Channel Distribution Information Research Articles

Sum Outage Capacity Maximization in Cognitive Radio Networks with Channel Distribution Information

Sum Outage Capacity Maximization in Cognitive Radio Networks with Channel Distribution Information

Resource Allocation in Decode-and-Forward Cooperative Communications Networks with Limited Rate Feedback Channel

In this paper, we propose a limited rate feedback scheme for decode-and-forward (DF) relay-assisted networks. It is assumed that the cellular user is far from the base station such that the direct communication is impossible and communication is performed with the help of a DF relay. To study the limited feedback channel, two cases are proposed: Perfect channel distribution information (CDI)-quantized channel state information (CSI) and quantized CDI-quantized CSI. While in the former, the space of channel gains is quantized into a finite number of regions, in the latter case, the space of CDI parameters is also quantized. We formulate the proposed resource allocation into an optimization problem whose objective is to maximize the average achievable rate under an average transmission power constraint. To solve the proposed optimization problems, we adopt the block coordinated descent algorithm, which is based on the space of variables partitioning into finite sets, and particle swarm optimization (PSO), which is an evolutionary computation technique. To solve the optimization problem for quantized CDI-quantized CSI case, we consider an approach based on the Lloyd algorithm. We also model and study the error in the feedback channel. Finally, the impact of different system parameters on the performance of the proposed scheme is investigated through simulations.

Artificial Noise Assisted Secure Transmission Under Training and Feedback

This paper proposes a framework for the artificial noise assisted secure transmission in multiple-input, multiple-output, multiple antenna eavesdropper (MIMOME) wiretap channels in frequency-division duplexed (FDD) systems. We focus on a practical scenario that only the eavesdroppers’ channel distribution information (CDI) is available and the imperfect channel state information (CSI) of the legitimate receiver is acquired through training and analog feedback. By taking explicitly into account the signaling overhead and training power overhead incurred by channel estimation and feedback, we define the achievable effective ergodic secrecy rate (ESR), and investigate a joint power allocation and training overhead optimization problem for the maximization of effective ESR. We first derive a deterministic approximation for the achievable effective ESR which facilitates the joint optimization. Then, efficient iterative algorithms are proposed to solve the considered nonconvex optimization problem. In particular, in the high-SNR regime, a block coordinate descent method (BCDM) is proposed to handle the joint optimization. In the low-SNR regime, we transform the problem into a sequence of geometric programmings (GPs) and locate its Karush–Kuhn–Tucker (KKT) solution using the successive convex approximation (SCA) method. For the general case of SNR, we maximize the lower bound of the achievable effective ESR. Simulation results corroborate the theoretical analysis and illustrate the secrecy performance of the proposed secure transmission scheme.

Minimum BER Power Allocation for OFDM-based Cognitive Radio Networks

In this paper, the optimal power allocation algorithm that minimizes the aggregate bit error rate (BER) of the secondary user (SU) in a downlink orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) system, while subjecting to the interference power constraint and the transmit power constraint, is investigated under the assumption that the instantaneous channel state information (CSI) of the interference links between the secondary transmitter and the primary receiver, and between the primary transmitter and the secondary receiver is perfectly known. Besides, a suboptimal algorithm with less complexity is also proposed. In order to deal with more practical situations, we further assume that only the channel distribution information (CDI) of the interference links is available and propose heuristic power allocation algorithms based on bisection search method to minimize the aggregate BER under the interference outage constraint and the transmit power constraint. Simulation results are presented to verify the effectiveness of the proposed algorithms.

Multicell Coordinated Beamforming With Rate Outage Constraint—Part I: Complexity Analysis

This paper studies the coordinated beamforming (CoBF) design in the multiple-input single-output interference channel, assuming only channel distribution information given a priori at the transmitters. The CoBF design is formulated as an optimization problem that maximizes a predefined system utility, e.g., the weighted sum rate or the weighted max-min-fairness (MMF) rate, subject to constraints on the individual probability of rate outage and power budget. While the problem is non-convex and appears difficult to handle due to the intricate outage probability constraints, so far it is still unknown if this outage constrained problem is computationally tractable. To answer this, we conduct a computational complexity analysis of the outage constrained CoBF problem. Specifically, we show that the outage constrained CoBF problem with the weighted sum rate utility is intrinsically difficult, i.e., NP-hard. Moreover, the outage constrained CoBF problem with the weighted MMF rate utility is also NP-hard except the case when all the transmitters are equipped with single antenna. The presented analysis results confirm that efficient approximation methods are indispensable to the outage constrained CoBF problem.

Multicell Coordinated Beamforming With Rate Outage Constraint—Part II: Efficient Approximation Algorithms

This paper studies the coordinated beamforming (CoBF) design for the multiple-input single-output interference channel, provided that only channel distribution information is known to the transmitters. The problem under consideration is a probabilistically constrained optimization problem which maximizes a predefined system utility subject to constraints on rate outage probability and power budget of each transmitter. Our recent analysis has shown that the outage-constrained CoBF problem is intricately difficult, e.g., NP-hard. Therefore, the focus of this paper is on suboptimal but computationally efficient algorithms. Specifically, by leveraging on the block successive upper bound minimization (BSUM) method in optimization, we propose a Gauss-Seidel type algorithm, called distributed BSUM algorithm, which can handle differentiable, monotone and concave system utilities. By exploiting a weighted minimum mean-square error (WMMSE) reformulation, we further propose a Jocobi-type algorithm, called distributed WMMSE algorithm, which can optimize the weighted sum rate utility in a fully parallel manner. Both algorithms are shown to converge to the stationary points of the original NP-hard problems. To further provide a performance benchmark, a relaxed approximation method based on polyblock outer approximation is also proposed. Simulation results show that the proposed algorithms are significantly superior to the existing successive convex approximation method in both performance and computational efficiency, and can yield promising approximation performance by comparing with the performance benchmark.

Outage Constrained Secrecy Throughput Maximization for DF Relay Networks

In this paper, we provide a comprehensive study of secrecy transmission in decode-and-forward (DF) relay networks subjected to slow fading. With only channel distribution information (CDI) of the wiretap channels, we aim at maximizing secrecy throughput of the two-hop transmission under a secrecy outage constraint through optimizing transmission region, rate parameters of the wiretap codes and power allocation between the source and relay. We propose fixed transmission parameter scheme (FTPS) and variable transmission parameter scheme (VTPS), which are based on the CDI and instantaneous channel state information of the main channels, respectively. In both schemes, source and relay use the same codeword, and the eavesdropper can use maximum ratio combining (MRC) reception. To improve the secrecy throughput, we further propose VTPS-D1 and VTPS-D2 schemes, where the source and relay either use independent codewords with identical code rates, or different codebooks with different code rates so that the eavesdropper can only decode the two-hop signals individually rather than using MRC. We provide explicit results on the design for all proposed schemes. Numerical results and comparisons on the secrecy throughput of these schemes are presented to reveal their respective superiorities and give some insights into the choice of design scheme.

A New Proof for the DoF Region of the MIMO Networks With No CSIT

In this paper, a new proof for the degrees of freedom (DoF) region of the K-user multiple-input multiple-output (MIMO) broadcast channel (BC) with no channel state information at the transmitter (CSIT) and perfect channel state information at the receivers (CSIR) is provided. Based on this proof, the capacity region of a certain class of MIMO BC with channel distribution information at the transmitter (CDIT) and perfect CSIR is derived. Finally, an outer bound for the DoF region of the K-user MIMO interference channel (IC) with no CSIT is provided.

Outage Minimization for a Fading Wireless Link With Energy Harvesting Transmitter and Receiver

This paper studies online power control policies for outage minimization in a fading wireless link with energy harvesting transmitter and receiver. The outage occurs when either the transmitter or the receiver does not have enough energy, or the channel is in outage, where the transmitter only has the channel distribution information. Under infinite battery capacity and without retransmission, we prove that threshold-based power control policies are optimal. We thus propose disjoint/joint threshold-based policies with and without battery state sharing between the transmitter and receiver, respectively. We also analyze the impact of practical receiver detection and processing on the outage performance. When retransmission is considered, policy with linear power levels is adopted to adapt the power thresholds per retransmission. With finite battery capacity, a three dimensional finite state Markov chain is formulated to calculate the optimal parameters and corresponding performance of proposed policies. The energy arrival correlation between the transmitter and receiver is addressed for both finite and infinite battery cases. Numerical results show the impact of battery capacity, energy arrival correlation and detection cost on the outage performance of the proposed policies, as well as the tradeoff between the outage probability and the average transmission times.

Hybrid Opportunistic Relaying and Jamming With Power Allocation for Secure Cooperative Networks

This paper studies the cooperative transmission for securing a decode-and-forward (DF) two-hop network where multiple cooperative nodes coexist with a potential eavesdropper. Under the more practical assumption that only the channel distribution information (CDI) of the eavesdropper is known, we propose an opportunistic relaying with artificial jamming secrecy scheme, where a “best” cooperative node is chosen among a collection of N possible candidates to forward the confidential signal and the others send jamming signals to confuse the eavesdroppers. We first investigate the ergodic secrecy rate (ESR) maximization problem by optimizing the power allocation between the confidential signal and jamming signals. In particular, we exploit the limiting distribution technique of extreme order statistics to build an asymptotic closed-form expression of the achievable ESR and the power allocation is optimized to maximize the ESR lower bound. Although the optimization problems are non-convex, we propose a sequential parametric convex approximation (SPCA) algorithm to locate the Karush-Kuhn-Tucker (KKT) solutions. Furthermore, taking the time variance of the legitimate links' CSIs into consideration, we address the impacts of the outdated CSIs to the proposed secrecy scheme, and derive an asymptotic ESR. Finally, we generalize the analysis to the scenario with multiple eavesdroppers, and give the asymptotic analytical results of the achievable ESR. Simulation results confirm our analytical results.

Capacity of Cognitive Radio with Partial Channel Distribution Information in Rayleigh Fading Environments

AbstractThis paper investigates the capacity of the secondary user (SU) in a cognitive radio (CR) network in Rayleigh fading environments. Different from existing works where perfect channel state information (CSI) or channel distribution information (CDI) of the interference link from the SU to the primary user (PU) is assumed to be available, this paper assumes that only partial CDI is available. Specifically, we assume the distribution parameter is unknown and estimated from a set of channel gain samples. With such partial CDI, closed-form expressions for the ergodic and outage capacities of the SU are obtained under the transmit power and the interference outage constraints. It is shown that the capacity with partial CDI is not degraded compared to that with perfect CDI if the interference outage constraint is loose. It is also shown that the capacity can be significantly improved by increasing the number of channel gain samples.

Quantized Ergodic Radio Resource Allocation in Cognitive Networks With Guaranteed Quality of Service for Primary Network

In this paper, for cognitive networks, ergodic resource allocation (ERA) in the downlink of an OFDMA-based secondary network is investigated, assuming the availability of quantized channel state information (CSI) between the secondary base station and secondary users. The main objective is to maximize the average sum rate of the secondary network subject to the average total transmission power constraint and the collision probability constraint of the primary users on each subcarrier. In the proposed scheme, there is no need for the instantaneous handshaking between secondary and primary networks to provide CSI between the secondary base station and primary receivers. In fact, the secondary base station only needs the knowledge of channel distribution information. Due to the probabilistic nature of the collision probability constraint in the proposed ERA problem, it cannot be solved by conventional methods such as dual decomposition. Therefore, we propose two novel suboptimal solutions called the iterative and analytical approaches. It is also demonstrated that the solutions obtained based on the proposed approaches are very close to the optimal solution. Numerical experiments are then carried out to demonstrate the performance of the proposed methods. Numerical results show that the performance of the analytical approach is inferior to that of the iterative approach, although it exhibits significantly less computational complexity.

Outage-Constrained Coordinated Beamforming With Opportunistic Interference Cancellation

In this paper, interference management is considered for the K-user multiple-input single-output (MISO) block-faded interference channel. It is assumed that perfect channel state information (CSI) can be obtained at the receivers, whereas only channel distribution information (CDI) is available to the transmitters. Furthermore, the receivers are assumed to be capable of implementing opportunistic interference cancellation (OIC). Based on these assumptions, the beamforming design problem for the MISO interference channel under consideration is formulated as a rate utility maximization problem under outage constraints and individual power constraints. By implementing OIC at the receivers, the outage probability is expected to be reduced, leading to a potential improvement on the utility value. However, this flexibility complicates the outage constraint, resulting in an optimization problem that is non-convex and difficult to handle. We propose a successive convex approximation (SCA) method that employs first-order approximation techniques and semi-definite relaxation (SDR) to efficiently obtain an approximate beamforming solution to this problem. Our proposed SCA algorithm has been shown to yield solutions that are stationary points of the original beamforming design problem. Furthermore, a decentralized version of the SCA algorithm is proposed, in which only local CDI and a limited amount of information exchange between transmitters are required. Our simulation results demonstrate that both of our proposed algorithms achieve near-optimal performance for the two-user case, and that enabling the receivers to implement OIC indeed improves the system performance by as large as 260% at high signal-to-noise ratios when user fairness is considered.

Interference Mitigation and Signal Enhancement for Multiuser MIMO Interference Channels With Redundant Antennas

For a transceiver pair in a multiuser Gaussian interference channel with multiple antennas, if the number of transmit antennas is greater than the number of receive antennas, then in an equivalent virtual channel this transceiver pair has redundant transmit antennas. These redundant antennas do not contribute to the transmission to the intended receiver, however, may generate interference to other receivers. The optimal way to use these redundant antennas to mitigate interference and enhance the useful signal is studied, under the assumption of perfect channel state information, channel distribution information, and imperfect channel state information at the transmitter side, respectively.

Overcoming Large-Scale Fading in Cellular Systems With Network Coordination

The cellular systems with network coordination are known for increasing the cell edge user throughput by processing signals captured by geographically distributed base stations coherently. This concept is also known as macrodiversity or coordinated multipoint (CoMP) in the literature. It is now well known that large-scale fading has a significant influence on the link-level performance of users in multiuser (MU) multicell systems. In this paper, we investigate a channel distribution information (CDI)-based MU multiple-input-multiple-output (MIMO) power control problem in the uplink with joint processing to overcome the large-scale fading in macrodiversity systems. There are many power control algorithms for different variants of this problem, but the CDI-based problem in MU scenario has not been well addressed in the literature. Perhaps, the lack of understanding of the performance of macrodiversity MU systems, in terms of CDI, may have prohibited advanced power control solutions. Despite such analytical difficulties, we propose a simple algorithm for this uplink power control problem, and its accuracy is proved using Monte Carlo simulation.

Relay assisted OFDMA spectrum sharing systems

ABSTRACTIn this paper, we propose relay assisted orthogonal frequency‐division multiple access (OFDMA) spectrum sharing system. We then design downlink radio resource allocation schemes for the proposed system with the objective of maximizing the secondary service sum rate. Two cases are considered, in the first (second) case, we assume that the channel distribution information (CDI) (the channel side information (CSI)) for the channel between the secondary transmitter and primary receiver is available at the secondary base station. For both cases, we further consider the availability of imperfect CSI of the channel between the secondary base station and the relay stations and the channel between the relay stations and the secondary users. The computational complexity issue is then addressed by proposing suboptimal solutions. Extensive simulation studies show that the impact of imperfectness in channel estimation on the system performance can be controlled by employing relays in the system. Simulation studies are also conducted to compare the performance of the two earlier mentioned cases, which indicates that in case of imperfect CSI estimation, it is often better to use CDI and let the collision probability be managed through corresponding optimised radio resource allocation. Using CDI then eliminates the need for feedback signalling between primary and secondary systems. Copyright © 2012 John Wiley & Sons, Ltd.

User Capacity Scaling Laws of Multi-user Fading Channels in the Presence of MMSE Channel Estimators

Considering development of delay-sensitive applications in wireless communications and cellular networks along with lack of system resources and environmental factors including fading and noise all together make it impossible for all users to be active and to achieve quality of service requirements simultaneously. To analyze wireless systems performance, user capacity is defined as the maximum number of users that can be activated at the same time. In order to obtain user capacity scaling laws, channel distribution information is required and channel gains can be estimated by different channel estimators such as minimum mean square error estimators. In this paper, estimated channel gains are substituted for true channel gains and effects of imperfect channel estimation errors on the user capacity scaling laws are analyzed. It is shown that the user capacity scales double logarithmically and there is a gap depending on channel estimators accuracy between the lower and upper bounds. Moreover, assuming estimated channels for different users are independent and identically distributed, it is shown that the user capacity scaling laws are asymptotically tight.

Optimal Power Allocation for Outage Probability Minimization in Fading Channels with Energy Harvesting Constraints

This paper studies the optimal power allocation for outage probability minimization in point-to-point fading channels with the energy-harvesting constraints and channel distribution information (CDI) at the transmitter. Both the cases with non-causal and causal energy state information (ESI) are considered, which correspond to the energy-harvesting (EH) rates being known and unknown prior to the transmissions, respectively. For the non-causal ESI case, the average outage probability minimization problem over a finite horizon of N EH periods is shown to be non-convex for a large class of practical fading channels. However, the globally optimal "offline" power allocation is obtained by a forward search algorithm with at most N one-dimensional searches, and the optimal power profile is shown to be non-decreasing over time and have an interesting "save-then-transmit" structure. In particular, for the special case of N=1, our result revisits the classic outage capacity for fading channels with uniform power allocation. Moreover, for the case with causal ESI, we propose both the optimal and suboptimal "online" power allocation algorithms, by applying the technique of dynamic programming and exploring the structure of optimal offline solutions, respectively.

Maximum a Posteriori Based Channel Estimation Strategy for Two-Way Relaying Channels

Wireless network coding can significantly improve the spectrum efficiency for relaying transmission when receivers can acquire accurate channel state information (CSI). In this paper, the channel estimation problem for two-way relaying channels is considered where two sources exchange information through an amplify-and-forward relay employing analog network coding protocol. By taking advantage of the apriori information of wireless channels to further improve channel estimation accuracy, the maximum a posteriori (MAP) based estimation schemes are developed to estimate the composite source-source channel coefficients and the amplitude of individual source-relay channels with apriori knowledge of channel distribution information (CDI). Variations of MAP estimation algorithms are also developed for systems under practical constraints where channel CDI needs to be estimated. In particular, scale MAP estimator as well as a long term estimation algorithm is developed to effectively control the negative impact of CDI estimation error on MAP estimation performance. The simulation results show that the MAP based estimation strategies consistently outperform maximum likelihood estimation methods in the measure of mean square error, thus establishes the advantage of presented MAP based schemes.

Cross-Layer Framework for Multiuser Real Time H.264/AVC Video Encoding and Transmission over Block Fading MIMO Channels Using Outage Probability

We present a framework for cross-layer optimized real time multiuser encoding of video using a single layer H.264/AVC and transmission over MIMO wireless channels. In the proposed cross-layer adaptation, the channel of every user is characterized by the probability density function of its channel mutual information and the performance of the H.264/AVC encoder is modeled by a rate distortion model that takes into account the channel errors. These models are used during the resource allocation of the available slots in a TDMA MIMO communication system with capacity achieving channel codes. This framework allows for adaptation to the statistics of the wireless channel and to the available resources in the system and utilization of the multiuser diversity of the transmitted video sequences. We show the effectiveness of the proposed framework for video transmission over Rayleigh MIMO block fading channels, when channel distribution information is available at the transmitter.