Date of Award

Spring 1-1-2015

Document Type


Degree Name

Doctor of Philosophy (PhD)


Electrical, Computer & Energy Engineering

First Advisor

Youjian Liu

Second Advisor

Lijun Chen

Third Advisor

Mahesh K. Varanasi

Fourth Advisor

Behrouz Touri

Fifth Advisor

Peter Mathys


This thesis studies optimization and performance of the MIMO B-MAC interference networks which includes broadcast channel (BC), multiaccess channel (MAC), interference channels, X networks, and many practical wireless networks as special cases. A 3D channel model for distributed MIMO system is set up, based on which the antenna correlations can be characterized in analytic form. We propose a new algorithm, named Dual Link algorithm, for the classic problem of weighted sum-rate maximization for MIMO multiaccess channels (MAC), broadcast channels (BC), and general MIMO interference channels with Gaussian input and a total power constraint. For MIMO MAC/BC, the algorithm finds optimal signals to achieve the capacity region boundary. For interference channels with Gaussian input assumption, two of the previous state-of-the-art algorithms are the WMMSE algorithm and the polite water-filling (PWF) algorithm. The WMMSE algorithm is provably convergent, while the PWF algorithm takes the advantage of the optimal transmit signal structure and converges the fastest in most situations but is not guaranteed to converge in all situations. It is highly desirable to design an algorithm that has the advantages of both algorithms. The proposed dual link algorithm is such an algorithm. Its fast and guaranteed convergence is important to distributed implementation and time varying channels. In addition, the technique and a scaling invariance property used in the convergence proof may find applications in other non-convex problems in communication networks. The dual link algorithm is also further modified to fit practical applications. Since the centralized algorithm is not scalable as network size increases, the optimization algorithm needs to be working in a mainly distributed fashion to avoid having huge signaling overheads. We've proposed the distributed dual link algorithm for time division duplex (TDD) interference networks. It replaces direct and cross channel information feedbacks with iterations of forward and reverse link pilots training whose complexity grows linearly with the number of users in the network. By totally avoiding channel state knowledge feedback, the distributed dual link algorithm has significant lower signaling overhead compared to the traditional methods, especially in networks with large number of interfering users. However, the real TDD channels are not reciprocal because the transmit and receive RF chains are different in a transceiver. To solve this issue, we proposed a simple method of channel calibration to restore TDD channel reciprocity for MIMO interference networks that is essential to the distributed implementation of the Dual Link algorithm and other algorithms that require reciprocity. On the other hand, the channel knowledge is generally imperfect in a realistic scenario. To study its impact, we introduce a simple channel uncertainty model that characterizes different levels of channel uncertainty. Based on this model, the ergodic weighted sum-rate maximization problem is studied. The ergodic dual link algorithm is proposed to analytically solve the optimization problem. We also propose the robust dual link algorithm which is sub-optimal but has good performance under all channel uncertainty levels and is suitable for online distributed implementation. Finally, we study the physical layer transmission and reception schemes in a cellular system where the basestations are equipped with infinitely many antennas. It is shown that the uplink Signal to Interference Ratio (SIR) and the downlink SIR corresponding to a given basestation (BS) - mobile station (MS) pair are identical.