arXiv subjects

Zesong Fei

Publications and source records attributed to Zesong Fei.

At least 73 records · Page 4Linked to original sources

arXiv2017

Resource Allocations for Secure Cognitive Satellite Terrestrial Networks

Cognitive satellite-terrestrial networks (STNs) have been recognized as the promising architecture for addressing spectrum scarcity in the next generation communication networks. In this letter, we investigate the secure transmission schemes in the cognitive STNs where the interference from terrestrial base station (BS) is introduced to enhance security of the satellite link. Our objectives are to minimize the transmit power by jointly optimizing the cooperative beamforming and artificial noise (AN) while guaranteeing the secrecy rate constraint for satellite link, the information rate constraint for terrestrial link and the total transmit power constraint. Both scenarios of the perfect and imperfect channel cases are respectively considered. These constraints make the optimization problems formulated non-convex and challenging, which are efficiently solved via certain transformations to be formulated more tractable versions, respectively. Numerical results are provided to corroborate the proposed schemes.

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arXiv2016

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 trade-offs 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.

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arXiv2015

Transceiver designs with matrix-version water-filling architecture under mixed power constraints

In this paper, we investigate the multiple-input multiple-output (MIMO) transceiver design under an interesting power model named mixed power constraints. In the considered power model, several antenna subsets are constrained by sum power constraints while the other antennas are subject to per-antenna power constraints. This kind of transceiver designs includes both the transceiver designs under sum power constraint and per-antenna power constraint as its special cases. This kind of designs is of critical importance for distributed antenna systems (DASs) with heterogeneous remote radio heads (RRHs) such as cloud radio access networks (C-RANs). In our work, we try to solve the optimization problem in an analytical way instead of using some famous software packages e.g., CVX or SeDuMi. In our work, to strike tradeoffs between performance and complexity, both iterative and non-iterative solutions are proposed. Interestingly the non-iterative solution can be interpreted as a matrix version water-filling solution extended from the well-known and extensively studied vector version. Finally, simulation results demonstrate the accuracy of our theoretical results.

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arXiv2014

A Framework of Performance Analysis for Distributed Antenna Systems Based on Random Matrix Theory

Future communications systems will definitely be built on green infrastructures. To realize such a goal, recently a new network infrastructure named cloud radio access network (C-RAN) is proposed by China Mobile to enhance network coverage and save energy simultaneously. In C-RANs, to order to save more energy the radio front ends are separated from the colocated baseband units and distributively located in physical positions. C-RAN can be recognized as a variant of distributed antenna systems (DASs). In this paper we analyze the performance of C-RANS using random matrix theory. Due to the fact that the antennas are distributed geographically instead of being installed nearby, the variances of the entries in the considered channel matrix are different from each other. To the best of the authors' knowledge, the work on random matrices with elements having different variances is largely open, which is of great importance for DASs. In our work, some fundamental results on the eigenvalue distributions of the random matrices with different variances are derived first. Then based on these fundamental conclusions the outage probability of the considered DAS is derived. Finally, the accuracy of our analytical results is assessed by some numerical results.

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arXiv2014

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

In this paper, we analyze the achievable rate of the uplink of a single-cell multi-user distributed massive multiple-input-multiple-output (MIMO) system. The multiple users are 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 tight 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 in the cell. 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. It is shown that circularly distributed massive MIMO system largely outperforms centralized massive MIMO system.

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arXiv2014

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

In this correspondence, we analyze the ergodic capacity of a large uplink multi-user multiple-input multiple-output (MU-MIMO) system over generalized-$K$ 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 capacity 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 lower bounds of the ergodic capacity have been derived with both perfect channel state information (CSI) and imperfect CSI. Simulation results assess the accuracy of these analytical expressions.

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arXiv2014

Adaptive Multi-objective Optimization for Energy Efficient Interference Coordination in Multi-Cell Networks

In this paper, we investigate the distributed power allocation for multi-cell OFDMA networks taking both energy efficiency and inter-cell interference (ICI) mitigation into account. A performance metric termed as throughput contribution is exploited to measure how ICI is effectively coordinated. To achieve a distributed power allocation scheme for each base station (BS), the throughput contribution of each BS to the network is first given based on a pricing mechanism. Different from existing works, a biobjective problem is formulated based on multi-objective optimization theory, which aims at maximizing the throughput contribution of the BS to the network and minimizing its total power consumption at the same time. Using the method of Pascoletti and Serafini scalarization, the relationship between the varying parameters and minimal solutions is revealed. Furthermore, to exploit the relationship an algorithm is proposed based on which all the solutions on the boundary of the efficient set can be achieved by adaptively adjusting the involved parameters. With the obtained solution set, the decision maker has more choices on power allocation schemes in terms of both energy consumption and throughput. Finally, the performance of the algorithm is assessed by the simulation results.

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arXiv2013

Low Complexity List Successive Cancellation Decoding of Polar Codes

We propose a low complexity list successive cancellation (LCLSC) decoding algorithm to reduce complexity of traditional list successive cancellation (LSC) decoding of polar codes while trying to maintain the LSC decoding performance at the same time. By defining two thresholds, namely "likelihood ratio (LR) threshold" and "Bhattacharyya parameter threshold", we classify the reliability of each received information bit and the quality of each bit channel. Based on this classification, we implement successive cancellation (SC) decoding instead of LSC decoding when the information bits from "bad" subchannels are received reliably and further attempt to skip LSC decoding for the rest information bits in order to achieve a lower complexity compared to full LSC decoding. Simulation results show that the complexity of LCLSC decoding is much lower than LSC decoding and can be close to that of SC decoding, especially in low code rate regions.

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arXiv2013

Improved LT Codes in Low Overhead Regions for Binary Erasure Channels

We study improved degree distribution for Luby Transform (LT) codes which exhibits improved bit error rate performance particularly in low overhead regions. We construct the degree distribution by modifying Robust Soliton distribution. The performance of our proposed LT codes is evaluated and compared to the conventional LT codes via And-Or tree analysis. Then we propose a transmission scheme based on the proposed degree distribution to improve its frame error rate in full recovery regions. Furthermore, the improved degree distribution is applied to distributed multi-source relay networks and unequal error protection. It is shown that our schemes achieve better performance and reduced complexity especially in low overhead regions, compared with conventional schemes.

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arXiv2013

Design of Binary Network Codes for Multi-user Multi-way Relay Networks

We study multi-user multi-way relay networks where $N$ user nodes exchange their information through a single relay node. We use network coding in the relay to increase the throughput. Due to the limitation of complexity, we only consider the binary multi-user network coding (BMNC) in the relay. We study BMNC matrix (in GF(2)) and propose several design criteria on the BMNC matrix to improve the symbol error probability (SEP) performance. Closed-form expressions of the SEP of the system are provided. Moreover, an upper bound of the SEP is also proposed to provide further insights on system performance. Then BMNC matrices are designed to minimize the error probabilities.

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arXiv2013

How to Understand LMMSE Transceiver Design for MIMO Systems From Quadratic Matrix Programming

In this paper, 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 e.g., the quadratic forms. It is also discovered that evolving from a point-to-point 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 paper is likely to be the first shoot for the transceiver design for the future ever-changing wireless systems.

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arXiv2013

A Matrix-Field Weighted Mean-Square-Error Model for MIMO Transceiver Designs

In this letter, we investigate an important and famous issue, namely weighted mean-square-error (MSE) minimization transceiver designs. In our work, for transceiver designs a novel weighted MSE model is proposed, which is defined as a linear matrix function with respect to the traditional data detection MSE matrix. The new model can be interpreted an extension of weighting operation from vector field to matrix field. Based on the proposed weighting operation a general transceiver design is proposed, which aims at minimizing an increasing matrix-monotone function of the output of the previous linear matrix function. The structure of the optimal solutions is also derived. Furthermore, two important special cases of the matrix-monotone functions are discussed in detail. It is also revealed that these two problems are exactly equivalent to the transceiver designs of sum MSE minimization and capacity maximization for dual-hop amplify-and-forward (AF) MIMO relaying systems, respectively. Finally, it is concluded that the AF relaying is undoubtedly this kind of weighting operation.

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arXiv2013

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) multiple-input multiple-out (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 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.

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arXiv2013

A Unified Linear MSE Minimization MIMO Beamforming Design Based on Quadratic Matrix Programming

In this paper, we investigate a unified linear transceiver design with mean-square-error (MSE) as the objective function for a wide range of wireless systems. The unified design is based on an elegant mathematical programming technology namely quadratic matrix programming (QMP). It is revealed that for different wireless systems such as multi-cell coordination systems, multi-user MIMO systems, MIMO cognitive radio systems, amplify-and-forward MIMO relaying systems, the MSE minimization beamforming design problems can always be solved by solving a number of QMP problems. A comprehensive framework on how to solve QMP problems is also given.

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arXiv2012

Distributed Resource Allocation Algorithm Design for Multi-Cell Networks Based on Advanced Decomposition Theory

In this letter, we investigate the resource allocation for downlink multi-cell coordinated OFDMA wireless networks, in which power allocation and subcarrier scheduling are jointly optimized. Aiming at maximizing the weighted sum of the minimal user rates (WSMR) of coordinated cells under individual power constraints at each base station, an effective distributed resource allocation algorithm using a modified decomposition method is proposed, which is suitable by practical implementation due to its low complexity and fast convergence speed. Simulation results demonstrate that the proposed decentralized algorithm provides substantial throughput gains with lower computational cost compared to existing schemes.

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arXiv2012

Symbol Error Rate of Space-Time Network Coding in Nakagami-m Fading

In this paper, we analyze the symbol error rate (SER) of space-time network coding (STNC) in a distributed cooperative network over independent but not necessarily identically distributed (i.n.i.d.) Nakagami-$m$ fading channels. In this network, multiple sources communicate with a single destination with the assistance of multiple decode-and-forward (DF) relays. We first derive new exact closed-form expressions for the SER with $M$-ary phase shift-keying modulation ($M$-PSK) and $M$-ary quadrature amplitude modulation ($M$-QAM). We then derive new compact expressions for the asymptotic SER to offer valuable insights into the network behavior in the high signal-to-noise ratio (SNR) regime. Importantly, we demonstrate that STNC guarantees full diversity order, which is determined by the Nakagami-$m$ fading parameters of all the channels but independent of the number of sources. Based on the new expressions, we examine the impact of the number of relays, relay location, Nakagami-$m$ fading parameters, power allocation, and nonorthogonal codes on the SER.

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arXiv2012

Performance Analysis for Heterogeneous Cellular Systems with Range Expansion

Recently heterogeneous base station structure has been adopted in cellular systems to enhance system throughput and coverage. In this paper, the uplink coverage probability for the heterogeneous cellular systems is analyzed and derived in closed-form. The randomness on the locations and number of mobile users is taken into account in the analysis. Based on the analytical results, the impacts of various system parameters on the uplink performance are investigated in detail. The correctness of the analytical results is also verified by simulation results. These analytical results can thus serve as a guidance for system design without the need of time consuming simulations.

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arXiv2012

Joint Robust Weighted LMMSE Transceiver Design for Dual-Hop AF Multiple-Antenna Relay Systems

In this paper, joint transceiver design for dual-hop amplify-and-forward (AF) MIMO relay systems with Gaussian distributed channel estimation errors in both two hops is investigated. Due to the fact that various linear transceiver designs can be transformed to a weighted linear minimum mean-square-error (LMMSE) transceiver design with specific weighting matrices, weighted mean square error (MSE) is chosen as the performance metric. Precoder matrix at source, forwarding matrix at relay and equalizer matrix at destination are jointly designed with channel estimation errors taken care of by Bayesian philosophy. Several existing algorithms are found to be special cases of the proposed solution. The performance advantage of the proposed robust design is demonstrated by the simulation results.

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