Sumei Sun

Full-Duplex Wireless-Powered Communication Network With Energy Causality

In this paper, we consider a wireless communication network with a full-duplex hybrid energy and information access point and a set of wireless users with energy harvesting capabilities. The hybrid access point (HAP) implements full-duplex through two antennas: one for broadcasting wireless energy to users in the downlink and the other for simultaneously receiving information from the users via time division multiple access (TDMA) in the uplink. Each user can continuously harvest wireless power from the HAP until it transmits, i.e., the energy causality constraint is modeled by assuming that energy harvested in the future cannot be used for the current transmission. This leads to the causal dependence of each users harvesting time on the transmission time of earlier users, e.g., the second user scheduled to transmit can harvest more energy if the first user has longer transmission time. Under this setup, we investigate the sum-throughput maximization (STM) problem and the total-time minimization (TTM) problem for the proposed full-duplex wireless-powered communication network. For the STM problem, the optimal solution is obtained as a closed-form expression, which can be computed with linear complexity. For the TTM problem, by exploiting the properties of the coupled constraints, we propose a two-step algorithm to obtain an optimal solution. Then, low-complexity suboptimal solutions are proposed for each problem by exploiting the characteristics of the optimal solutions. Finally, simulation studies on the effect of user scheduling show that different scheduling strategies should be adopted for STM and TTM.

Energy-Efficient, Large-Scale Distributed-Antenna System (L-DAS) for Multiple Users

Large-scale distributed-antenna system (L-DAS) with very large number of distributed antennas, possibly up to a few hundred antennas, is considered. A few major issues of the L-DAS, such as high latency, energy consumption, computational complexity, and large feedback (signaling) overhead, are identified. The potential capability of the L-DAS is illuminated in terms of an energy efficiency (EE) throughout the paper. We firstly and generally model the power consumption of an L-DAS, and formulate an EE maximization problem. To tackle two crucial issues, namely the huge computational complexity and large amount of feedback (signaling) information, we propose a channel-gain-based antenna selection (AS) method and an interference-based user clustering (UC) method. The original problem is then split into multiple subproblems by a cluster, and each clusters precoding and power control are managed in parallel for high EE. Simulation results reveal that i) using all antennas for zero-forcing multiuser multiple-input multiple-output (MU-MIMO) is energy inefficient if there is nonnegligible overhead power consumption on MU-MIMO processing, and ii) increasing the number of antennas does not necessarily result in a high EE. Furthermore, the results validate and underpin the EE merit of the proposed L-DAS complied with the AS, UC, precoding, and power control by comparing with non-clustering L-DAS and colocated antenna systems.

Block-iterative generalized decision feedback equalizers for large MIMO systems: algorithm design and asymptotic performance analysis

This paper studies the problem of signal detection for multiple-input multiple-output (MIMO) channels with large signal dimensions. We propose a block-iterative generalized decision feedback equalization (BI-GDFE) receiver to recover the transmitted symbols in a block-iterative manner. By exploiting the input-decision correlation, a measure for the reliability of the earlier-made decisions, we design the feed-forward equalizers (FFEs) and feedback equalizers (FBEs) in such a way that maximized signal-to-interference-plus-noise ratio (SINR) is achieved for each of the iterations. Novel implementations are also introduced to simplify the complexity of the receiver, which requires only one-tap filters for FFE and FBE. The proposed receiver also works when the signal dimension is greater than the observation dimension. The asymptotic performance of the proposed receiver is analyzed and its convergence has been confirmed through numerical evaluations for various parameters. Computer simulations are presented to illustrate the capability of the proposed receiver to achieve single user matched-filter bound (MFB) for large random MIMO channels when the received SNR is high enough.

A Comparative Study of QRD-M Detection and Sphere Decoding for MIMO-OFDM Systems

We present a comparative study of two tree search based detection algorithms, namely, the M-algorithm combined with QR decomposition (QRD-M) and the sphere decoding (SD) algorithms, for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. First, we show that nodes ordering before and during the tree search are important for both algorithms. With appropriate ordering, QRD-M can improve detection performance significantly and SD can reduce decoding complexity substantially. Then we compare the implementation complexity of the two algorithms, in terms of the number of nodes required to search or the required number of multiplications to achieve maximum likelihood detection performance. It is interesting to show that the average complexity of SD is lower than that of QRD-M, whereas the worst case complexity of SD is much higher than that of QRD-M

Decentralized Precoding for Multicell MIMO Downlink

Interference is a performance limiting factor in dense cellular networks with aggressive frequency reuse. Cooperation among base stations (BSs) is a promising approach for improving data rates by eliminating or mitigating interference. For the downlink, the highest spectral efficiency gains are achieved through precoding with full coordination, which requires complete channel state information (CSI) and data be shared among BSs at the cost of significant utilization of the backhaul. In this paper, we propose distributed precoding techniques for the multicell MIMO downlink. Unlike prior work, our proposed precoders are both decentralized with respect to the BSs as well as capable of enabling multiple users to share the same frequency carrier spatially within each cell. Specifically, each BS designs its own precoder without requiring data or downlink CSI of links from other BSs. Since CSI is unlikely to be perfect, we study the effect of imperfect CSI on our proposed precoders and propose a robust precoder in the presence of CSI uncertainty. Simulations show that our proposed methods enjoy a rate increase with SNR similar to multicell joint dirty paper coding in the high SNR regime due to effective interference mitigation. Numerical results reflect the sensitivity of each proposed precoder with respect to the imperfectness in the available CSI.

Spectral Efficiency and Energy Efficiency of OFDM Systems: Impact of Power Amplifiers and Countermeasures

In wireless communication systems, the nonlinear effect and inefficiency of power amplifier (PA) have posed practical challenges for system designs to achieve high spectral efficiency (SE) and energy efficiency (EE). In this paper, we analyze the impact of PA on the SE-EE tradeoff of orthogonal frequency division multiplex (OFDM) systems. An ideal PA that is always linear and incurs no additional power consumption can be shown to yield a decreasing convex function in the SE-EE tradeoff. In contrast, we show that a practical PA has an SE-EE tradeoff that has a turning point and decreases sharply after its maximum EE point. In other words, the Pareto-optimal tradeoff boundary of the SE-EE curve is very narrow. A wide range of SE-EE tradeoff, however, is desired for future wireless communications that have dynamic demand depending on the traffic loads, channel conditions, and system applications, e.g., high-SE-with-low-EE for rate-limited systems and high-EE-with-low-SE for energy-limited systems. For the SE-EE tradeoff improvement, we propose a PA switching (PAS) technique. In a PAS transmitter, one or more PAs are switched on intermittently to maximize the EE and deliver an overall required SE. As a consequence, a high EE over a wide range SE can be achieved, which is verified by numerical evaluations: with 15% SE reduction for low SE demand, the PAS between a low power PA and a high power PA can improve EE by 323%, while a single high power PA transmitter improves EE by only 68%.

Mobile Data Offloading Through A Third-Party WiFi Access Point: An Operator's Perspective

WiFi offloading is regarded as one of the most promising techniques to deal with the explosive data increase in the existing cellular network due to its high data transmission rate, and low requirement on devices. In this paper, we investigate the mobile data offloading problem through a third-party WiFi access point (AP) for a cellular mobile system. From the cellular operators perspective, by assuming the data offloaded through the third-party WiFi AP is charged based on usage, we formulate mobile data offloading problem as a utility maximization problem, which is an integer programming problem. A centralized mobile data offloading scheme is then obtained by considering its relaxation problem. It is strictly proved that the proposed centralized data offloading scheme is near-optimal when the number of users is large. Then, to relieve the computing burden on the cellular base station, we propose a threshold-based distributed data offloading scheme. We show that the proposed distributed scheme performs very well once the threshold is properly chosen.

Link adaptation based on adaptive modulation and coding for multiple-antenna OFDM system

In this paper, we study the problem of link adaptation based on adaptive modulation and coding for multiple antenna OFDM system in slow fading channel. Based on the extrinsic information transfer analysis, we give an accurate packet error rate prediction with channel estimation errors. This method uses Gaussian approximation to characterize the output of the detector and decoder. We also discuss approaches for searching and selecting the best modulation and coding scheme for the link adaptation algorithm. Finally, the performance of the proposed link adaptation algorithm is studied for the IEEE 802.11n multiple-antenna OFDM system. Good system throughput are achieved using the proposed method, compared to the SNR based algorithm.

Power and Load Coupling in Cellular Networks for Energy Optimization

We consider the problem of minimization of sum transmission energy in cellular networks where coupling occurs between cells due to mutual interference. The coupling relation is characterized by the signal-to-interference-and-noise-ratio (SINR) coupling model. Both cell load and transmission power, where cell load measures the average level of resource usage in the cell, interact via the coupling model. The coupling is implicitly characterized with load and power as the variables of interest using two equivalent equations, namely, non-linear load coupling equation (NLCE) and non-linear power coupling equation (NPCE), respectively. By analyzing the NLCE and NPCE, we prove that operating at full load is optimal in minimizing sum energy, and provide an iterative power adjustment algorithm to obtain the corresponding optimal power solution with guaranteed convergence, where in each iteration a standard bisection search is employed. To obtain the algorithmic result, we use the properties of the so-called standard interference function; the proof is non-standard because the NPCE cannot even be expressed as a closed-form expression with power as the implicit variable of interest. We present numerical results illustrating the theoretical findings for a real-life and large-scale cellular network, showing the advantage of our solution compared to the conventional solution of deploying uniform power for base stations.

Robust MMSE channel estimation in OFDM systems with practical timing synchronization

Robust minimum mean-square error (MMSE) channel estimation for orthogonal frequency-division multiplexing (OFDM) systems with practical timing synchronization is considered. The correlation between the channel coefficients at the different subcarriers depends upon the channel power delay profile (PDP) and the probability density function (pdf) of the timing synchronization offset. Since both of these are not known at design time, there is a need for a robust estimator that results in mean-square error performance independent of the actual channel power delay profile (PDP) and the actual timing synchronization offset pdf. We develop the notion of effective PDP, given by the convolution of the channel PDP and the pdf of the timing synchronization offset. We show that designing with a uniform PDP of the same length as the effective PDP leads to a robust solution. This follows from the robustness of the uniform PDP for MMSK estimation, a known result for which we provide an alternative derivation. We illustrate the performance of the robust estimator using a numerical example.