Fiber link design considerations for cloud-Radio Access Networks

Analog radio over fiber (RoF) links may offer advantages for cloud-Radio Access Networks in terms of component cost, but the behavior of the distortion with large numbers of subcarriers needs to be understood. In this paper, this is presented in terms of the variation between subcarriers. Memory polynomial predistortion is also shown to compensate for RoF and wireless path distortion. Whether for digitized or analog links, it is shown that appropriate framing structure parameters must be used to assure performance, especially of time-division duplex systems

Experimental analysis of single and multiple antenna units in uplink of radio-over-fiber distributed antenna system

Increasing the number of antennas either at the transmitter or receiver has been shown to improve system reliability without occupying additional spectrum. In this paper, we experimentally investigate the error vector magnitude (EVM) of single and multiple remote antenna units (RAU) focusing on uplink transmission. We demonstrate that for 64-QAM modulation, the EVM requirement of 6.5% could be achieved with multiple separated RAUs in situations where a single RAU fails to meet this requirement. The EVM result was obtained as the transmitting device was placed at different locations in a typical office environment with OFDM signals gathered through the RAUs and brought back to a central unit for processing. The EVM results show that using multiple RAUs and an efficient signal combining technique, here, maximal ratio combining (MRC), the EVM performance could reduce by approximately 2% when the distance between the RAUs was 0.3m and further reduced by 4% and 6% when the inter-RAU distance was 2m and 4m, respectively, compared to a single RAU

Hierarchical forecast reconciliation with machine learning

Hierarchical forecasting methods have been widely used to support aligned decision-making by providing coherent forecasts at different aggregation levels. Traditional hierarchical forecasting approaches, such as the bottom-up and top-down methods, focus on a particular aggregation level to anchor the forecasts. During the past decades, these have been replaced by a variety of linear combination approaches that exploit information from the complete hierarchy to produce more accurate forecasts. However, the performance of these combination methods depends on the particularities of the examined series and their relationships. This paper proposes a novel hierarchical forecasting approach based on machine learning that deals with these limitations in three important ways. First, the proposed method allows for a non-linear combination of the base forecasts, thus being more general than the linear approaches. Second, it structurally combines the objectives of improved post-sample empirical forecasting accuracy and coherence. Finally, due to its non-linear nature, our approach selectively combines the base forecasts in a direct and automated way without requiring that the complete information must be used for producing reconciled forecasts for each series and level. The proposed method is evaluated both in terms of accuracy and bias using two different data sets coming from the tourism and retail industries. Our results suggest that the proposed method gives superior point forecasts than existing approaches, especially when the series comprising the hierarchy are not characterized by the same patterns

The effect of different queuing regimes on a Switched Ethernet fronthaul

This paper investigates the effects of different queuing regimes on the mean and standard deviation of the frame inter-arrival delay of a LTE traffic stream under the presence of background Ethernet traffic. The background traffic is used to represent traffic that would be generated by different functional subdivisions in the physical layer of traditional LTE base station. In this work, a Switched Ethernet architecture is used as the fronthaul section of a Cloud Radio Access Network (C-RAN). Contention in this fronthaul becomes an important issue since different traffic streams originating from different functional subdivisions with different quality of service specifications will be transmitted over the same physical links. Trunk ports then, will have to handle the queuing management and prioritization. Handling the traffic with different queuing regimes will reflect on the latency and latency variations of the LTE traffic

Does indoor environmental quality affect students' performance?

There is little knowledge on if and how indoor environmental quality influences students’ attendance and productivity. However, this issue has been of growing interest the recent years in the scientific community and results are showing that student learning performance is significantly affected by indoor environmental quality factors. In the present study the learning performance is examined through numerical test scores achieved by primary school students in their classrooms. The assessment of indoor environmental quality parameters such as thermal, visual, acoustic and air quality and the evaluation of Sick Building Syndrome (SBS) symptoms was conducted through questionnaires handed out to the same sample of students. Main objective of this paper is to investigate whether the degradation of the indoor environmental quality can impact the overall performance of students

Optical Fronthaul Options for Meeting 5G Requirements

New functional splits for the 5G Radio Access Network have been identified so that fronthaul will no longer need to transport sampled time-domain waveforms. However, the different functional split points place differing demands on the fronthaul transport, while also posing different constraints to 5G techniques, such as massive MIMO. According to these conflicting demands, it is likely that in many cases, more than one split point may be needed in the same radio access network

The new flexible mobile fronthaul: Digital or analog, or both?

It has become apparent that current fronthaul technology cannot be simply extended to meet the projected demands of 5G and beyond mobile systems. This current technology, based on the transport of sampled radio waveforms, has been the preferred option, with analog radio over fiber reserved to relatively niche application scenarios. However, for future systems, it is recognised that different functional splits between the central location and the remote units are needed; sampled waveform transport is not scalable to these systems. We propose a flexible fronthaul, therefore, in which both digital and analog transport technologies can coexist. Using practical examples from our work, we describe where these technologies can be used in the future fronthaul

Statistical distribution of packet inter-arrival rates in an Ethernet fronthaul

This paper investigates the effects of background traffic streams in the packet inter-arrival rates of an LTE traffic stream, when these streams are transported over the same Ethernet fronthaul network. Contention of background traffic with LTE traffic can occur in a Cloud-RAN that is transporting traffic streams originating from Constant Bit-Rate (CBR) sources such as the Common Public Radio Interface (CPRI) and from other non-CBR sources originating from different LTE physical layer functional subdivisions. Packet inter-arrival statistics are important in such a network, as they can be used to estimate and/or predict buffer sizes in receiving network nodes. Buffer management will also be important for traffic streams originating from functional splits (such as direct LTE MAC transport block transportation) where user plane data and control primitives have to be time aligned at the receiving node

An Ethernet-Based Fronthaul Implementation with MAC/PHY Split LTE Processing

A testbed implementation for an Ethernet fronthaul transporting signals arising from a long-term evolution (LTE) functional subdivision (“split”) at the media-access control (MAC)/physical layer (PHY) interface is presented. Based on open LTE base station software, the testbed demonstrates significant data rate reductions compared to current fronthaul implementations that rely on In-phase and Quadrature radio sample transportation and data rates that scale with cell load. All generated traffic flows are clearly distinguishable using appropriate packet headers. A selection of test cases and their corresponding results are presented to demonstrate the operation of the fronthaul and the performance of individual flows in terms of data rates and overheads

A Flexible Subcarrier Multiplexing System with Analog Transport and Digital Processing for 5G (and beyond) Fronthaul

A flexible subcarrier multiplexing system combining analog transport with digital domain processing is presented. By making use of band-pass sampling and applying a systematic mapping of signals into available Nyquist zones, the multiplexing system is able to present multiple signals at the same intermediate frequency at the remote site. This simplifies the processing required for multiple antenna systems. We further propose the use of track-and-hold amplifiers at the remote site. These elements are used to extend the mapping to a mapping hierarchy, offering flexibility in frequency placement of signals and relaxation of analog-to-digital converter bandwidth and sampling rate constraints. The system allows the transport of different numerologies in a number of next generation radio access network scenarios. Experimental results for large signal multiplexes with both generic and 5th-generation mobile numerologies show error-vector magnitude performance well within specifications, validating the proposed system. Simulation results from a system model matched to these experimental results provide performance predictions for larger signal multiplexes and larger bandwidths