Zesong Fei

A General Robust Linear Transceiver Design for Multi-Hop Amplify-and-Forward MIMO Relaying Systems

In this paper, linear transceiver design for multi-hop amplify-and-forward (AF) multi-input multi-output (MIMO) relaying systems with Gaussian distributed channel estimation errors is investigated. Commonly used transceiver design criteria including weighted mean-square-error (MSE) minimization, capacity maximization, worst-MSE/MAX-MSE minimization and weighted sum-rate maximization, are considered and unified into a single matrix-variate optimization problem. A general robust design algorithm is proposed to solve the unified problem. Specifically, by exploiting majorization theory and properties of matrix-variate functions, the optimal structure of the robust transceiver is derived when either the covariance matrix of channel estimation errors seen from the transmitter side or the corresponding covariance matrix seen from the receiver side is proportional to an identity matrix. Based on the optimal structure, the original transceiver design problems are reduced to much simpler problems with only scalar variables whose solutions are readily obtained by an iterative water-filling algorithm. A number of existing transceiver design algorithms are found to be special cases of the proposed solution. The differences between our work and the existing related work are also discussed in detail. The performance advantages of the proposed robust designs are demonstrated by simulation results.

MIMO Beamforming Designs With Partial CSI Under Energy Harvesting Constraints

In this letter, we investigate multiple-input multiple-output (MIMO) communications under energy harvesting (EH) constraints. In our considered EH system, there is one information transmitting (ITx) node, one traditional information receiving (IRx) node and multiple EH nodes. EH nodes can transform the received electromagnetic waves into energy to enlarge the network operation life. When the ITx node sends signals to the destination, it should also optimize the beamforming/precoder matrix to charge the EH nodes efficiently simultaneously. Additionally, the charged energy should be larger than a predefined threshold. Under the EH constraints, in our work both minimum mean-square-error (MMSE) and mutual information are taken as the performance metrics for the beamforming designs at the ITx node. In order to make the proposed algorithms suitable for practical implementation and have affordable overhead, our work focuses on the beamforming designs with partial CSI and this is the distinct contribution of our work. Finally, numerical results are given to show the performance advantages of the proposed algorithms.

A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems

Wireless sensor networks (WSNs) have attracted substantial research interest, especially in the context of performing monitoring and surveillance tasks. However, it is challenging to strike compelling tradeoffs amongst the various conflicting optimization criteria, such as the network’s energy dissipation, packet-loss rate, coverage, and lifetime. This paper provides a tutorial and survey of recent research and development efforts addressing this issue by using the technique of multi-objective optimization (MOO). First, we provide an overview of the main optimization objectives used in WSNs. Then, we elaborate on various prevalent approaches conceived for MOO, such as the family of mathematical programming-based scalarization methods, the family of heuristics/metaheuristics-based optimization algorithms, and a variety of other advanced optimization techniques. Furthermore, we summarize a range of recent studies of MOO in the context of WSNs, which are intended to provide useful guidelines for researchers to understand the referenced literature. Finally, we discuss a range of open problems to be tackled by future research.

How to understand linear minimum mean-square-error transceiver design for multiple-input–multiple-output systems from quadratic matrix programming

In this study, a unified linear minimum mean-square-error (LMMSE) transceiver design framework is investigated, which is suitable for a wide range of wireless systems. The unified design is based on an elegant and powerful mathematical programming technology termed as quadratic matrix programming (QMP). Based on QMP it can be observed that for different wireless systems, there are certain common characteristics which can be exploited to design LMMSE transceivers, for example, the quadratic forms. It is also discovered that evolving from a point-to-point multiple-input–multiple-output (MIMO) system to various advanced wireless systems such as multi-cell coordinated systems, multi-user MIMO systems, MIMO cognitive radio systems, amplify-and-forward MIMO relaying systems and so on, the quadratic nature is always kept and the LMMSE transceiver designs can always be carried out via iteratively solving a number of QMP problems. A comprehensive framework on how to solve QMP problems is also given. The work presented in this study is likely to be the first shot for the transceiver design for the future ever-changing wireless systems.

Heterogeneous network in LTE-advanced system

This paper provides a thorough analysis of the frequency resource allocation among multi-layers of the intra-RAT (Radio Access Technology) heterogeneous network. From the aspect of the spectrum utilization efficiency, the co-channel heterogeneous network provides higher system capacity, but its control channel coverage and quality is much worse than the orthogonal frequency allocation between macro cell and local cells. Enhancement of co-channel deployment are analyzed and evaluated such as range expansion and the Frequency Division Duplexing (FDM)/Time Division Duplexing (TDM) orthogonal control channel design. As a further step of evolution, an approach with dynamic spectrum sharing among macro cells and local cells are proposed to utilize the spared macro uplink resource in the downlink/uplink traffic asymmetric scenario for hotspot local DL access with well-designed interference management.

Performance Analysis and Location Optimization for Massive MIMO Systems With Circularly Distributed Antennas

We analyze the achievable rate of the uplink of a single-cell multi-user distributed massive multiple-input-multiple-output (MIMO) system. Each user is equipped with single antenna and the base station (BS) is equipped with a large number of distributed antennas. We derive an analytical expression for the asymptotic ergodic achievable rate of the system under zero-forcing (ZF) detector. In particular, we consider circular antenna array, where the distributed BS antennas are located evenly on a circle, and derive an analytical expression and closed-form bounds for the achievable rate of an arbitrarily located user. Subsequently, closed-form bounds on the average achievable rate per user are obtained under the assumption that the users are uniformly located. Based on the bounds, we can understand the behavior of the system rate with respect to different parameters and find the optimal location of the circular BS antenna array that maximizes the average rate. Numerical results are provided to assess our analytical results and examine the impact of the number and the location of the BS antennas, the transmit power, and the path-loss exponent on system performance. Simulations on multi-cell networks are also demonstrated. Our work shows that circularly distributed massive MIMO system largely outperforms centralized massive MIMO system.

A scheme of multi-user reusing one slot on enhancing capacity of GSM/EDGE networks

GSM network is seeing its greatest expansion because of the growing demand for mobile voice services in emerging markets recently. A newly proposed technology, multiuser reusing one slot (MUROS), would help operators in densely populated cities to alleviate the strain on their networks. The concept of MUROS is based on multiplexing two or more users onto one time slot without degrading the speech quality. We improved one solution of MUROS, orthogonal sub channel (OSC) in this contribution. For the downlink (DL) OSC, we designed new training sequence codes (TSCs) which are low cross-correlated with legacy TSCs. For the uplink (UL) OSC, we adopted successive interference cancellation based on minimum mean square error (MMSE-SIC) algorithm. Theoretical analysis and simulation results shows that with proper TSC design, OSC is a promising scheme of MUROS due to its ability to double the capacity of GSM/EDGE networks without degrading the speech quality very much.

The Role of Large-Scale Fading in Uplink Massive MIMO Systems

In this paper, we analyze the ergodic achievable rate of a large uplink multiuser multiple-input-multiple-output (MU-MIMO) system over generalized-

Robust Low-Complexity MMSE Precoding Algorithm for Cloud Radio Access Networks

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The Application of EESM and MI-Based Link Quality Models for Rate Compatible LDPC Codes

fading channels. In the considered scenario, multiple users transmit their information to a base station equipped with a very large number of antennas. Since the effect of fast fading asymptotically disappears in massive MIMO systems, large-scale fading becomes the most dominant factor for the ergodic achievable rate of massive MIMO systems. Regarding this fact, in our work, we concentrate our attention on the effects of large-scale fading for massive MIMO systems. Specifically, some interesting and novel asymptotic expressions of ergodic achievable rate have been derived with both perfect channel state information (CSI) and imperfect CSI. Simulation results assess the accuracy of these analytical expressions.