Ghaith Hattab

Graduate Research Assistant at UCLA.


[New] Why We Make Resolutions (and Why They Fail) (link here).

[Old]- 5 Powerful Exercises to Increase Your Mental Strength (link here).

[Old]- Mentally Strong People: The 13 Things They Avoid (link here).

[Old]- 6 Things You Should Quit Doing To Be More Successful (link here).

[Old]- 10 Words To Erase From Your Vocabulary (link here)

[Old]- 20 Things 20-Year-Olds Don't Get (link here).

The list will be updated regularly. Also, let me know if any of the links do not work (These articles are not written by me, and the opinions, findings and conclusions, or recommendations expressed in these articles are those of the authors).

Books for Electrical Engineering Students

Below is a list of books that I strongly recommend for cognitive radio, the broad area of wireless communications, signal detection and estimation, convex optimization, and probability and stochastic processes.

Cognitive Radio

Principles of Cognitive Radio, E. Biglieri, A. J. Goldsmith, L. J. Greenstein, N. Mandayam, and H. V. Poor

It is a very recent book (published in December 2012), which thoroughly studies the principles and fundamentals of Cognitive Radio. I believe it can be the first book to be taught at an undergraduate level. 

Wireless Communications

Principles of Digital Communication, R. G. Gallager

This book is written by the renowned communications theorist R. Gallager. He has an incredible teaching style with a unique philosophical approach. A course on the principles of digital communications is taught by him at MIT, and it is available here. His video lectures can be found here  

Principles Digital Communications over Fading Channels, M. K. Simon and M. Sl. Alouini

This book provides a unified framework for the performance analysis of digital communication systems under a variety of fading channels.

Wireless Communications, A. J. Goldsmith
It provides a comprehensive introduction to the underlying theory, design techniques and analytical tools of wireless communications, focusing primarily on the core principles of wireless system design.

Wireless Communications: Principles and Practice, T. Rappaport

Even though it is a relatively old book, it explains the principles of wireless communications in a very neat way. It also provides a great analysis of different communication channel models.

Fundamentals of Wireless Communication, D. Tse and P. Viswanath

This is my favorite textbook under this category. It takes a unified view of the fundamentals of wireless communication and explains the web of concepts underpinning these advances at an easy level such that you only need some basic knowledge of Digital Communications and Probability.
Digital Communications, J. Proakis and M. Salehi
An excellent textbook for graduate students. It provides thorough analysis and design of digital communication systems.

Signal Detection and Estimation

Fundamentals of Statistical Signal Processing (Volume I: Estimation Theory. Volume II: Detection Theory), S. Kay

It is one of my favorite textbooks in signal detection and estimation. It tackles both the detection and estimation problems in a very neat way.

Principles of Signal Detection and Parameter Estimation, B. Levy

A new book that covers the fundamentals of signal detection and parameter estimation.

An Introduction to Signal Detection and Estimation, V. Poor

Even though this book is old (1998), it stands out in the field if statistical processing. It provides the essential background for detection and estimation theories, and it is suitable for graduate students.

Optimization, Probability, and Stochastic Processes

Convex Optimization, S. Boyd and L. Vandenberghe

It is one of the most powerful books for convex optimization, a topic that has recently emerged in wireless communications applications. It is also available online, for free, here. Dr. Boyd also provides excellent lectures on Youtube here.

Probability and Random Processes, S. Miller and D. Childersook

This textbook is really good for fresh graduate students who want to improve their mathematical background on probability distributions and the essential tools to analyze random and stochastic processes.