Dr. Tripathi, a Principal Consultant at Award Solutions, joined Award Solutions in March 2004, bringing his knowledge and experience in mobile wireless technologies to facilitate the planning, development and delivery of technical training seminars. He teaches and consults on various technologies including, LTE E-UTRAN and EPC, WiMAX, UMTS R99, HSDPA, HSUPA, HSPA+, 1xEV-DO, IMS, and WiMAX. He has taught various aspects of 3G and 4G commercial cellular technologies including but not limited to network operations, network planning, and network optimization.
Since receiving his doctorate in Wireless Communications from Virginia Tech, Dr. Tripathi has held several strategic positions in the wireless arena. For Nortel Networks, he worked to analyze and optimize the performance of CDMA networks, in such areas as load balancing, handoff, power control, supplemental channel management, and switch antenna diversity. As a Senior Systems Engineer and Product Manager for Huawei Technologies, Dr. Tripathi worked on the infrastructure design and optimization of CDMA2000, 1xEV-DO, and UMTS radio networks. He has significant experience designing, analyzing, and field-testing Radio Resource Management algorithms for CDMA2000 and 1xEV-DO.
In 2001, he co-authored a book on Radio Resource Management, and he is the author of numerous research papers and patent submissions. He has contributed chapters to two books on applications of fuzzy logic to communications and applicability of network neutrality principles to wireless systems. He is a co-author of an upcoming book on cellular communications (to be published by IEEE/Wiley).
Dr. Tripathi's position at Award Solutions puts him at the forefront of emerging technologies. He has authored courseware related to LTE, WiMAX, 1xEV-DO, HSUPA, UMTS optimization, 1xEV-DO RF optimization, advanced antenna techniques, and IP convergence. In addition to teaching the students in the Industry, he also trains his colleagues (i.e., instructors) on various technologies (e.g., LTE, WiMAX, 1xEV-DO, HSDPA, HSUPA, 802.11n, and advanced antenna techniques). His extensive knowledge, hands-on experience with commercial deployments, and enthusiasm for the subject matter, coupled with a passion for teaching, provide the foundation for consistently enjoyable, informative, and effective classes.
By Dr. Nishith Tripathi
A Self-Organizing Network (SON) in LTE (Long Term Evolution)
is a network that automates various tasks related to network planning,
configuration, and optimization. Such automation
reduces the amount of "manual" work, thereby reducing the operating expenditure
(OpEx) for a service operator. The
specific algorithms that implement the SON functionality are not standardized
and are product differentiators for SON vendors. We will briefly summarize below the SON
architecture and SON use cases.
The SON architecture may be centralized, distributed, or
hybrid. In the centralized architecture,
the SON functionality is implemented in the OAM (Operations, Administration,
and Maintenance) system, and, the OAM system communicates with other entities
such as eNodeBs to collect measurements and provide parameter settings. In a distributed architecture, the SON
functionality is implemented at many network elements (NEs) such as eNodeBs. The hybrid architecture, as the name
suggests, is a compromise between the centralized and distributed
architectures, where part of the SON functionality is in the OAM system, and,
part of the functionality is in the NEs.
Let's discuss different ways in which the SON can be
used. The SON, in its most comprehensive
form, can perform three types of functions- self-configuration,
self-optimization, and self-healing. Self-configuration
means that the eNodeB obtains many of its configuration parameters
automatically from the SON upon "power-up."
Self-optimization refers to the process in which the SON digests
information related to network performance and modifies the parameters (e.g.,
handover and random access parameters) to enhance the network performance. Self-healing refers to the mechanism by which
certain failures (e.g., software issues) are detected automatically and
corrective actions are taken (e.g., fallback to a previous software
version). Initial focus of the LTE
standard is on self-configuration and self-optimization, and we will focus on
these two as well here. The UE is
required to support these functions by providing relevant feedback to the
Self-configuration applies to "pre-operational" state, where
the eNodeB has been powered up and has the backbone connectivity but its RF
transmitter has not been turned on yet.
Basic setup and radio configuration are considered part of
self-configuration. During the basic
setup, the eNodeB acquires an IP address and detects an OAM system. Initial radio configuration involves
downloading of some parameter settings (e.g., an initial neighbor list). The use cases for self-configuration
specified by the standard are mentioned below.
Self-optimization is executed in the operational state of
the eNodeB. The UE measurements are
processed by the SON to optimize parameter settings (e.g., an updated neighbor
list). The self-optimization related use
cases specified by the standard are as follows.
In the era of fierce competition and frugality, the SON is
attractive due to its potential for OpEx reduction. However, caution must be exercised while
embracing the SON for automatic and un-supervised determination of critical
parameters. The SON functionality, while
conceptually quite attractive, heavily depends on the design of the SON
algorithms. Until confidence on the SON
algorithms is built up, off-line evaluation of the SON-suggested parameter
changes can yield a wealth of useful information to configure and optimize the
network. Such evaluation could still
provide some OpEx savings while providing a structured method for parameter configuration