Optimal Training Design for Channel Estimation in Decode-and-Forward Relay Networks With Individual and Total Power Constraints

In this paper, we study the channel estimation and the optimal training design for relay networks that operate under the decode-and-forward (DF) strategy with the knowledge of the interference covariance. In addition to the total power constraint on all the relays, we introduce individual power constraint for each relay, which reflects the practical scenario where all relays are separated from one another. Considering the individual power constraint for the relay networks is the major difference from that in the traditional point-to-point communication systems where only a total power constraint exists for all colocated antennas. Two types of channel estimation are involved: maximum likelihood (ML) and minimum mean square error (MMSE). For ML channel estimation, the channels are assumed as deterministic and the optimal training results from an efficient multilevel waterfilling type solution that is derived from the majorization theory. For MMSE channel estimation, however, the second-order statistics of the channels are assumed known and the general optimization problem turns out to be nonconvex. We instead consider three special yet reasonable scenarios. The problem in the first scenario is convex and could be efficiently solved by state-of-the-art optimization tools. Closed-form waterfilling type solutions are found in the remaining two scenarios, of which the first one has an interesting physical interpretation as pouring water into caves

Synchronization in Cooperative Communication Systems

Cooperative communication is an attractive solution to combat fading in wireless communication systems. Achieving synchronization is a fundamental requirement in such systems. In cooperative networks, multiple single antenna relay terminals receive and cooperatively transmit the source information to the destination. The multiple distributed nodes, each with its own local oscillator, give rise to multiple timing offsets (MTOs) and multiple carrier frequency offsets (MCFOs). Particularly, the received signal at the destination is the superposition of the relays' transmitted signals that are attenuated differently, are no longer aligned with each other in time, and experience phase rotations at different rates due to different channels, MTOs, and MCFOs, respectively. The loss of synchronization due to the presence of MTOs and MCFOs sets up the recovery of the source signal at the destination to be a very challenging task. This thesis seeks to develop estimation and compensation algorithms that can achieve synchronization and enable cooperative communication for both decode-and-forward (DF) and amplify-and-forward (AF) relaying networks in the presence of multiple impairments, i.e., unknown channel gains, MTOs, and MCFOs. In the first part of the thesis, a training-based transmission scheme is considered, in which training symbols are transmitted first in order to assist the joint estimation of multiple impairments at the destination node in DF and AF cooperative relaying networks. New transceiver structure at the relays and novel receiver design at the destination are proposed which allow for the decoding of the received signal in the presence of unknown channel gains, MTOs, and MCFOs. Different estimation algorithms, e.g., least squares (LS), expectation conditional maximization (ECM), space-alternating generalized expectation-maximization (SAGE), and differential evolution (DE), are proposed and analyzed for joint estimation of multiple impairments. In order to compare the estimation accuracy of the proposed estimators, Cramer-Rao lower bounds (CRLBs) for the multi-parameter estimation are derived. Next, in order to detect the signal from multiple relays in the presence of multiple impairments, novel optimal and sub-optimal minimum mean-square error (MMSE) compensation and maximum likelihood (ML) decoding algorithm are proposed for the destination receiver. It has been evidenced by numerical simulations that application of the proposed estimation and compensation methods in conjunction with space-time block codes achieve full diversity gain in the presence of channel and synchronization impairments. Considering training-based transmission scheme, this thesis also addresses the design of optimal training sequences for efficient and joint estimation of MTOs and multiple channel parameters. In the second part of the thesis, the problem of joint estimation and compensation of multiple impairments in non-data-aided (NDA) DF cooperative systems is addressed. The use of blind source separation is proposed at the destination to convert the difficult problem of jointly estimating the multiple synchronization parameters in the relaying phase into more tractable sub-problems of estimating many individual timing offsets and carrier frequency offsets for the independent relays. Next, a criteria for best relay selection is proposed at the destination. Applying the relay selection algorithm, simulation results demonstrate promising bit-error rate (BER) performance and realise the achievable maximum diversity order at the destination

On channel estimation and optimal training design for amplify and forward relay networks

10.1109/GLOCOM.2007.763GLOBECOM - IEEE Global Telecommunications Conference4015-401

Distributed space-time coding for two-way wireless relay networks

In this paper, we consider distributed space-time coding for two-way wireless relay networks, where communication between two terminals is assisted by relay nodes. Relaying protocols using two, three, and four time slots are proposed. The protocols using four time slots are the traditional amplify-and-forward (AF) and decode-and-forward (DF) protocols, which do not consider the property of the two-way traffic. A new class of relaying protocols, termed as partial decode-and-forward (PDF), is developed for the two time slots transmission, where each relay first removes part of the noise before sending the signal to the two terminals. Protocols using three time slots are proposed to compensate the fact that the two time slots protocols cannot make use of direct transmission between the two terminals. For all protocols, after processing their received signals, the relays encode the resulting signals using a distributed linear dispersion (LD) code. The proposed AF protocols are shown to achieve the diversity order of min{N,K}(1- (log log P/log P)), where N is the number of relays, P is the total power of the network, and K is the number of symbols transmitted during each time slot. When random unitary matrix is used for LD code, the proposed PDF protocols resemble random linear network coding, where the former operates on the unitary group and the latter works on the finite field. Moreover, PDF achieves the diversity order of min{N,K} but the conventional DF can only achieve the diversity order of 1. Finally, we find that two time slots protocols also have advantages over four-time-slot protocols in media access control (MAC) layer