Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can address a number of challenges the operators face while trying to support growing end-user's needs. The main idea behind C-RAN is to pool the Baseband Units (BBUs) from multiple base stations into centralized BBU Pool for statistical multiplexing gain, while shifting the burden to the high-speed wireline transmission of In-phase and Quadrature (IQ) data. C-RAN enables energy efficient network operation and possible cost savings on baseband resources. Furthermore, it improves network capacity by performing load balancing and cooperative processing of signals originating from several base stations. This paper surveys the state-of-the-art literature on C-RAN. It can serve as a starting point for anyone willing to understand C-RAN architecture and advance the research on C-RAN.

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Cloud RAN for Mobile Networks—A Technology Overview

Femtocells, despite their name, pose a potentially large disruption to the carefully planned cellular networks that now connect a majority of the planet's citizens to the Internet and with each other. Femtocells - which by the end of 2010 already outnumbered traditional base stations and at the time of publication are being deployed at a rate of about five million a year - both enhance and interfere with this network in ways that are not yet well understood. Will femtocells be crucial for offloading data and video from the creaking traditional network? Or will femtocells prove more trouble than they are worth, undermining decades of careful base station deployment with unpredictable interference while delivering only limited gains? Or possibly neither: are femtocells just a "flash in the pan"; an exciting but short-lived stage of network evolution that will be rendered obsolete by improved WiFi offloading, new backhaul regulations and/or pricing, or other unforeseen technological developments? This tutorial article overviews the history of femtocells, demystifies their key aspects, and provides a preview of the next few years, which the authors believe will see a rapid acceleration towards small cell technology. In the course of the article, we also position and introduce the articles that headline this special issue.

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Femtocells: Past, Present, and Future

This paper provides a comprehensive study of interleave-division multiple-access (IDMA) systems. The IDMA receiver principles for different modulation and channel conditions are outlined. A semi-analytical technique is developed based on the density evolution technique to estimate the bit-error-rate (BER) of the system. It provides a fast and relatively accurate method to predict the performance of the IDMA scheme. With simple convolutional/repetition codes, overall throughputs of 3 bits/chip with one receive antenna and 6 bits/chip with two receive antennas are observed for IDMA systems involving as many as about 100 users.

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Interleave division multiple-access

Embedding pico/femto base-stations and relay nodes in a macro-cellular network is a promising method for achieving substantial gains in coverage and capacity compared to macro-only networks. These new types of base-stations can operate on the same wireless channel as the macro-cellular network, providing higher spatial reuse via cell splitting. However, these base-stations are deployed in an unplanned manner, can have very different transmit powers, and may not have traffic aggregation among many users. This could potentially result in much higher interference magnitude and variability. Hence, such deployments require the use of innovative cell association and inter-cell interference coordination techniques in order to realize the promised capacity and coverage gains. In this paper, we describe new paradigms for design and operation of such heterogeneous cellular networks. Specifically, we focus on cell splitting, range expansion, semi-static resource negotiation on third-party backhaul connections, and fast dynamic interference management for QoS via over-the-air signaling. Notably, our methodologies and algorithms are simple, lightweight, and incur extremely low overhead. Numerical studies show that they provide large gains over currently used methods for cellular networks.

Cell Association and Interference Coordination in Heterogeneous LTE-A Cellular Networks

Pacing the way toward 5G has lead researchers and industry in the direction of centralized processing known from Cloud-Radio Access Networks (C-RAN). In C-RAN research, a variety of different functional splits is presented by different names and focusing on different directions. The functional split determines how many base station functions to leave locally, close to the user, with the benefit of relaxing fronthaul network bitrate and delay requirements, and how many functions to centralize with the possibility of achieving greater processing benefits. This paper presents for the first time a comprehensive overview systematizing the different work directions for both research and industry, while providing a detailed description of each functional split option and an assessment of the advantages and disadvantages. This paper gives an overview of where the most effort has been directed in terms of functional splits, and where there is room for further studies. The standardization currently taking place is also considered and mapped into the research directions. It is investigated how the fronthaul network will be affected by the choice of functional split, both in terms of bitrates and latency, and as the different functional splits provide different advantages and disadvantages, the option of flexible functional splits is also looked into.

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A Survey of the Functional Splits Proposed for 5G Mobile Crosshaul Networks

In this paper, we develop novel Bayesian detection methods that are applicable to both synchronous code-division multiple-access and multiple-input multiple-output communication systems. Markov chain Monte Carlo (MCMC) simulation techniques are used to obtain Bayesian estimates (soft information) of the transmitted symbols. Unlike previous reports that widely use statistical inference to estimate a posteriori probability (APP) values, we present alternative statistical methods that are developed by viewing the underlying problem as a multidimensional Monte Carlo integration. We show that this approach leads to results that are similar to those that would be obtained through a proper Rao-Blackwellization technique and thus conclude that our proposed methods are superior to those reported in the literature. We also note that when the channel signal-to-noise ratio is high, MCMC simulator experiences some very slow modes of convergence. Thus accurate estimation of APP values requires simulations of very long Markov chains, which may be infeasible in practice. We propose two solutions to this problem using the theory of importance sampling. Extensive computer simulations show that both solutions improve the system performance greatly. We also compare the proposed MCMC detection algorithms with the sphere decoding and minimum mean square error turbo detectors and show that the MCMC detectors have superior performance.

Markov chain Monte Carlo algorithms for CDMA and MIMO communication systems

Coherent OFDM detection requires accurate channel state information (CSI). Mobile radio channels are both time and frequency dispersive, especially at high vehicular speeds, which makes channel estimation a challenging problem in system design. Conventional preamble-based and pilot-aided channel estimation require numerous reference signals, which significantly compromises the system throughput. This paper proposes a novel low complexity iterative turbo channel estimation technique which makes use of preamble, pilots and soft decoded data information in an iterative fashion to improve the system performance over the time and frequency selective fading channel while maintaining the system throughput. The numerical and analytical results show that the proposed technique can approach the performance of systems with perfect CSI with much fewer preamble and pilots symbols compared to existing channel estimation methods.

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Iterative Turbo Channel Estimation for OFDM System over Rapid Dispersive Fading Channel

Joint iterative decoding of multiple forward error control (FEC) encoded data streams is studied for linear multiple access channels, such as code-division multiple access (CDMA). It is shown that such systems can be viewed as serially concatenated coding systems, and that iterative soft-decision decoding can be performed successfully To improve power efficiency, powerful FEC codes are used. These FEC codes are themselves serially concatenated. The overall transmission system can be viewed as the concatenation of two error control codes with the linear multiple access channel, and soft-decision decoders are used at each stage. A variance transfer function approach applied to the analysis of this system captures the role of the component decoders in an overall iterative decoding system. We show that this approach forms a methodology to study the effects of the component codes as well as that of the iteration schedule. Analysis and simulation examples are presented for transmission systems that operate close to the Shannon limit and illustrate the accuracy of the analysis.

Joint iterative decoding of serially concatenated error control coded CDMA

This invention addresses the problem of channel estimation in fast fading communications channels, particularly for OFDM systems. It finds wide application in existing and future systems such as WLAN and WiMax. In particular, the invention involves a method of channel estimation and data detection for rapid dispersive fading channels due to high mobility. The invention involves decoding a symbol of the received transmission by retrieving pilot tones from it and using these to estimate variations in the channel frequency response using an iterative maximum likelihood channel estimation process, in which the estimation process comprises the following steps: In a first iteration, deriving soft decoded data information, that is information having a confidence value or reliability associated with it, from the estimates of the channel frequency response for the symbol obtained from pilot tones. And, in at least a second iteration using the soft decoded data information as virtual pilot tones together with the pilot tones to re-estimate the channel frequency response for the symbol. In other aspects the invention concerns a receiver and software designed to perform the method.

Channel estimation for rapid dispersive fading channels

Iterative interference cancellation of coded code-division multiple access (CDMA) using random spreading with linear cancellation is analyzed. If users are grouped into power classes and Shannon bound approaching codes are used, a geometric power distribution achieves the additive white Gaussian noise (AWGN) channel Shannon bound as the numbers of classes becomes large. The optimal distribution of the size of these classes is shown to be uniform. If users are grouped into different rate classes with equal powers among equal rate users, the Shannon bound for AWGN channels can be achieved with an arbitrary distribution of the classes sizes, provided that the size of the largest rate class obeys the mild condition that its ratio of size to processing gain is much smaller than the inverse of the signal-to-noise ratio (SNR). The case of equal powers and equal rates among all users is addressed as a "worst case" scenario. It is argued that simple repetition codes provide for a larger achievable capacity than stronger codes. It is shown that this capacity monotonically increases as the rate of the code decreases. A density evolution analysis is used to show that the achievable rates exceed those of a minimum-mean square error filter applied to the uncoded signals. This lower bound is tight for small ratios of bit energy to noise power, and otherwise the iterative cancellation receiver provides an appreciably larger capacity. Relating to recent result from the application of statistical mechanics it is shown that the repetition-coded system with iterative cancellation achieves the performance of an equivalent optimal joint detector for uncoded transmission

http://www.ece.ualberta.ca/%7Ehcdc/Library/PowerPaper.pdf

Zhenning Shi

Papers

Markov chain Monte Carlo algorithms for CDMA and MIMO communication systems

Iterative Turbo Channel Estimation for OFDM System over Rapid Dispersive Fading Channel

Joint iterative decoding of serially concatenated error control coded CDMA

Channel estimation for rapid dispersive fading channels

Optimal Power/Rate Allocation and Code Selection for Iterative Joint Detection of Coded Random CDMA