Outage Constraint Research Articles

Performance of Cognitive Radios in Dynamic Fading Channels Under Primary Outage Constraint

This article investigates the performance of a cognitive user in a dynamic fading environment. The cognitive user communicates, using a spectrum-sharing technology, over a channel reserved to a primary user (PU). The transmit power of the cognitive user satisfies the outage probability constraint of the PU. The channels of the primary and cognitive users experience independent and non-identically distributed fading models. Nakagami- $$m$$ m and hyper-Nakagami- $$m$$ m channel fading models are specifically considered. The cognitive user's mean transmit power, channel capacity, and bit error rate are derived for this setup. In addition, numerical results are presented to verify the theoretical analysis and investigate the effects of the parameters of the communication environment on the performance measures of the cognitive user.

On the Tradeoff Between Spectral Efficiency and Energy Efficiency of Homogeneous Cellular Networks With Outage Constraint

In this paper, the tradeoff relationship between the spectral efficiency (SE) and energy efficiency (EE) of homogenous cellular networks in which the BSs are arbitrarily distributed is investigated. The network performance metrics of SE and EE are assessed subject to a downlink transmission outage constraint in interference-limited operational environments. The EE is expressed in closed form as a function of SE, based on which the performance bounds of the network are derived. Unlike the traditional inverse relationship between SE and EE, it is found in this paper that there exists an operational regime for which both the SE and EE increase while satisfying the outage requirement, and the density of base stations (BSs) simultaneously sharing the spectrum is optimal. The difference in the performance achieved for the SE when operating in the EE maximizing mode as compared with the SE maximizing mode strongly depends on the received signal-to-interference ratio (SIR) threshold. In the SE-EE tradeoff regime, the analytical tools from microeconomics theory are applied to determine the optimal BS density with respect to the utility achieved by the network operator via balancing the SE and EE objectives. Numerical results show that, by tuning a preference factor toward either the SE or EE metrics, it is feasible to realize Pareto optimal performance.

Interference management with adaptive fractional frequency reuse for LTE-A femtocells networks

This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse (FFR) scheme for macro and femto networks. The strategy aims to maximize the system throughput taking into account a number of system constraints. Here, the system constrains consist of the outage constraints of two-tier users and macrocell spectral efficiency requirement. The detailed procedures of our proposed strategy are: 1) A reference signal received power (RSRP) based selection algorithm is presented to adaptively select the optional FFR schemes satisfying the outage constraints. 2) Considering the macrocell spectral efficiency, the optimal FFR scheme is selected from the optional FFR schemes at MeNB side, to achieve the maximum system throughput in two-tier femtocell networks. We study the efficacy of the proposed strategy using an long term evolution advanced (LTE-A) system level simulator. Simulation results show that our proposed interference management strategy can select the best FFR scheme to maximize the system throughput, and the FFR schemes derived by using RSRP-based selection algorithm can be the effective solutions to deploy femtocells in macrocells.

Analysis and Design of Wireless Ad Hoc Networks With Channel Estimation Errors

We investigate the impact and design of two important application dependent parameters - the effective per-node data rate and the outage constraint - for single-antenna point-to-point transmission in wireless ad hoc networks. In contrast to most existing work, our results explicitly account for the effects of channel estimation. We first derive a new outage probability expression, from which we completely characterize the feasible range of effective per-node data rate and outage constraint pairs which yield a positive transmission capacity, and derive an exact expression for the transmission capacity in such cases. We then proceed to optimize the transmission capacity under different assumptions, yielding considerable new insight. First, assuming that all nodes place a stringent outage constraint, the optimal pilot-training length is derived and this is shown to increase with the frame length according to a square root law. Consequently, for a sufficiently long coherence interval, we show that there is a negligible loss in transmission capacity when using this optimal pilot-training length. Second, we show that if nodes place a constraint on their required effective data rate, then the outage constraint yielding the maximum transmission capacity is quite large. Moreover, this result demonstrates that, from an overall network perspective, it is preferable to operate with a higher total data rate (aggregated across all nodes) at the expense of a lower reliability.

Energy-efficient cooperative beamforming in clustered wireless networks

Recently, due to the growing concern over the ever-increasing energy consumption, much attention has been given to the energy-efficient design of wireless communication systems. Various strategies for improving the energy efficiency, which is defined as the transmitted bits per total energy consumed (in bits/Joule), have been proposed. In this paper, we analyze the energy efficiency of clustered cooperative beamforming where distributed relay nodes construct a virtual Multiple-Input Single-Output beamforming system with a maximum transmit power constraint, and compare its performance with that of direct communications. All the energy consumption overheads incurred are taken into account in the energy efficiency analysis assuming a constant circuit-power consumption model. We then study the number of relay nodes that maximizes the efficiency for a given outage constraint. In addition, we propose a mode switching algorithm which optimally chooses between using cooperative beamforming or direct communications for transmission. We show that cooperative beamforming significantly outperforms direct communications in energy efficiency, as well as in spectral efficiency, even though a much larger amount of circuit power is consumed.

Joint power and rate allocation for spectrum sharing cognitive radio multicast networks under service outage constraint

This letter considers a downlink spectrum sharing cognitive radio (CR) multicast network coexisting with a primary network. The problem of joint power and rate allocation to maximize the average sum rate is studied. In this regard, a joint power and rate allocation scheme is proposed, where the allocated rate can be higher than the lowest rate of all the secondary users (SUs) within the same group, which is different from the conventional multicast transmission scheme. To guarantee the quality of service (QoS) of the SU, the service outage probability defined as the probability that the maximum achievable rate of the SU is lower than the rate of the group, is constrained to be under a certain threshold, which is termed as the service outage constraint. The numerical results show that the proposed scheme provides significant improvement over the conventional scheme in terms of average sum rate.

Cross-Layer Design of Congestion Control and Power Control in Fast-Fading Wireless Networks

We study the cross-layer design of congestion control and power allocation with outage constraint in an interference-limited multihop wireless networks. Using a complete-convexification method, we first propose a message-passing distributed algorithm that can attain the global optimal source rate and link power allocation. Despite the attractiveness of its optimality, this algorithm requires larger message size than that of the conventional scheme, which increases network overheads. Using the bounds on outage probability, we map the outage constraint to an SIR constraint and continue developing a practical near-optimal distributed algorithm requiring only local SIR measurement at link receivers to limit the size of the message. Due to the complicated complete-convexification method, however the congestion control of both algorithms no longer preserves the existing TCP stack. To take into account the TCP stack preserving property, we propose the third algorithm using a successive convex approximation method to iteratively transform the original nonconvex problem into approximated convex problems, then the global optimal solution can converge distributively with message-passing. Thanks to the tightness of the bounds and successive approximations, numerical results show that the gap between three algorithms is almost indistinguishable. Despite the same type of the complete-convexification method, the numerical comparison shows that the second near-optimal scheme has a faster convergence rate than that of the first optimal one, which make the near-optimal scheme more favorable and applicable in practice. Meanwhile, the third optimal scheme also has a faster convergence rate than that of a previous work using logarithm successive approximation method.

Robust Power Control under Channel Uncertainty for Cognitive Radios with Sensing Delays

We develop robust power control strategies for cognitive radios in the presence of sensing delay and model parameter uncertainty. We use a discrete-time Markov chain (DTMC) to characterize the primary users' (PU) dynamics as well as the fading channel. The power control problem is formulated as a Markov decision process (MDP) problem, which can be optimally solved by dynamic programming. However, due to the time-varying nature of the wireless channel and the spectrum sensing overhead, typically only the delayed sensing results are available at any time. The delay in spectrum sensing, if not properly accounted for, could significantly deteriorate the power control performance. Furthermore, the false sensing data and limited feedback cause noisy estimate of the transition probability matrix, leading to further performance degradation of the power control and channel outage. We first propose power control schemes based on a delayed MDP formulation, that account for all possible current channel state based on the delayed channel state. In addition, we propose an outage constraint to protect PU transmissions and properly manage channel outage. We then propose a robust power control framework that optimizes the worst-case system performance. Extensive simulation results are provided to demonstrate the effectiveness of the proposed power control algorithms.

Outage-based design of robust Tomlinson–Harashima transceivers for the MISO downlink with QoS requirements

We consider a broadcast channel in which the base station is equipped with multiple antennas and each user has a single antenna, and we study the design of transceivers based on Tomlinson–Harashima precoders with probabilistic quality of service (QoS) requirements for each user, in scenarios with uncertain channel state information (CSI) at the transmitter. Each user's QoS requirement is specified as a constraint on the maximum allowed outage probability of the receiver's mean square error (MSE) with respect to a specified target MSE, and we demonstrate that these outage constraints are associated with constraints on the outage of the received signal-to-interference-plus-noise-ratio (SINR). We consider four different stochastic models for the channel uncertainty, and we design the downlink transceiver so as to minimize the total transmitted power subject to the satisfaction of the probabilistic QoS constraints. We present three conservative approaches to solving the resulting chance constrained optimization problems. These approaches are based on efficiently solvable deterministic convex design formulations that guarantee the satisfaction of the probabilistic QoS constraints. We also demonstrate how to apply these approaches in order to obtain computationally efficient solutions to some related design problems. Our simulations indicate that the proposed methods can significantly expand the range of QoS requirements that can be satisfied in the presence of uncertainty in the CSI.

Service-Outage Capacity Maximization in Cognitive Radio for Parallel Fading Channels

This paper focuses on a cognitive radio network consisting of a secondary user (SU) equipped with orthogonal frequency-division multiplexing (OFDM) technology able to access N randomly fading frequency bands for transmitting delay-insensitive (e.g. data) as well as delay-sensitive (e.g. voice or video) data. Each band is licensed to a distinct delay-sensitive primary user (PU) interested in meeting a minimum rate guarantee for delay-sensitive services with a maximum allowable primary outage probability or a primary outage constraint (POC) . Typically, a PU is oblivious to the SU's existence and has its own power policy based on the channel side information (CSI) of its direct gain between the PU transmitter and the PU receiver only. Under the assumption that the SU knows PUs' power policies and CSI of the entire network, we solve the SU's ergodic capacity maximization problem subject to SU's average transmit power and outage probability constraints (SOC) and all POCs or the so-called service-outage based capacity maximization for SU with POCs. We use a rigorous probabilistic power allocation technique that allows us to derive optimal power policies applicable to both continuous and discrete fading channels. Also, a suboptimal power control policy is proposed in order to avoid the high computational complexity of the optimal policy when N is large. Numerical results are presented to illustrate the performance of the power allocation algorithms.

A Unified Framework for the Ergodic Capacity of Spectrum Sharing Cognitive Radio Systems

We consider a spectrum sharing communication scenario in which a primary and a secondary users are communicating, simultaneously, with their respective destinations using the same frequency carrier. Both optimal power profile and ergodic capacity are derived for fading channels, under an average transmit power and an instantaneous interference outage constraints. Unlike previous studies, we assume that the secondary user has a noisy version of the cross link and the secondary link Channel State Information (CSI). After deriving the capacity in this case, we provide an ergodic capacity generalization, through a unified expression, that encompasses several previously studied spectrum sharing settings. In addition, we provide an asymptotic capacity analysis at high and low signal-to-noise ratio (SNR). Numerical results, applied for independent Rayleigh fading channels, show that at low SNR regime, only the secondary channel estimation matters with no effect of the cross link on the capacity; whereas at high SNR regime, the capacity is rather driven by the cross link CSI. Furthermore, a practical on-off power allocation scheme is proposed and is shown, through numerical results, to achieve the full capacity at high and low SNR

Coordinated Beamforming for Multiuser MISO Interference Channel Under Rate Outage Constraints

This paper studies the coordinated beamforming design problem for the multiple-input single-output (MISO) interference channel, assuming only channel distribution information (CDI) at the transmitters. Under a given requirement on the rate outage probability for receivers, we aim to maximize the system utility (e.g., the weighted sum rate, weighted geometric mean rate, and the weighed harmonic mean rate) subject to the rate outage constraints and individual power constraints. The outage constraints, however, lead to a complicated, nonconvex structure for the considered beamforming design problem and make the optimization problem difficult to handle. {Although} this nonconvex optimization problem can be solved in an exhaustive search manner, this brute-force approach is only feasible when the number of transmitter-receiver pairs is small. For a system with a large number of transmitter-receiver pairs, computationally efficient alternatives are necessary. The focus of this paper is hence on the design of such efficient approximation methods. In particular, by employing semidefinite relaxation (SDR) and first-order approximation techniques, we propose an efficient successive convex approximation (SCA) algorithm that provides high-quality approximate beamforming solutions via solving a sequence of convex approximation problems. The solution thus obtained is further shown to be a stationary point for the SDR of the original outage constrained beamforming design problem. {Furthermore}, we propose a distributed SCA algorithm where each transmitter optimizes its own beamformer using local CDI and information obtained from limited message exchange with the other transmitters. Our simulation results demonstrate that the proposed SCA algorithm and its distributed counterpart indeed converge, and near-optimal performance can be achieved for all the considered system utilities.

Performance analysis for buffer‐aided communication over block Rayleigh fading channels: queue length distribution, overflow probability, and ε‐overflow rate

ABSTRACTIn this paper, we consider information transmission over a block Rayleigh fading channel, where a finite size buffer is employed to match the source traffic with the channel service capability. Given the buffer size, the transmission capability of a block fading Rayleigh channel is characterized from two aspects: (i) the buffer behavior when the input traffic rate is constant; and (ii) the traffic rate that can be supported by the channel for a given overflow probability constraint. For the first problem, the stationary distribution of the queue length in the buffer is derived by discretizing the queue length using a uniform quantization strategy. It is also shown that the overflow probability of the finite size buffer decreases exponentially with buffer size. An explicit upper bound on the overflow probability is also given. For the second one, a new concept of ε‐overflow rate is proposed to measure the transmission capability of a block fading channel under overflow probability constraints. It will be shown that the ε‐overflow rate is larger than the ε‐outage capacity under the same outage constraint and will meet the great gap between outage capacity and ergodic capacity as the overflow probability constraint varies. Copyright © 2012 John Wiley & Sons, Ltd.

Capacity Maximization and Transmission Rates Optimization for Relay Assisted Wireless Multicast

In this letter, we maximize the multicast capacity of a cellular system with dedicated decode-and-forward (DF) relays, by jointly optimizing transmission data rates of the base station (BS) and the relays subject to an average outage constraint in Rayleigh fading channels. The optimal transmission rates of the BS and relays and the optimal relay locations are obtained based on an outage probability analysis for the relay-assisted multicast. Numerical results show that relay-aided multicast significantly outperforms direct multicast, and the best transmission strategy is for the BS and dedicated relays to transmit at the same rate.

WBAN 채널 특성과 전송 효율 분석

본 논문에서는 wireless body area network(WBAN) 채널을 분석하기 위해 실제 채널을 측정하고, 그것의 통계적 특성들을 조사하였다. On-/off-body 채널에서, 인체의 움직임을 고려하기 위해 대표적인 움직임들을 같이 측정하여 그 분석 결과들을 비교하였다. 또한, 세 종류의 신호 전송 기법을 제한된 Outage 확률을 가질 때 최소 소비 전력을 분석하여, 이론적인 총 전력 소비를 계산하였다. 그리고 채널 측정 데이터들을 통해 이론과 실제의 차이를 분석하였다. 본 논문의 결과로 협력 통신을 통하여 전송 효율을 높일 수 있음을 알 수 있으며, 센서 노드의 부착 위치와 움직임이 신호 전송 전력에 어떠한 영향을 미치는지 확인할 수 있다. This paper presents the real channel measurements and investigates their statistical characterization in wireless body area network(WBAN). In on-/off body channel, the measurements are performed with some representative human movements for considering human movements. Moreover, three signal transmission schemes with outage constraint are studied for getting total power consumption in each transmission scheme. Using the real channel measurements, between theoretical and realistic simulation are compared. This paper shows that power efficiency is improved through cooperative communication, and how much position of sensor node and human movement affect signal transmission power.

Cross-Layer Optimization for Congestion and Power Control in OFDM-Based Multi-Hop Cognitive Radio Networks

Efficient and fair power allocation associated with congestion control in orthogonal frequency division multiplexing (OFDM)-based multi-hop cognitive radio networks (CRNs) is a challenging and complicated problem. In this paper, we consider their mutual relationship through a cross-layer optimization design that addresses both aggregate utility maximization and energy consumption minimization. By introducing the unique outage constraint of primary user (PU) protection, the joint congestion control and power control (JCPC) formulation is shown to be a nonlinear non-convex optimization problem. Using dual decomposition approach, we first propose a distributed algorithm that can attain the optimal solution via message passing while maintaining the architectural modularity between the layers. Next, we develop a suboptimal algorithm using a new heuristic method to alleviate the overhead burden of the first solution. Finally, the numerical results confirm that the OFDM-based multi-hop CRNs can optimally exploit the spectrum opportunity if the PU outage probability is kept below the target.

Power allocation policies with full and partial inter-system channel state information for cognitive radio networks

This paper investigates several power allocation policies in orthogonal frequency division multiplexing -based cognitive radio networks under the different availability of inter-system channel state information (CSI) and the different capability of licensed primary users (PUs). Specifically, we deal with two types of PUs having different capabilities: a dumb (peak interference-power tolerable) PU and a more sophisticated (average interference-power tolerable) PU. For such PU models, we first formulate two optimization problems that maximize the capacity of unlicensed secondary user (SU) while maintaining the quality of service of PU under the assumption that both intra- and inter-system CSI are fully available. However, due to loose cooperation between SU and PU, it may be difficult or even infeasible for SU to obtain the full inter-system CSI. Thus, under the partial inter-system CSI setting, we also formulate another two optimization problems by introducing interference-power outage constraints. We propose optimal and efficient suboptimal power allocation policies for these four problems. Extensive numerical results demonstrate that the spectral efficiency achieved by SU with partial inter-system CSI is less than half of what is achieved with full inter-system CSI within a reasonable range of outage probability (e.g., less than 10 %). Further, it is shown that the average interference-power tolerable PU can help to increase the saturated spectral efficiency of SU by about 20 and 50 % in both cases of full and partial inter-system CSI, respectively.

Ergodic Capacity of Cognitive Radio Under Imperfect Channel-State Information

A spectrum-sharing communication system where the secondary user is aware of the instantaneous channel-state information (CSI) of the secondary link but knows only the statistics and an estimated version of the secondary transmitter-primary receiver link is investigated. The optimum power profile and the ergodic capacity of the secondary link are derived for general fading channels [with a continuous probability density function (pdf)] under the average and peak transmit power constraints and with respect to the following two different interference constraints: 1) an interference outage constraint and 2) a signal-to-interference outage constraint. When applied to Rayleigh fading channels, our results show, for example, that the interference constraint is harmful at the high-power regime, because the capacity does not increase with the power, whereas at the low-power regime, it has a marginal impact and no-interference performance, which corresponds to the ergodic capacity under average or peak transmit power constraint in the absence of the primary user, may be achieved.

Transmission strategies with interference coordination in spectrum sharing cognitive radio networks under outage probability constraint

In this article, we consider a cognitive radio (CR) communication system based on spectrum sharing schemes, where we have a secondary user (SU) link with multiple transmitting antennas and a single receiving antenna, coexisting with a primary user (PU) link with a single receiving antenna. At the SU transmitter (SU-Tx), the channel state information (CSI) of the SU link is assumed to be perfectly known; while the interference channel from the SU-Tx to the PU receiver (PU-Rx) is not perfectly known due to less cooperation between the SU and the PU. As such, the SU-Tx is only assumed to know that the interference channel gain can randomly take values from a finite set with certain probabilities. Considering a SU transmit power constraint, our design objective is to determine the transmit covariance matrix that maximizes the SU rate, while we protect the PU by enforcing both a PU average interference constraint and a PU outage probability constraint. This problem is first formulated as a non-convex optimization problem with a non-explicit probabilistic constraint, which is then approximated as a mixed binary integer programming (MBIP) problem and solved with the branch and bound (BB) algorithm. The complexity of the BB algorithm is analyzed and numerical results are presented to validate the effectiveness of the proposed algorithm. A key result proved in the article is that the rank of the optimal transmit covariance matrix is one, i.e., CR beamforming is optimal under PU outage constraints. Finally, a heuristic algorithm is proposed to provide a suboptimal solution to our MBIP problem by efficiently (in polynomial time) solving a particularly-constructed convex problem.

Mean Value-Based Power Allocation without Instantaneous CSI Feedback in Spectrum Sharing Systems

In this paper, we investigate a power allocation method without feedback of the instantaneous channel gain between a secondary transmitter (ST) and a primary receiver (PR) in spectrum sharing systems where channel information between the ST and the PR is outdated. We propose a mean value-based power allocation scheme (MVPA), which uses only the mean value of the channel gain of the ST-PR link. The proposed MVPA satisfies the interference outage constraint at the PR without feedback of the instantaneous channel information, which enables MVPA to reduce feedback burden. We also derive the ergodic capacity based on MVPA in closed-form and compare the ergodic capacity based on MVPA with that of a power allocation method using the outdated channel information instantaneously. Through the comparison, we convincingly demonstrate that MVPA without feedback of instantaneous channel information provides more reliable and superior capacity performance by reducing capacity loss from which the power allocation method using the outdated channel information severely suffers.