Uplink Linear Receivers for Multi-cell Multiuser MIMO with Pilot Contamination: Large System Analysis

Base stations with a large number of transmit antennas have the potential to serve a large number of users at high rates. However, the receiver processing in the uplink relies on channel estimates which are known to suffer from pilot interference. In this work, making use of the similarity of the uplink received signal in CDMA with that of a multi-cell multi-antenna system, we perform a large system analysis when the receiver employs an MMSE filter with a pilot contaminated estimate. We assume a Rayleigh fading channel with different received powers from users. We find the asymptotic Signal to Interference plus Noise Ratio (SINR) as the number of antennas and number of users per base station grow large while maintaining a fixed ratio. Through the SINR expression we explore the scenario where the number of users being served are comparable to the number of antennas at the base station. The SINR explicitly captures the effect of pilot contamination and is found to be the same as that employing a matched filter with a pilot contaminated estimate. We also find the exact expression for the interference suppression obtained using an MMSE filter which is an important factor when there are significant number of users in the system as compared to the number of antennas. In a typical set up, in terms of the five percentile SINR, the MMSE filter is shown to provide significant gains over matched filtering and is within 5 dB of MMSE filter with perfect channel estimate. Simulation results for achievable rates are close to large system limits for even a 10-antenna base station with 3 or more users per cell.Comment: Accepted for publication in IEEE Transactions on Wireless Communication

Cellular Systems with Many Antennas: Large System Analysis under Pilot Contamination

Base stations with a large number of transmit antennas have the potential to serve a large number of users simultaneously at higher rates. They also promise a lower power consumption due to coherent combining at the receiver. However, the receiver processing in the uplink relies on the channel estimates which are known to suffer from pilot interference. In this work, we perform an uplink large system analysis of multi-cell multi-antenna system when the receiver employs a matched filtering with a pilot contaminated estimate. We find the asymptotic Signal to Interference plus Noise Ratio (SINR) as the number of antennas and number of users per base station grow large while maintaining a fixed ratio. To do this, we make use of the similarity of the uplink received signal in a multi-antenna system to the representation of the received signal in CDMA systems. The asymptotic SINR expression explicitly captures the effect of pilot contamination and that of interference averaging. This also explains the SINR performance of receiver processing schemes at different regimes such as instances when the number of antennas are comparable to number of users as well as when antennas exceed greatly the number of users. Finally, we also propose that the adaptive MMSE symbol detection scheme, which does not require the explicit channel knowledge, can be employed for cellular systems with large number of antennas.Comment: 5 pages, 4 figure

Tree based reliable topology for distributing link state information

Finding paths that satisfy the performance requirements of applications according to link state information in a network is known as the Quality-of- Service (QoS) routing problem and has been extensively studied. However, distributing link state information may introduce a significant protocol overhead on network resources. In this thesis, the issue on how to update link state information efficiently and effectively is investigated. A theoretical framework is presented, and a high performance link state policy that is capable of minimizing the false blocking probability of connections under a given update rate constraint is proposed. Through theoretical analysis, it is shown that the proposed policy outperforms the current state of the art in terms of the update rate and higher scalability and reliability

Leveraging Global Resources: A Process Maturity Framework for Managing Distributed Software Product Development

Distributed software development is pervasive in the software industry as companies vie to leverage global resources. However popular quality and process frameworks do not specifically address the key processes needed for managing distributed software development. We develop an evolutionary process maturity framework for globally distributed software development that incorporates 24 new key process areas essential for managing distributed software product development We test the validity of our process framework using data collected from more than sixty large, distributed enterprise product development projects. We believe we have laid new ground for software process research by extending generic quality process frameworks to address the distributed development scenario

Leveraging global resources: A distributed process maturity framework for software product development

Distributed software development is pervasive in the software industry as companies vie to leverage global resources. However popular quality and process frameworks do not specifically address the key processes needed for managing distributed software development. We develop an evolutionary process maturity framework for globally distributed software development that incorporates 24 new key process areas essential for managing distributed software product development We test the validity of our process framework using data collected from more than sixty large, distributed enterprise product development projects. We believe we have laid new ground for software process research by extending generic quality process frameworks to address the distributed development scenario

Does complexity deter customer‐focus?

Economic models suggest that firms use a simple cost‐benefit calculation to evaluate customer requests for new product features, but an extensive organizational literature shows the decision to implement innovation is more nuanced. We address this theoretical tension by studying how firms respond to customer requests for incremental product innovations, and how these responses change when the requested innovation is complex. Using large sample empirical analyses combined with detailed qualitative data drawn from interviews, we find considerable variance in the relationship between customer demands, complexity, and investments in incremental innovations. The qualitative study revealed the importance of organization structures, competitive pressures, and incentives for resource allocation processes. Copyright © 2011 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89508/1/947_ftp.pd

Effect of Website Characteristics on Consumer Behavior: A Multilevel Analysis

This paper uses a hierarchical linear modeling approach to examine factors that affect Website effectiveness from a customer viewpoint. Use of hierarchical linear modeling allows analysis of multilevel and cross-level interactions that have not been explicitly considered in previous research. Our preliminary analysis of online Web survey data suggests that the relative importance of different Website features may vary depending on the domain in which Websites are nested