Yupeng Jia

Outage Probability and Power Allocation of Two-Way Amplify-and-Forward Relaying with Channel Estimation Errors

We consider a two-way amplify-and-forward (AF) relaying system consisting of two source nodes and a half-duplex relay. We assume that the source nodes are equipped with the linear minimum mean squared error (LMMSE) channel estimators. We investigate the effect of uncertainty due to channel estimation error on the system outage probability, considering the imposed bandwidth and energy costs of channel estimation. For a fixed transmission block length and a total transmit power constraint, we provide a compact-form expression for the system outage probability upper bound and we explore the optimal number of training symbols, the optimal power allocation between data and training, and the optimal power allotment between the two users and the relay, such that this bound is minimized. Our numerical results show that channel estimation error does not limit the performance in high signal-to-noise ratio (SNR). Also, the optimal power allocation between data and training and between the users and the relay provides a significant SNR improvement, compared with the suboptimal schemes, including fixed power allocation. The optimization gain increases as the relay moves away from the middle point.

How Does Channel Estimation Error Affect Average Sum-Rate in Two-Way Amplify-and-Forward Relay Networks?

This paper studies the impact of channel estimation error on the performance of a two-way amplify-and-forward (AF) relay network and investigates the optimal transmit resource allocation that minimizes the impact. In particular, we consider a three node network, consisting of two user terminals \mathbb{T}_A and \mathbb{T}_B and a half duplex relay node \mathbb{R}, where only \mathbb{T}_A and \mathbb{T}_B are equipped with channel estimators. Assuming block flat fading channel model, we adopt two estimation theoretic performance metrics, namely the Bayesian Cramer-Rao lower bound (CRLB) and the mean-squared error (MSE) of the linear minimum mean square error (LMMSE) channel estimate, and an information theoretic performance metric, namely the average sum-rate lower bound, as our optimality criteria. For a fixed transmission block length and under the total transmit power constraint, we investigate the optimal training vector design, the optimal number of training symbols in the training vector, the optimal power allocation between training and data in a transmission block, and the optimal power allotment between three nodes, such that these performance metrics are optimized, via utilizing bi-objective optimization methods. Our simulation results demonstrate that the optimal solutions corresponding to each performance metric vary, as the relay location and the system signal-to-noise ratio (SNR) change. They also reveal interesting symmetry relationship between these optimal solutions and the relay location.

Transmission Resource Allocation for Training Based Amplify-and-Forward Relay Systems

For a three node amplify-and-forward (AF) relay system in which only destination D is equipped with a channel estimator, we derive lower bound on training-based mutual information per transmission block. For a given transmission block length and a fixed total transmit power constraint between source S and relay R, we investigate jointly optimal number of training symbols, optimal power allocation between training and data, and optimal power allotment between S and R, such that the mutual information lower bound is maximized. For the AF relay system without direct link we provide analytical solutions to the joint optimization problem and relate the solutions to the relay location. For the AF relay system with direct link we resort to numerical evaluations to find the optimal solutions.

Maximizing throughput in cooperative networks via cross-layer adaptive designs

For a three node cooperative wireless network with an overall transmission power constraint, we present an adaptive cross-layer design framework for maximization of a single user throughput using the power allocation ratio among the source and relay nodes, the packet length, and the modulation level as optimization variables. The design framework integrates automatic repeat request (ARQ) at the MAC layer and cooperative diversity at the physical (PHY) layer. We consider amplify-and-forward (AF) and selective decode-and-forward (SDF) schemes in our study and investigate the impact of average channel qualities on throughput maximization. We show that at low SNR regime, the maximum throughput is achieved by adapting the power allocation between the source and the relay nodes, whereas at high SNR the maximum throughput is attained by adapting all three parameters. While the two cooperative schemes have the same diversity gain, we show that the SDF scheme provides a slightly higher throughput than AF.

Impact of channel estimation error upon sum-rate in amplify-and-forward two-way relaying systems

In this work, we consider the amplify-and-forward (AF) two-way relay network where the two terminals TA, TB exchange their information through a relay node TR in a bi-directional manner and study the impact of the training-based channel estimation upon individual and sum-rate of the two users. We assume that in the multiple-access (MA) phase TA, TB initiate transmission by sending their training symbols to TR, and in the broadcasting (BC) phase TR initiates transmission by sending its own training symbol, followed by an amplified version of the signal received in MA phase. This training symbol facilitates TA and TB to perform self-interference suppression and to estimate the cascaded overall relay channel required for recovery of the data of interest. We derive lower bounds on the training-based individual rates and sum-rate of the two users and investigate the impact of channel estimation errors upon the sum-rate lower bound. Under the total transmit power constraint, we search for the optimal power allocation among the three nodes and optimal power allocation between data and training such that the sum-rate lower bound is maximized. Furthermore, we discuss the relationship between the optimal solutions and the relay location.

Two-way relaying for energy constrained systems: Joint transmit power optimization

We consider an energy constrained two-way wireless relay system, where a bidirectional connection between two terminals TA and TB is established via one decode-and-forward (DF) relay ℝ. We study the optimal power allocation that minimizes the total transmit power consumption, under given requirements on the end-to-end bit error rate (BER) at TA and TB. By approximating the non-convex BER constraints, we formulate a convex optimization problem and provide closed form solutions for the optimal power assignment problem. Comparing the resulting overall transmit power consumption with that achieved through the individual link requirement strategy (where power is assigned under a per-link BER constraint), we show that the proposed power allocation scheme can achieve a maximum of 50% power reduction.

Multi-channel Phase-Coherent RF Measurement System Architectures and Performance Considerations

The paradigm for wireless communication is, shifting toward multiple-input multiple-output (MIMO) communications, enabled by multiple antennas at the transmitter and receiver. Instrument synchronization requirements for MIMO test are some of the most difficult in the test industry. In a MIMO test system, each channel of a multichannel RF instrument must achieve true channel-to-channel phase coherency. While MIMO test setups traditionally used multiple VSAs with a shared 10 MHz reference clock, new modular RF instruments allow for a single LO to be shared between each channel of a multi-channel VSA. For both architectures, key contributors to channel-to-channel phase uncertainty are uncorrelated phase noise and ADC quantization noise. As the results from these experiments demonstrate, uncorrelated phase noise dominates channel-to-channel phase offsets in multichannel VSAs which use independent LOs for each down converter. By contrast, ADC quantization noise dominates channel-to-channel phase uncertainty in multi-channel VSAs using a common synthesized LO for each channel. Moreover, the absolute channel-to-channel phase uncertainty is significantly better in the multi-channel VSA which uses a common LO for each down converter chain.

Training design for information rate maximization over amplify and forward relay channels

For a three node relay channel with amplify- and-forward (AF) transmission mode we study the effect of channel estimation error at the destination on the mutual information between the transmitted block by the source and the corresponding received block at the destination. Given that the destination forms the linear MMSE (LMMSE) estimate of the cascaded source-relay-destination channel, we derive a lower bound on the mutual information. Under the total transmit power constraint, we find the optimal power allocation between source and relay, as well as the optimal power allocation between training and data symbols at the source such that this lower bound is maximized. The two optimal power allocations are mutually related and depend on the channel and noise statistics.

A novel selective relaying protocol for wireless networks

For a three-node cooperative network model we propose a novel relaying strategy, referred to as selective Decode-and-Forward/Ampliy-and-Forward (selective DF/AF), and analyze its symbol error rate (SER) performance. In the proposed scheme, the relay always cooperate: when it is able to decode correctly the transmitted information symbols it forwards the decoded information to the destination, when it fails to correctly decode the information symbols, rather than staying idle, it amplifies and forwards the received signal from the source to the destination. The performance of selective DF/AF scheme is compared against that of selective DF/idle scheme, in which the relay is idle when it is unable to decode the source message reliably. The selective DF/idle scheme has been investigated in [1, 2], however, it remains unclear whether it is the optimal selective relaying protocol. Using high SNR approximation of SER as the performance metric, we show that both schemes harvest full diversity, when the destination employs maximum ratio combining (MRC) to combine signals received from the source and the relay, while the proposed scheme provides higher cooperative gain.

Improving Adjacent Channel Power measurements of wireless standards

Adjacent Channel Power (ACP) is a key spectral measurement, particularly for power amplifiers in modern wireless communication systems. This paper presents a definition of ACP and the current methodology for measuring it. We will propose an alternative way to use modular RF instruments to optimize the measurement performance of ACP, while keeping the measurement time low.