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Showing papers on "Channel state information published in 2009"


Posted Content
TL;DR: In this paper, a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission is considered, where the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner.
Abstract: This paper considers a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission. For precoding at the base stations, channel state information (CSI) is essential at the base stations. A popular technique for obtaining this CSI in time division duplex (TDD) systems is uplink training by utilizing the reciprocity of the wireless medium. This paper mathematically characterizes the impact that uplink training has on the performance of such multi-cell multiple antenna systems. When non-orthogonal training sequences are used for uplink training, the paper shows that the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner. This paper analyzes this fundamental problem of pilot contamination in multi-cell systems. Furthermore, it develops a new multi-cell MMSE-based precoding method that mitigate this problem. In addition to being a linear precoding method, this precoding method has a simple closed-form expression that results from an intuitive optimization problem formulation. Numerical results show significant performance gains compared to certain popular single-cell precoding methods.

1,040 citations


Journal ArticleDOI
TL;DR: This paper proposes a distributed game-theoretical framework over multiuser cooperative communication networks to achieve optimal relay selection and power allocation without knowledge of CSI.
Abstract: The performance in cooperative communication depends on careful resource allocation such as relay selection and power control, but the traditional centralized resource allocation requires precise measurements of channel state information (CSI). In this paper, we propose a distributed game-theoretical framework over multiuser cooperative communication networks to achieve optimal relay selection and power allocation without knowledge of CSI. A two-level Stackelberg game is employed to jointly consider the benefits of the source node and the relay nodes in which the source node is modeled as a buyer and the relay nodes are modeled as sellers, respectively. The proposed approach not only helps the source find the relays at relatively better locations and "buyrdquo an optimal amount of power from the relays, but also helps the competing relays maximize their own utilities by asking the optimal prices. The game is proved to converge to a unique optimal equilibrium. Moreover, the proposed resource allocation scheme with the distributed game can achieve comparable performance to that employing centralized schemes.

419 citations


Journal ArticleDOI
TL;DR: This paper studies the robust beamforming design for a multi-antenna cognitive radio (CR) network, which transmits to multiple secondary users (SUs) and coexists with a primary network of multiple users, and proposes iterative algorithms for obtaining the robust optimal beamforming solution.
Abstract: This paper studies the robust beamforming design for a multi-antenna cognitive radio (CR) network, which transmits to multiple secondary users (SUs) and coexists with a primary network of multiple users. We aim to maximize the minimum of the received signal-to-interference-plus-noise ratios (SINRs) of the SUs, subject to the constraints of the total SU transmit power and the received interference power at the primary users (PUs) by optimizing the beamforming vectors at the SU transmitter based on imperfect channel state information (CSI). To model the uncertainty in CSI, we consider a bounded region for both cases of channel matrices and channel covariance matrices. As such, the optimization is done while satisfying the interference constraints for all possible CSI error realizations. We shall first derive equivalent conditions for the interference constraints and then convert the problems into the form of semi-definite programming (SDP) with the aid of rank relaxation, which leads to iterative algorithms for obtaining the robust optimal beamforming solution. Results demonstrate the achieved robustness and the performance gain over conventional approaches and that the proposed algorithms can obtain the exact robust optimal solution with high probability.

298 citations


Journal ArticleDOI
TL;DR: It is demonstrated that the diversity order of the system is reduced to 1 when CSI is outdated, being this behavior independent of the level of CSI accuracy.
Abstract: In this paper, we analyze the outage probability and diversity order of opportunistic relay selection in a scenario based on decode and forward and where the available channel state information (CSI) is outdated. The study is conducted analytically by obtaining a closed-form expression for the outage probability, which is defined as the probability that the instantaneous capacity is below a target value. We derive high-SNR approximations for the outage probability. By doing so, we demonstrate that the diversity order of the system is reduced to 1 when CSI is outdated, being this behavior independent of the level of CSI accuracy. A physical explanation for this extreme loss of diversity is provided along with numerical results to support the analytical study.

260 citations


Journal ArticleDOI
TL;DR: This paper considers robust transmit strategies, against the imperfectness of the channel state information at the transmitter (CSIT), for multi-input multi-output (MIMO) communication systems, and finds that the optimal transmit directions are just the right singular vectors of the nominal channel under some mild conditions.
Abstract: In this paper, we consider robust transmit strategies, against the imperfectness of the channel state information at the transmitter (CSIT), for multi-input multi-output (MIMO) communication systems. Following a worst-case deterministic model, the actual channel is assumed to be inside an ellipsoid centered at a nominal channel. The objective is to maximize the worst-case received signal-to-noise ratio (SNR), or to minimize the worst-case Chernoff bound of the error probability, thus leading to a maximin problem. Moreover, we also consider the QoS problem, as a complement of the maximin design, which minimizes the transmit power consumption and meanwhile keeps the received SNR above a given threshold for any channel realization in the ellipsoid. It is shown that, for a general class of power constraints, both the maximin and QoS problems can be equivalently transformed into convex problems, or even further into semidefinite programs (SDPs), thus efficiently solvable by the numerical methods. The most interesting result is that the optimal transmit directions, i.e., the eigenvectors of the transmit covariance, are just the right singular vectors of the nominal channel under some mild conditions. This result leads to a channel-diagonalizing structure, as in the cases of perfect CSIT and statistical CSIT with mean or covariance feedback, and reduces the complicated matrix-valued problem to a scalar power allocation problem. Then we provide the closed-form solution to the resulting power allocation problem.

241 citations


Journal ArticleDOI
TL;DR: This paper transforms a spectrum sharing based cognitive radio (CR) communication system into a second order cone programming (SOCP) problem and then solves it via a standard interior point algorithm and develops an analytical solution with significantly reduced complexity from a geometric perspective.
Abstract: This paper considers a spectrum sharing based cognitive radio (CR) communication system, which consists of a secondary user (SU) having multiple transmit antennas and a single receive antenna and a primary user (PU) having a single receive antenna. The channel state information (CSI) on the link of the SU is assumed to be perfectly known at the SU transmitter (SU-Tx). However, due to loose cooperation between the SU and the PU, only partial CSI of the link between the SU-Tx and the PU is available at the SU-Tx. With the partial CSI and a prescribed transmit power constraint, our design objective is to determine the transmit signal covariance matrix that maximizes the rate of the SU while keeping the interference power to the PU below a threshold for all the possible channel realizations within an uncertainty set. This problem, termed the robust cognitive beamforming problem, can be naturally formulated as a semi-infinite programming (SIP) problem with infinitely many constraints.We first transform this problem into a second order cone programming (SOCP) problem and then solve it via a standard interior point algorithm. Then, an analytical solution with significantly reduced complexity is developed from a geometric perspective. It is shown that both algorithms yield the same optimal solution. Simulation examples are presented to validate the effectiveness of the proposed algorithms.

227 citations


Journal ArticleDOI
TL;DR: Numerical results show that PU2RC achieves higher throughput and is more robust against CSI quantization errors than the popular alternative of zero-forcing beamforming if the number of users is sufficiently large, and the asymptotic throughput scaling laws forPU2RC with a large user pool are derived for different regimes of the signal-to-noise ratio (SNR).
Abstract: On the multiantenna broadcast channel, the spatial degrees of freedom support simultaneous transmission to multiple users. The optimal multiuser transmission, which is known as dirty paper coding, is not directly realizable. Moreover, close-to-optimal solutions such as Tomlinson-Harashima precoding are sensitive to channel state information (CSI) inaccuracy. This paper considers a more practical design called per user unitary and rate control (PU2RC), which has been proposed for emerging cellular standards. PU2RC supports multiuser simultaneous transmission, enables limited feedback, and is capable of exploiting multiuser diversity. Its key feature is an orthogonal beamforming (or precoding) constraint, where each user selects a beamformer (or precoder) from a codebook of multiple orthonormal bases. In this paper, the asymptotic throughput scaling laws for PU2RC with a large user pool are derived for different regimes of the signal-to-noise ratio (SNR). In the multiuser interference-limited regime, the throughput of PU2RC is shown to logarithmically scale with the number of users. In the normal SNR and noise-limited regimes, the throughput is found to scale double logarithmically with the number of users and linearly with the number of antennas at the base station. In addition, numerical results show that PU2RC achieves higher throughput and is more robust against CSI quantization errors than the popular alternative of zero-forcing beamforming if the number of users is sufficiently large.

224 citations


Journal ArticleDOI
TL;DR: This paper shows how convex approximation-based multicast beamforming tools (originally developed without regard to primary interference constraints) can be adapted to work in a spectrum underlay context and demonstrates the effectiveness of the proposed approaches.
Abstract: Secondary spectrum usage has the potential to considerably increase spectrum utilization. In this paper, quality-of-service (QoS)-aware spectrum underlay of a secondary multicast network is considered. A multiantenna secondary access point (AP) is used for multicast (common information) transmission to a number of secondary single-antenna receivers. The idea is that beamforming can be used to steer power towards the secondary receivers while limiting sidelobes that cause interference to primary receivers. Various optimal formulations of beamforming are proposed, motivated by different ldquocohabitationrdquo scenarios, including robust designs that are applicable with inaccurate or limited channel state information at the secondary AP. These formulations are NP-hard computational problems; yet it is shown how convex approximation-based multicast beamforming tools (originally developed without regard to primary interference constraints) can be adapted to work in a spectrum underlay context. Extensive simulation results demonstrate the effectiveness of the proposed approaches and provide insights on the tradeoffs between different design criteria.

221 citations


Journal ArticleDOI
TL;DR: This paper addresses the problem of robust transceiver design in a downlink multiuser system, with respect to the erroneous channel knowledge at the transmitter, using semidefinite programming methods from convex optimization theory.
Abstract: The knowledge of the channel at the transmit side of a communication system can be exploited by using precoding techniques, from which the overall transmission quality might benefit significantly. However, in practical wireless systems, the channel state information is prone to errors, which sometimes deteriorates the performance drastically. In this paper, we address the problem of robust transceiver design in a downlink multiuser system, with respect to the erroneous channel knowledge at the transmitter. The base station is equipped with an antenna array, while users have single antennas. The transceiver optimization is performed under a set of predefined users' quality-of-service constraints, defined as maximum mean square errors, or minimum signal-to-interference-plus-noise ratios (SINRs), which must be satisfied for all disturbances that belong to given, bounded uncertainty sets. Efficient numerical solutions are obtained using semidefinite programming methods from convex optimization theory. The proposed algorithms are found to outperform related approaches in the literature in terms of the achieved performance, while maintaining low computational complexity. The studied uncertainty models are applicable in mitigating typical errors that emerge as a result of quantization or channel estimation.

214 citations


Proceedings ArticleDOI
28 Jun 2009
TL;DR: A multi-cell MMSE-based precoding is proposed that, when combined with frequency/time/pilot reuse techniques, mitigate this problem of pilot contamination.
Abstract: This paper considers a multi-cell multiple antenna system with precoding at the base stations for downlink transmission. To enable precoding, channel state information (CSI) is obtained via uplink training. This paper mathematically characterizes the impact that uplink training has on the performance of multi-cell multiple antenna systems. When non-orthogonal training sequences are used for uplink training, it is shown that the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells. This problem of pilot contamination is analyzed in this paper. A multi-cell MMSE-based precoding is proposed that, when combined with frequency/time/pilot reuse techniques, mitigate this problem.

213 citations


Journal ArticleDOI
TL;DR: New results on joint linear transceiver design under the minimum total mean-square error (MSE) criterion are presented, with channel mean as well as both transmit and receive correlation information at both ends of a multiple-input multiple-output (MIMO) link.
Abstract: This paper presents new results on joint linear transceiver design under the minimum total mean-square error (MSE) criterion, with channel mean as well as both transmit and receive correlation information at both ends of a multiple-input multiple-output (MIMO) link. The joint design is formulated into an optimization problem. The optimum closed-form precoder and decoder are derived. Compared to the case with perfect channel state information (CSI), linear filters are added at both ends to balance the suppression of channel noise and the noise from imperfect channel estimation. The impact of channel estimation error as well as channel correlation on system performance is assessed, based on analytical and simulation results.

Journal ArticleDOI
TL;DR: It is shown that multi-hop transmission systems employing a decode- and-forward relaying scheme achieve higher ergodic capacities than multi- hop transmission systems with amplify-and- forward relaying schemes.
Abstract: The ergodic capacity in Rayleigh fading of multi- hop wireless transmission systems employing either amplify- and-forward relaying or decode-and-forward relaying is studied, assuming channel state information is only known at the receiving terminals. Two upper bounds based on Jensen's inequality and the harmonic-geometric means inequality as well as an infinite series representation for the ergodic capacity of an amplify-and- forward multi-hop transmission system are derived. Numerical results are provided to examine the tightness of the upper bounds as well as to show the high accuracy of the infinite series approach. In addition, the ergodic capacity of a decode- and-forward multi-hop transmission system is obtained. It is shown that multi-hop transmission systems employing a decode- and-forward relaying scheme achieve higher ergodic capacities than multi-hop transmission systems with amplify-and-forward relaying schemes.

Journal ArticleDOI
TL;DR: This letter shows that the optimal collaborative-relay beamforming (CRB) solution achieves the full diversity of a MISO antenna system and develops a distributed algorithm that allows each individual relay to learn its own weight, based on the Karush-Kuhn-Tucker (KKT) analysis.
Abstract: This letter studies the collaborative use of amplify-and-forward (AF) relays to form a virtual multiple-input single-output (MISO) beamforming system with the aid of perfect channel state information (CSI) in a flat-fading channel. In particular, we optimize the relay weights jointly to maximize the received signal-to-noise ratio (SNR) at the destination terminal with both individual and total power constraints at the relays. We show that the optimal collaborative-relay beamforming (CRB) solution achieves the full diversity of a MISO antenna system. Another main contribution of this letter is a distributed algorithm that allows each individual relay to learn its own weight, based on the Karush-Kuhn-Tucker (KKT) analysis.

Journal ArticleDOI
TL;DR: A general theory for 1:N and M:1 dimension changing mappings is presented, and two examples for a Gaussian source and channel are provided where both a 2:1 bandwidth-reducing and a 1:2 bandwidth-expanding mapping are optimized.
Abstract: This paper deals with lossy joint source-channel coding for transmitting memoryless sources over AWGN channels. The scheme is based on the geometrical interpretation of communication by Kotel'nikov and Shannon where amplitudecontinuous, time-discrete source samples are mapped directly onto the channel using curves or planes. The source and channel spaces can have different dimensions and thereby achieving either compression or error control, depending on whether the source bandwidth is smaller or larger than the channel bandwidth. We present a general theory for 1:N and M:1 dimension changing mappings, and provide two examples for a Gaussian source and channel where we optimize both a 2:1 bandwidth-reducing and a 1:2 bandwidth-expanding mapping. Both examples show high spectral efficiency and provide both graceful degradation and improvement for imperfect channel state information at the transmitter.

Proceedings ArticleDOI
24 Sep 2009
TL;DR: The downlink performance of distributed antenna systems (DAS) in a multi-cell environment is investigated and a simple sub-optimal power allocation scheme is proposed by substituting the approximation for the objective function.
Abstract: In this paper, the downlink performance of distributed antenna systems (DAS) in a multi-cell environment is investigated. The individual power constraints (IPC) for the distributed antennas and the total power constraint (TPC) for all the distributed antennas are proposed to characterize the inter-cell interference power limits and the total transmit power consumption, respectively. When the large-scale channel state information is available at the transmitter, the problem of power allocation among distributed antennas with the target of downlink ergodic capacity maximization is formulated with consideration of IPC and TPC. Based on system scale-up, an approximation of the objective function is derived, which is further proved to be concave on the transmit powers of the distributed antennas. Consequently, a simple sub-optimal power allocation scheme is proposed by substituting the approximation for the objective function. The system capacity with the sub-optimal power allocation is illustrated to be quite close to the optimal one obtained by numerical optimizations.

Posted Content
TL;DR: In this article, a new limited feedback strategy is proposed for multicell beamforming where cooperation is restricted to sharing only the CSI of active users among base stations, and an upper bound on the mean loss in sum rate due to random vector quantization is derived.
Abstract: Base station cooperation improves the sum-rates that can be achieved in cellular systems. Conventional cooperation techniques require sharing large amounts of information over finite-capacity backhaul links and assume that base stations have full channel state information (CSI) of all the active users in the system. In this paper, a new limited feedback strategy is proposed for multicell beamforming where cooperation is restricted to sharing only the CSI of active users among base stations. The system setup considered is a linear array of cells based on the Wyner model. Each cell contains single-antenna users and multi-antenna base stations. Closed-form expressions for the beamforming vectors that approximately maximize the sum-rates in a multicell system are first presented, assuming full CSI at the transmitter. For the more practical case of a finite-bandwidth feedback link, CSI of the desired and interfering channels is quantized at the receiver before being fed back to the base station. An upper bound on the mean loss in sum rate due to random vector quantization is derived. A new feedback-bit allocation strategy, to partition the available bits between the desired and interfering channels, is developed to approximately minimize the mean loss in sum-rate due to quantization. The proposed feedback-bit partitioning algorithm is shown, using simulations, to yield sum-rates close to the those obtained using full CSI at base stations.

Journal ArticleDOI
TL;DR: A general jointly correlated MIMO channel model, which does not require separable spatial correlations at the transmitter and receiver is considered, and an iterative water-filling algorithm with guaranteed convergence is developed.
Abstract: We investigate multiple-input multiple-output (MIMO) eigenmode transmission using statistical channel state information at the transmitter. We consider a general jointly correlated MIMO channel model, which does not require separable spatial correlations at the transmitter and receiver. For this model, we first derive a closed-form tight upper bound for the ergodic capacity, which reveals a simple and interesting relationship in terms of the matrix permanent of the eigenmode channel coupling matrix and embraces many existing results in the literature as special cases. Based on this closed-form and tractable upper bound expression, we then employ convex optimization techniques to develop low-complexity power allocation solutions involving only the channel statistics. Necessary and sufficient optimality conditions are derived, from which we develop an iterative water-filling algorithm with guaranteed convergence. Simulations demonstrate the tightness of the capacity upper bound and the near-optimal performance of the proposed low-complexity transmitter optimization approach.

Journal ArticleDOI
TL;DR: This paper develops optimal resource allocation algorithms for the OFDMA downlink assuming the availability of only partial (imperfect) CSI, and considers both continuous and discrete ergodic weighted sum rate maximization subject to total power constraints, and average bit error rate constraints for the discrete rate case.
Abstract: Previous research efforts on OFDMA resource allocation have typically assumed the availability of perfect channel state information (CSI). Unfortunately, this is unrealistic, primarily due to channel estimation errors, and more importantly, channel feedback delay. In this paper, we develop optimal resource allocation algorithms for the OFDMA downlink assuming the availability of only partial (imperfect) CSI. We consider both continuous and discrete ergodic weighted sum rate maximization subject to total power constraints, and average bit error rate constraints for the discrete rate case. We approach these problems using a dual optimization framework, allowing us to solve these problems with O(MK) complexity per symbol for an OFDMA system with K used subcarriers and M active users, while achieving relative optimality gaps of less than 10-5 for continuous rates and less than 10-3 for discrete rates in simulations based on realistic parameters.

Journal ArticleDOI
TL;DR: The problem of designing multiple-input-multiple-output (MIMO) relay for multipoint to multipoint communication in wireless networks can be relaxed to a convex problem consisting of second-order cone (SOC) and semidefinite cone constraints using the semidfinite relaxation technique.
Abstract: The problem of designing multiple-input-multiple-output (MIMO) relay for multipoint to multipoint communication in wireless networks has been dealt with by considering the fact that only the imperfect channel state information (CSI) is available at the MIMO relay. In particular, assuming that the second-order terms of the uncertainties of the source-relay and relay-destination channels are negligible, we design an amplify-and-forward (AF) MIMO relay that provides robustness against channel uncertainties. In our proposed robust method, the objective is to design the MIMO relay in which the worst-case relay transmit power is minimized by keeping the worst-case signal-to-interference-and-noise ratio (SINR) for all destinations above a certain threshold value. This paper shows that the aforementioned problem is nonconvex but it can be relaxed to a convex problem consisting of second-order cone (SOC) and semidefinite cone constraints using the semidefinite relaxation technique. The optimal solution of the relaxed problem is utilized to generate the best approximate solution of the original nonconvex problem using the well-known randomization technique. Computer simulations verify the robustness of the proposed MIMO relay when compared to the nonrobust MIMO relay.

Journal ArticleDOI
TL;DR: The problem of transceiver optimization in multiuser multiple-input multiple-output downlink wireless systems is considered and the proposed framework can be applied for solving robust counterparts of several related MSE-optimization problems.
Abstract: We study robust transceiver optimization in a downlink, multiuser, wireless system, where the transmitter and the receivers are equipped with antenna arrays. The robustness is defined with respect to imperfect knowledge of the channel at the transmitter. The errors in the channel state information are assumed to be bounded, and certain quality-of-service targets in terms of mean-square errors (MSEs) are guaranteed for all channels from the uncertainty regions. Iterative algorithms are proposed for the transceiver design. The iterations perform alternating optimization of the transmitter and the receivers and have equivalent semidefinite programming representations with efficient numerical solutions. The framework supports robust counterparts of several MSE-optimization problems, including transmit power minimization with per-user or per-stream MSE constraints, sum MSE minimization, min-max fairness, etc. Although the convergence to the global optimum cannot be claimed due to the intricacy of the problems, numerical examples show good practical performance of the presented methods. We also provide various possibilities for extensions in order to accommodate a broader set of scenarios regarding the precoder structure, the uncertainty modeling, and a multicellular setup.

Journal ArticleDOI
TL;DR: Analytical results concerning CSI feedback are derived by modeling quantized CSI as a first-order finite-state Markov chain and feedback delay is proved to reduce the throughput gain due to CSI feedback at least exponentially.
Abstract: Feedback of quantized channel state information (CSI), called limited feedback, enables transmit beamforming in multiple-input-multiple-output (MIMO) wireless systems with a small amount of overhead. Due to its efficiency, beamforming with limited feedback has been adopted in several wireless communication standards. Prior work on limited feedback commonly adopts the block fading channel model where temporal correlation in wireless channels is neglected. In this paper, we consider temporally correlated channels and design single-user transmit beamforming with limited feedback. Analytical results concerning CSI feedback are derived by modeling quantized CSI as a first-order finite-state Markov chain. These results include the information rate of the CSI quantizer output, the bit rate a CSI feedback channel is required to support, and the effect of feedback delay on throughput. In particular, based on the theory of Markov chain convergence rate, feedback delay is proved to reduce the throughput gain due to CSI feedback at least exponentially. Furthermore, an algorithm is proposed for CSI feedback compression in time. Combining the results in this work leads to a new method for designing limited feedback beamforming as demonstrated by a design example.

Patent
08 Jan 2009
TL;DR: In this paper, a method for transmitting and receiving channel state information (CSI) periodically and aperiodically is disclosed, which includes receiving an indicator requesting a CSI report from a base station over a downlink control channel, and a periodically transmitting the CSI to the BS over a physical uplink shared channel (PUSCH) upon receiving the indicator.
Abstract: A method for transmitting and receiving channel state information (CSI) periodically and aperiodically is disclosed. The method for aperiodically transmitting channel state information (CSI) by a terminal includes receiving an indicator requesting a channel state information report of a downlink channel from a base station over a downlink control channel, and aperiodically transmitting the channel state information (CSI) to the base station over a physical uplink shared channel (PUSCH) upon receiving the indicator from the base station.

Journal ArticleDOI
TL;DR: Simulation results show that hybrid RF/FSO systems with BICM outperform previously proposed hybrid systems employing a simple repetition code and selection diversity and develop code design and power assignment criteria and provide an efficient code search procedure.
Abstract: In this paper, we propose a novel architecture for hybrid radio frequency (RF)/free-space optics (FSO) wireless systems. Hybrid RF/FSO systems are attractive since the RF and FSO sub-systems are affected differently by weather and fading phenomena. For example, while 60-GHz RF systems are susceptible to rain, fog is detrimental to FSO systems. We show that a hybrid system robust to these impairments is obtained by joint bit-interleaved coded modulation (BICM) of the bit steams transmitted over the RF and FSO sub-channels. An asymptotic performance analysis reveals that a properly designed convolutional code can exploit the diversity offered by the independent sub-channels. Furthermore, we develop code design and power assignment criteria and provide an efficient code search procedure. The cut-off rate of the proposed hybrid system is also derived and compared to that of hybrid systems with perfect channel state information at the transmitter. Simulation results show that hybrid RF/FSO systems with BICM outperform previously proposed hybrid systems employing a simple repetition code and selection diversity.

Journal ArticleDOI
TL;DR: The framework relies on the Moment Generating Function (MGF-) based approach for performance analysis of communication systems over fading channels, and on some properties of the Laplace Transform, which allow to develop a single-integral relation between the M GF of a random variable and the MGF of its inverse.
Abstract: In this Letter, we propose a comprehensive framework for performance analysis of cooperative wireless systems using Amplify and Forward (AF) relay methods. The framework relies on the Moment Generating Function (MGF-) based approach for performance analysis of communication systems over fading channels, and on some properties of the Laplace Transform, which allow to develop a single-integral relation between the MGF of a random variable and the MGF of its inverse. Moreover, a simple lower bound for Outage Probability (Pout) and Outage Capacity (OC) computation is also introduced. Numerical and simulation results are provided to substantiate the accuracy of the proposed framework.

Journal ArticleDOI
TL;DR: It is proved, under a condition on the quality of the estimated CSI, the robust-optimal collaborative-relay beamforming (CRBF) can be obtained by S-procedure and rank relaxation techniques, and a distributed algorithm is developed by examining the structure of the optimal CRBF solution.
Abstract: Relay communications is a promising technique to extend the range of wireless communications by forwarding the message from the sender to the intended destination. While fixed or variable-power relays have been previously investigated, this paper addresses the collaborative use of variable-phase variable-power amplify-and-forward (AF) relays for robust beamforming, with the aid of imperfect channel state information (CSI) at the sender. In particular, the maximization of the worst-case signal-to-noise ratio (SNR) at the destination terminal is studied under a bounded spherical region for the norm of the CSI error vector from the relays to the destination. Our main contribution is that we prove, under a condition on the quality of the estimated CSI, the robust-optimal collaborative-relay beamforming (CRBF) can be obtained by S-procedure and rank relaxation techniques. In addition, a distributed algorithm is developed by examining the structure of the optimal CRBF solution. Results demonstrate a significant gain of CRBF over non-robust approaches.

Journal ArticleDOI
TL;DR: Analytical and simulation-based performance results illustrate that notable performance improvements compared to non-cooperative transmission are achieved by the proposed schemes, especially when more than two hops are considered, and that the proposed distributed TPA schemes typically perform close to the OC-TPA solution.
Abstract: In this paper, we consider a relay-assisted wideband cognitive-radio (CR) system under the assumption that the frequency band chosen by the CR relay network for unlicensed spectrum usage overlaps with one or more bands dedicated to primary (e.g., licensed) narrowband links. Our objective is to optimize the performance of the CR system while limiting the interference in direction of the primary receivers, without requiring any adaptation of the transmitted signal spectra at the cognitive nodes. To this end, we study appropriate transmit power allocation (TPA) strategies among the cognitive relays. We first investigate the optimal centralized (OC) TPA solution and show that it can be formulated as a linear program. Since the OC-TPA solution requires a considerable amount of information exchange between the cognitive nodes, we develop two distributed TPA schemes, namely (i) a fully decentralized (FD) TPA scheme and (ii) a distributed feedback-assisted (DFA) TPA scheme. The FD-TPA scheme aims at maximizing the output signal-to-interference- plus-noise ratio (SINR) at the destination node of the CR network according to a best-effort strategy. It requires neither feedback information from the destination node nor an exchange of channel state information between the cognitive relays. The DFA-TPA scheme, on the other hand, utilizes feedback information from the destination node, in order to achieve a predefined target output SINR value, while minimizing the overall transmit power spent by the relays. Analytical and simulation-based performance results illustrate that notable performance improvements compared to non-cooperative transmission (i.e., without relay assistance) are achieved by the proposed schemes, especially when more than two hops are considered. In particular, the proposed distributed TPA schemes typically perform close to the OC-TPA solution.

Proceedings ArticleDOI
01 Nov 2009
TL;DR: Using the obtained bounds, the optimal number of data streams to transmit, and the optimal SRDOF to use for interference cancellation are derived that provide the best scaling of the transmission capacity with the number of antennas.
Abstract: The transmission capacity of an ad-hoc network is the maximum density of active transmitters in an unit area, given an outage constraint at each receiver for a fixed rate of transmission. Assuming channel state information is available at the receiver, this paper presents bounds on the transmission capacity as a function of the number of antennas used for transmission, and the spatial receive degrees of freedom used for interference cancelation at the receiver. Canceling the strongest interferers, using a single antenna for transmission together with using all but one spatial receive degrees of freedom for interference cancelation is shown to maximize the transmission capacity. Canceling the closest interferers, using a single antenna for transmission together with using a fraction of the total spatial receive degrees of freedom for interference cancelation depending on the path loss exponent, is shown to maximize the transmission capacity.

Journal ArticleDOI
TL;DR: The moment generating function (MGF) is evaluated for the probability density function characterizing this new channel model and the derived MGF expression is used in evaluating the bit error rate for different coherent modulation techniques over this generalized fading channel.
Abstract: In this letter, we consider the alpha - mu channel fading model and we evaluate the moment generating function (MGF) for the probability density function characterizing this new channel model. The derived MGF expression is used in evaluating the bit error rate for different coherent modulation techniques over this generalized fading channel. We also derive an expression for the outage probability for this channel model. All the derived expressions are in closed forms and general that can reduce to the well known fading channel distributions in the literature such as Rayleigh, Nakagami-m, and Weibull model as special cases.

Proceedings ArticleDOI
19 Apr 2009
TL;DR: An amplify-and-forward based cooperative protocol to improve the security of of wireless communications and assuming availability of global channel state information, system design that maximizes the secrecy capacity is considered.
Abstract: A physical layer approach to security for wireless networks is considered. In single-antenna wireless systems, such approaches are hampered by channel conditions in the presence of one or more eavesdroppers. Cooperation has the potential to overcome this problem and improve the security of of wireless communications. In this paper, an amplify-and-forward based cooperative protocol is proposed. Assuming availability of global channel state information, system design that maximizes the secrecy capacity is considered. Since the optimal solution to this problem is intractable, suboptimal closed-form solutions are proposed that optimize bounds on secrecy capacity for the case of a single eavesdropper, or that introduce additional constraints, such as nulling of signals at all eavesdroppers, for the case of multiple eavesdroppers.

Posted Content
TL;DR: This paper investigates collaborative use of relays to form a beamforming system with the aid of perfect channel state information (CSI) and to provide physical-layer security and a simplified and suboptimal technique which reduces the computation complexity under individual power constraints.
Abstract: In this paper, collaborative use of relays to form a beamforming system and provide physical-layer security is investigated. In particular, decode-and-forward (DF) and amplify-and-forward (AF) relay beamforming designs under total and individual relay power constraints are studied with the goal of maximizing the secrecy rates when perfect channel state information (CSI) is available. In the DF scheme, the total power constraint leads to a closed-form solution, and in this case, the optimal beamforming structure is identified in the low and high signal-to-noise ratio (SNR) regimes. The beamforming design under individual relay power constraints is formulated as an optimization problem which is shown to be easily solved using two different approaches, namely semidefinite programming and second-order cone programming. A simplified and suboptimal technique which reduces the computation complexity under individual power constraints is also presented. In the AF scheme, not having analytical solutions for the optimal beamforming design under both total and individual power constraints, an iterative algorithm is proposed to numerically obtain the optimal beamforming structure and maximize the secrecy rates. Finally, robust beamforming designs in the presence of imperfect CSI are investigated for DF-based relay beamforming, and optimization frameworks are provided