Simon Yiu

Uncoordinated Beamforming for Cognitive Networks

In this paper, we propose jointly-optimized beam-forming algorithms for cognitive networks to maximize the achievable rates assuming single information stream in both primary and secondary links. The primary and cognitive users share the same spectrum and are equipped with multiple antennas. No coordination is required between the primary and cognitive users and the interference cancellation is done at the cognitive user. Specifically, the beamforming vectors of the cognitive link are designed to maximize the achievable rate under the condition that the interference both at the primary and cognitive receivers is completely nullified. The sum rate performance of the proposed algorithms is evaluated by Monte Carlo simulations.

On the high capacity lightradio™ metro cell design for stadiums

Offering good quality of experience (QoE) in stadiums poses unprecedented challenges to wireless operators, due to extreme traffic conditions. During popular sporting events, there could be tens of thousands of active users packed into a relatively small area, sharing pictures and video clips through smartphone applications. This creates high traffic densities and drives requirements for high capacity, yet economically feasible solutions for stadiums. Ensuring high capacity in open environments with high interference such as these is a daunting task. In this paper we explain why Alcatel-Lucents lightRadio™ metro cells offer a good solution for stadium deployments due to their particular ability to provide high “local” capacity. We demonstrate key design concepts employed to achieve a target capacity with lightRadio metro cells including the number of metro cells and their optimal locations, power levels, antenna patterns and orientation, and frequency reuse patterns. We further quantify the capacity benefits of using metro cells through a comprehensive performance analysis framework using Long Term Evolution (LTE) as an example.

Coordinated dual-layer beamforming for public safety network: Architecture and algorithms

The revolutionary success of commercial broadband wireless network has spurred significant interest in employing related technologies such as 3GPP long term evolution (LTE) technologies to build a nationwide mobile broadband network for public safety entities. The successful deployment and operation of a public safety network, however, are more challenging than the traditional commercial wireless networks due to the high reliability and security requirements, unpredictable traffic patterns, and fast time-varying user population density. In this paper, we propose a framework of coordinated dual-layer beamforming schemes to address these challenges. The distinct features of the proposed systems are detailed and the architecture and realization are discussed. While a smart antenna is capable of forming multiple beams, it is unlikely to activate all of them simultaneously. We thus develop efficient beam scheduling algorithms that could adapt to the time-varying channel conditions and traffic loads by adaptively adjusting the beam switching sequence. We also reveal that the coordinated dual-layer beamforming technologie not only has the potential of significantly enhancing the system capacity, but also can turn a NP-complete beam scheduling problem into a problem that can be easily solved if network MIMO technologies are employed. It is seen through simulation studies that the proposed schemes could offer multi-fold capacity improvements over more traditional systems equipped with broader antenna patterns (e.g., omnidirectional). Also, while we focus on public safety network in this paper, the proposed coordinated dual-layer beamforming framework can be equally applied to provide mobile access to any hotspot area with dense mobile users, e.g., a conference room or a stadium.

Wireless RSSI fingerprinting localization

Localization has attracted a lot of research effort in the last decade due to the explosion of location based service (LBS). In particular, wireless fingerprinting localization has received much attention due to its simplicity and compatibility with existing hardware. In this work, we take a closer look at the underlying aspects of wireless fingerprinting localization. First, we review the various methods to create a radiomap. In particular, we look at the traditional fingerprinting method which is based purely on measurements, the parametric pathloss regression model and the non-parametric Gaussian Process (GP) regression model. Then, based on these three methods and measurements from a real world deployment, the various aspects such as the density of access points (APs) and impact of an outdated signature map which affect the performance of fingerprinting localization are examined. At the end of the paper, the audiences should have a better understanding of what to expect from fingerprinting localization in a real world deployment.

Gaussian Process Assisted Fingerprinting Localization

This paper presents an application of the firefly algorithm (FA) to Gaussian process (GP)-based localization. Partial radio-frequency (RF) signature map is first collected and used to train the GP model. The hyperparameters of the GP prior model are searched by the FA. GP regression is then used to generate an estimation of the RF signature map for the entire area to be localized. This is in contrast to traditional fingerprinting-based localization where a database of RF signature has to be collected for the entire area of interest. Using the estimated signature map, the position of the device is estimated using a combined likelihood function from multiple access points (APs). The proposed scheme relies on only existing infrastructures and can be used both indoor and outdoor. Experiments using indoor WiFi APs show that median error is around 3 m.

Distributed Beam Scheduling in Multi-Cell Networks via Auction over Competitive Markets

The capacity of a wireless network could be considerably improved by employing directional antennas that are capable of illuminating multiple beams toward different directions. However, more beams from the same BS may lead to stronger inter-cell interference. In this paper, we consider coordinated beam scheduling schemes to mitigate the inter-cell interference. We first formulate this problem as a combinatorial optimization problem. We then reveal that the complexity of this problem hinges upon a single scalar termed as degree of constraint (DoC), which is related to the degree of conflict a beam is subject to. If the DoC is at least three, the general beam scheduling problem is NP-hard. If DoC is smaller than three, which corresponds to a relevant subclass of the beam scheduling problem arising in practice, this problem can be solved in polynomial time. We propose an optimal beam scheduling algorithm based on the auction method to this particular subclass of problem. This algorithm is of low complexity and is well suited for distributed implementations. We then extend the auction algorithm to solve the general multi-cell beam scheduling problem. The performance of the proposed algorithms is finally assessed through extensive simulation studies.

Locating user equipments and access points using RSSI fingerprints: A Gaussian process approach

Location fingerprinting (LF) is an attractive localization technique which relies on existing infrastructures. The major drawback of LF is the requirement of having an updated fingerprint database. Gaussian Process (GP) is a non-parametric modeling technique which can be used to model the received signal strength indicator (RSSI) and create the fingerprint database based on few training data. In this paper we use a parametric pathloss model for the GP mean and a flexible non-parametric covariance function, so we can get reliable estimates with low fingerprinting effort. In our experiment, we show that with 23 fingerprint locations we perform as well as traditional fingerprinting with over 230 fingerprinted locations for an office space of 2500m2.

Distributed STBC-OFDM and distributed SFBC-OFDM for frequency-selective and time-varying channels

Distributed space-time block coding with orthogonal frequency division multiplexing (DSTBC-OFDM) and distributed space-frequency block coding with orthogonal frequency division multiplexing (DSFBC-OFDM) are introduced in this paper. Unlike the original DSTBC scheme which was designed for networks with a fixed number of relays operating in frequency-nonselective channels with insignificant Doppler spread, the proposed schemes are designed specifically for networks with an arbitrary number of relays and wireless channels with significant delay spread and Doppler spread. It is shown that geographically distributed antennas employing the new transmission schemes in a frequency-selective and severe Doppler spread environment can achieve the same performance (in terms of diversity gain and coding gain) as the previously proposed scheme.

Modeling 5G wireless network service reliability prediction with bayesian network

In 5G networks, prediction of service reliability is critical because of strict service performance requirements. In this work, we present a wireless service model for reliability computation, and we use Bayesian network (BN) to compactly represent the joint probability distribution. Furthermore, we use the model to predict network service reliability and infer hidden states of a network. Our approach provides a promising direction for modeling network service reliability and insight in designing next generation networks which comply with high service quality requirements.

Is conflict always bad? From an interference management perspective

In this paper, we first introduce a simple two-cell multiple-input multiple-output (MIMO) solution where each base station has only its own data message. The algorithm is based on limited feedback from the mobile station (MS). We assume there is no base station (BS) cooperation through backbone; therefore cooperation among BSs is not a requirement. This renders the concept of the proposed solution easier for product implementation. To extend the algorithm to a multi-cell scenario, we next propose a novel physical beam-switching method based on the proposed two-cell MIMO solution. Conventionally, all BSs align the beam directions to avoid inter-cell interference. In this paper, however, we propose using a different beam-switching method based on beam conflict. Instead of aligning all the beams, we intentionally create a strong interference term. In doing so, all but the strongest interference is significantly reduced; the strongest interference term is further removed/minimized by the proposed two-cell MIMO solution. This results in increasing the received signal-to-noise-plus-interference ratio (SINR). Unlike prior work, our solution creates and utilizes the conflict, that is, the conflict is useful. That the conflict significantly helps multi-cell systems improve throughput is confirmed through numerical results.