Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G

We investigate Early Hybrid Automatic Repeat reQuest (E-HARQ) feedback schemes enhanced by machine learning techniques as a path towards ultra-reliable and low-latency communication (URLLC). To this end, we propose machine learning methods to predict the outcome of the decoding process ahead of the end of the transmission. We discuss different input features and classification algorithms ranging from traditional methods to newly developed supervised autoencoders. These methods are evaluated based on their prospects of complying with the URLLC requirements of effective block error rates below $10^{-5}$ at small latency overheads. We provide realistic performance estimates in a system model incorporating scheduling effects to demonstrate the feasibility of E-HARQ across different signal-to-noise ratios, subcode lengths, channel conditions and system loads, and show the benefit over regular HARQ and existing E-HARQ schemes without machine learning.Comment: 14 pages, 15 figures; accepted versio

Performance of cognitive stop-and-wait hybrid automatic repeat request in the face of imperfect sensing

The cognitive radio (CR) paradigm has the potential of improving the exploitation of the electromagnetic spectrum by detecting instantaneously unoccupied spectrum slots allocated to primary users (PUs). In order to support the process of spectrum reuse, we consider a CR scheme, which senses and opportunistically accesses a PU's spectrum for communication between a pair of nodes relying on the stop-and-wait hybrid automatic repeat request (SW-HARQ) protocol. This arrangement is represented by the cognitive SW-HARQ (CSW-HARQ), where the availability/unavailability of the PU's channel is modeled as a two-state Markov chain having OFF and ON states, respectively. Once the cognitive user (CU) finds that the PU's channel is available (i.e., in the OFF state), the CU transmits data over the PU channel's spectrum, while relying on the principles of SW-HARQ. We investigate both the throughput and the delay of CSW-HARQ, with a special emphasis on the impact of the various system parameters involved in the scenarios of both perfect and imperfect spectrum sensing. Furthermore, we analyze both the throughput as well as the average packet delay and end-to-end packet delay of the CSW-HARQ system. We propose a pair of analytical approaches: 1) the probability-based and 2) the discrete time Markov chain-based. Closed-form expressions are derived for both the throughput and the delay under the perfect and imperfect sensing environments that are validated by simulation. We demonstrate that the activity of PUs, the transmission reliability of the CU, and the sensing environment have a significant impact on both the throughput and the delay of the CR system

Robust scheduling algorithm for Guaranteed Bit Rate services

This paper proposes a novel packet scheduling algorithm to overcome detrimental effects of channel impairments on the quality of service of delay-sensitive Guaranteed Bit Rate (GBR) services. The proposed algorithm prioritises the packets that require retransmission of Hybrid Automatic Repeat Request (HARQ) users compared to the packets of new users. The packets of new users are scheduled according to the Channel Quality Information (CQI), average throughput and packet delay information. Computer simulations have demonstrated that the proposed algorithm has 22.7% system capacity improvement over a well-known algorithm. It also tolerates for up to 200% delay of CQI and reduces the uplink signalling overhead by 150% compared to the well-known algorithm without compromising the quality of service requirements of the GBR services. Copyright © 2013 Inderscience Enterprises Ltd

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table