two-player zero-sum games fails because Nash equilibria of the game with public policy announcements may not correspond to Nash equilibria of the original game. As a consequence, existing sound decision-time planning algorithms require complicated additional mechanisms that have unappealing properties. The main contribution of this work is showing that certain regularized equilibria do not possess the aforementioned non-correspondence problem -- thus, computing them can be treated as perfect information problems. Because these regularized equilibria can be made arbitrarily close to Nash equilibria, our result opens the door to a new perspective on solving two-player zero-sum games and, in particular, yields a simplified framework for decision-time planning in two-player zero-sum games, void of the unappealing properties that plague existing decision-time planning approaches