Optimal power allocation for cognitive radio under interference outage constraint

Cognitive radio is able to share the spectrum with primary licensed user, which greatly improves the spectrum efficiency. We study the optimal power allocation for cognitive radio to maximize its ergodic capacity under interference outage constraint. An optimal power allocation scheme for the secondary user with complete channel state information is proposed and its approximation is presented in closed form in Rayleigh fading channels. When the complete channel state information is not available, a more practical transmitter-side joint access ratio and transmit power constraint is proposed. The new constraint guarantees the same impact on interference outage probability at primary user receiver. Both the optimal power allocation and transmit rate under the new constraint are presented in closed form. Simulation results evaluate the performance of proposed power allocation schemes and verify our analysis.     

On the Impacts of Channel Estimation Errors and Feedback Delay on the Ergodic Capacity for Spectrum Sharing Cognitive Radio

Spectrum sharing cognitive radio aims to improve the spectrum efficiency via sharing the spectrum band licensed to the primary user (PU) with the secondary user (SU) concurrently provided that the interference caused by the SU to the PU is limited. The channel state information (CSI) between the secondary transmitter (STx) and the primary receiver (PRx) is used by the STx to calculate the appropriate transmit power to limit the interference. We assume that this CSI is not only having channel estimation errors but also outdated due to feedback delay, which is different from existing studies. We derive closed-form expressions for the ergodic capacities of the SU with this imperfect CSI under the average interference power (AIP) constraint and the peak interference power (PIP) constraint. Illustrative results are presented to show the effects of the imperfect CSI. It is shown that the ergodic capacity of the SU is robust to the channel estimation errors and feedback delay under high feedback delay. It is also shown that decreasing the distance between STx and secondary receiver (SRx) or increasing the distance between STx and PRx can mitigate the impact of the imperfect CSI and significantly increase the ergodic capacity of the SU.     

Secrecy outage analysis in a hybrid cognitive relay network with energy harvesting

In this paper, we investigate the physical layer security of a hybrid cognitive relay network using an energy harvesting relay in presence of an eavesdropper. In the hybrid scheme, a secondary user (SU) as well as a cognitive relay works either in underlay or in overlay mode. In underlay, the transmit power of the SU as well as the relay is limited by the maximum acceptable interference at primary user (PU) receiver as required by an outage constraint of PU, a quality of service for PU. The secondary network consists of a decode and forward relay that harvests energy from radio frequency signal of secondary transmitter as well as PU transmitter to assist the SU in forwarding the information signal to the destination. A time switching relaying protocol is used at the relay. We evaluate the secrecy outage probability of secondary relay network assuming that channel state information of the interfering links from both the SU and relay transmitter to PU receiver is imperfect. Our results reveal the impact of imperfect channel state information, energy harvesting time, tolerable interference threshold, and PU outage constraint on the secrecy outage probability of SU.     

感知频谱共享下的多天线功率优化分配算法研究

本文构建了一种在感知结果下具有多天线次用户的频谱共享模型,该模型由单入单出主用户对和多入单出认知用户对构成。当认知用户感知到主用户占用信道时,主用户向认知用户发送Message信息,使得认知用户发射端能够得知主用户对干扰总功率的限制要求,通过自适应地调整认知用户发射机的发射功率,以保证其对主用户不造成有害干扰;如果主用户未占用信道,认知用户立刻以最大发射功率占用信道。并分别在主用户存在和不存在两种情况下,优化认知用户发射机各天线的发射功率来最大化系统总的数据传输率。最后,通过数值仿真来验证推导出的功率分配策略,并对其进行分析和讨论。仿真结果表明:相比于机会频谱接入（Opportunistic Spectrum Access, OSA）和基于感知的频谱共享（Sensing-based spectrum sensing）模式,推导的功率分配策略在提出的模型中可以获得更高的信息传输率。      

Performance of cognitive relay network with energy harvesting relay under imperfect CSI

This paper evaluates the performance of an underlay cognitive relay network under imperfect channel state information (CSI) where a secondary user (SU) transmits using a secondary relay (SR) based on decode and forward scheme. The outage probability (OP) of SU is investigated in a scenario where the decode and forward relay harvests energy from radio frequency signal of SU. The relay uses a fraction of time for harvesting in time switching–based relaying (TSR) while a fraction of received power is used for harvesting in power splitting–based relaying (PSR) scheme. The SU and relay control their transmit power using a scaling factor, based on CSI of the interfering links (ie, links from SU transmitter and SR to the primary user [PU] receiver) to protect the quality of service of PU. The available CSI at the SU and SR are imperfect due to practical limitation. Analytical expressions of the OP are derived for TSR‐ and PSR‐based schemes. The impact of harvesting time, power splitting ratio, imperfect CSI, PU outage constraint and interference threshold on the OP of the SU network, and average transmit power of SR is indicated. Further, the impact of multiple SRs is also shown.     

Optimal precoder design for non‐regenerative multiple‐input multiple‐output cognitive relay systems with perfect and imperfect channel state information

This paper studies optimal precoder design for non‐regenerative multiple‐input multiple‐output (MIMO) cognitive relay systems, where the secondary user (SU) and relay station (RS) share the same spectrum with the primary user (PU). We aim to maximize the system capacity subject to the transmit power constraints at the SU transmitter (SU‐Tx) and RS, and the interference power constraint at the PU. We jointly optimize precoders for the SU‐Tx and RS with perfect and imperfect channel state information (CSI) between the SU‐Tx/RS and PU, where our design approach is based on the alternate optimization method. With perfect CSI, we derive the optimal structures of the RS and SU‐Tx precoding matrices and develop the gradient projection algorithm to find numerical solution of the RS precoder. Under imperfect CSI, we derive equivalent conditions for the interference power constraints and convert the robust SU‐Tx precoder optimization into the form of semi‐definite programming. For the robust RS precoder optimization, we relax the interference power constraint related with the RS precoder to be convex by using an upper bound and apply the gradient projection algorithm to deal with it. Simulation results demonstrate the effectiveness of the proposed schemes. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Opportunistic power allocation strategies and fair subcarrier allocation in OFDM-based cognitive radio networks

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user’s QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user’s tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.     

Service outage based power and rate allocation for parallel fading channels

The service outage based allocation problem explores variable-rate transmission schemes and combines the concepts of ergodic capacity and outage capacity for fading channels. A service outage occurs when the transmission rate is below a given basic rate r/sub o/. The allocation problem is to maximize the expected rate subject to the average power constraint and the constraint that the outage probability is less than /spl epsi/. A general class of probabilistic power allocation schemes is considered for an M-parallel fading channel model. The optimum power allocation scheme is derived and shown to be deterministic except at channel states of a boundary set. The resulting service outage achievable rate ranges from 1-/spl epsi/ of the outage capacity up to the ergodic capacity with increasing average power. Two near-optimum schemes are also derived by exploiting the fact that the outage probability is usually small. The second near-optimum scheme significantly reduces the computational complexity of the optimum solution; moreover, it has a simple structure for the implementation of transmission of mixed real-time and non-real-time services.     

Performance analysis of an opportunistic multi‐user cognitive network with multiple primary users

Consider a multi‐user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami‐m fading. The interference channel between the secondary users (SUs) and the primary users is assumed to have Rayleigh fading. A power allocation based on the instantaneous channel state information is derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the moment‐generating function, outage performance, symbol error rate performance, and the ergodic capacity are derived. Numerical results corroborate the derived analytical results. The performance is also studied in the asymptotic regimes, and the generalized diversity gain of this scheduling scheme is derived. It is shown that when the interference channel is deeply faded and the peak transmit power constraint is relaxed, the scheduling scheme achieves full diversity and that increasing the number of primary users does not impact the diversity order. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal transmission strategies and impact of correlation in multiantenna systems with different types of channel state information

We study the optimal transmission strategy of a multiple-input single-output (MISO) wireless communication link. The receiver has perfect channel state information (CSI), while the transmitter has different types of CSI, i.e., either perfect CSI, or no CSI, or long-term knowledge of the channel covariance matrix. For the case in which the transmitter knows the channel covariance matrix, it was recently shown that the optimal eigenvectors of the transmit covariance matrix correspond with the eigenvectors of the channel covariance matrix. However, the optimal eigenvalues are difficult to compute. We derive a characterization of the optimum power allocation. Furthermore, we apply this result to provide an efficient algorithm which computes the optimum power allocation. In addition to this, we analyze the impact of correlation on the ergodic capacity of the MISO system with different CSI schemes. At first, we justify the belief that equal power allocation is optimal if the transmitter is uninformed and the transmit antennas are correlated. Next, we show that the ergodic capacity with perfect CSI and without CSI at the transmitter is Schur-concave, i.e., the more correlated the transmit antennas are, the less capacity is achievable. In addition, we show that the ergodic capacity with covariance knowledge at the transmitter is Schur-convex with respect to the correlation properties. These results completely characterize the impact of correlation on the ergodic capacity in MISO systems. Furthermore, the capacity loss or gain due to correlation is quantified. For no CSI and perfect CSI at the transmitter, the capacity loss due to correlation is bounded by some small constant, whereas the capacity gain due to correlation grows unbounded with the number of transmit antennas in the case in which transmitter knows the channel covariance matrix. Finally, we illustrate all theoretical results by numerical simulations.     

Ergodic capacity of multiuser scheduling in cognitive radio networks: analysis and comparison

This paper analyzes the ergodic capacity of secondary point‐to‐multipoint communications under the outage constraint of multiple primary user receivers (PU‐Rxs) and the secondary user (SU) maximum transmit power limit. We first derive analytical expressions of the ergodic capacity for three scheduling schemes, that is, round robin, Max‐signal‐to‐interference‐plus‐noise‐ratio (Max‐SINR) and Min‐SINR, and compare their performance. Numerical examples show that when the number of SU receivers (SU‐Rxs) increases in the presence of a single PU‐Rx and at high SINR, the Min‐SINR outperforms the Max‐SINR scheme. As the number of PU‐Rxs increases, the Max‐SINR performs better than the Min‐SINR scheduling. When the number of SU‐Rxs becomes large, the system capacity is enhanced but so is the feedback load. To exploit the Max‐SINR transmission while reducing the feedback load, we assume a threshold based on the channel quality where the SU‐Rxs with the instantaneous SINR above the threshold participate in the Max‐SINR scheduling; otherwise, an SU‐Rx is selected randomly. Then, an analytical expression of the average capacity is derived. Numerical results illustrate that the capacity with limited feedback is approximately the same as for the case of Max‐SINR with full feedback when the SU threshold for feedback condition is set to low and medium values. Copyright © 2016 John Wiley & Sons, Ltd.     

Outage capacities and optimal power allocation for fading multiple-access channels

We derive the outage capacity region of an M-user fading multiple-access channel (MAC) under the assumption that both the transmitters and the receiver have perfect channel side information (CSI). The outage capacity region is implicitly obtained by deriving the outage probability region for a given rate vector. Given a required rate and average power constraint for each user, we find a successive decoding strategy and a power allocation policy that achieves points on the boundary of the outage probability region. We discuss the scenario where an outage must be declared simultaneously for all users (common outage) and when outages can be declared individually (individual outage) for each user.     

Communication with causal CSI and controlled information outage

In this letter, a Rayleigh block-fading (BF) channel, subject to an information outage probability constraint, is considered. The transmitter is assumed to have causal knowledge of the channel state information (CSI), which is exploited to intelligently allocate the power over the blocks (and hence vary the channel mutual information) to minimize the average transmitted power per block for satisfying the outage probability constraint for a given target code-rate. We first show that the optimal solution to this problem can be obtained by solving the reverse problem of minimizing the outage probability for a range of long-term power constraints through repeated uses of dynamic programming (DP), which is nevertheless prohibitively complex. Then, we develop a suboptimal allocation algorithm which still uses DP to exploit the CSI causality but at a much reduced complexity. A performance lower-bound is further derived, which permits us to see that the proposed algorithm is near-optimal, especially in the small outage probability regime. A scheme called equal-outage-probability per block (EOPPB) which compromises the performance further for reducing the complexity is also devised. To compare the methods, we evaluate both analytically and numerically their complexities and performance. The results are finally generalized to multipleinput multiple-output (MIMO) BF channels.     

Investigation on outage capacity of spectrum sharing system using CSI and SSI under received power constraints

In this paper, we have investigated the outage capacity of secondary user for opportunistic spectrum sharing under the joint peak and average received power constraints for Rayleigh fading environment. Under this communication scenario, on detecting the licensed primary user inactive, the secondary unlicensed users transmit data/information in the licensed frequency band such that no or minimum interference may be experienced by the primary user. The soft sensing information (SSI) and secondary user’s channel state information is used to obtain the closed form expressions for the ergodic and outage capacity using truncated channel inversion with fixed rate technique under the joint peak and average received power constraints. Numerically simulated results are provided to demonstrate the improvement in outage capacity of secondary user under the proposed spectrum sharing scheme. Moreover, the proposed scheme is also compared with other conventional spectrum sharing schemes to illustrate the benefits of SSI and received power constraints on the outage capacity of secondary user.

     

过时CSI下全双工中继辅助D2D网络的物理层安全

中继辅助终端直通（devicetodevice,D2D）网络通过与蜂窝网络共享频谱提高D2D用户的频谱效率和蜂窝用户（cellular user,CU）的物理层安全性。为进一步改善其性能,可以在基站和D2D链路的中继节点采用天线选择以及在中继节点采用全双工技术。然而,由于存在反馈时延和移动性,用于蜂窝链路和所有D2D链路天线选择的信道状态信息（channelstateinformation,CSI）均可能是过时的,针对该场景下的物理层安全性和可靠性问题,提出一种主动窃听和过时CSI场景下基站和中继节点均采用发射天线选择的全双工中继辅助D2D网络安全模型,推导CU的中断概率、遍历容量、非零安全容量概率、安全中断概率、渐近安全中断概率的解析表达式。数值计算与仿真结果均表明,基站发射天线数、中继干扰天线数越多,CU的安全性能越好;过时的CSI会降低CU的中断性能和安全性能。     

Joint Beamforming and Power Allocation for Cognitive MIMO Systems Under Imperfect CSI Based on Game Theory

The problem of joint beamforming and power allocation for cognitive multi-input multi-output systems is studied via game theory. The objective is to maximize the sum utility of secondary users (SUs) subject to the primary user (PU) interference constraint, the transmission power constraint of SUs, and the signal-to-interference-plus-noise ratio (SINR) constraint of each SU. In our earlier work, the problem was formulated as a non-cooperative game under the assumption of perfect channel state information (CSI). Nash equilibrium (NE) is considered as the solution of this game. A distributed algorithm is proposed which can converge to the NE. Due to the limited cooperation between the secondary base station (SBS) and the PU, imperfect CSI between the SBS and the PU is further considered in this work. The problem is formulated as a robust game. As it is difficult to solve the optimization problem in this case, existence of the NE cannot be analyzed. Therefore, convergence property of the sum utility of SUs will be illustrated numerically. Simulation results show that under perfect CSI the proposed algorithm can converge to a locally optimal pair of transmission power vector and beamforming vector, while under imperfect CSI the sum utility of SUs converges with the increase of the transmission power constraint of SUs.     

On the Ergodic Capacity and Energy Efficiency for Fading MIMO NOMA Systems

Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access techniques for 5G networks due to its superior spectral efficiency (SE). Previous research mainly focus on the design to improve the SE performance with instantaneous channel state information (CSI). In this paper, we consider the fading MIMO channels with only statistical CSI at the transmitter, and explore the potential gains of MIMO NOMA scheme in terms of both ergodic capacity and energy efficiency (EE). The ergodic capacity maximization problem is first studied for the fading multiple-input multiple-output (MIMO) NOMA systems. We derive the optimal input covariance structure and propose both optimal and low complexity suboptimal power allocation schemes to maximize the ergodic capacity of MIMO NOMA system. For the EE maximization, the optimization problem is formulated to maximize the system EE (defined by ergodic capacity under unit power consumption) under the total transmit power constraint and the minimum rate constraint of the weak user. By transforming the EE maximization problem into an equivalent one-dimensional optimization problem, the optimal power allocation for EE design is proposed. To further reduce the computation complexity, a near-optimal solution based on golden section search and suboptimal closed form solution are proposed as well. Numerical results show that the proposed NOMA schemes significantly outperform the traditional orthogonal multiple access scheme with traditional orthogonal multiple access transmission in terms of both SE and EE.     

Energy‐efficient outage‐constrained power allocation based on statistical channel knowledge for dual‐hop cognitive relay networks

This paper investigates the power allocation problem in decode‐and‐forward cognitive dual‐hop systems over Rayleigh fading channels. In order to optimize the performance of the secondary network in terms of power consumption, an outage‐constrained power allocation scheme is proposed. The secondary nodes adjust their transmit power subject to an average interference constraint at the primary receiver and an outage probability constraint for the secondary receivers while having only statistical channel knowledge with respect to the primary nodes. We compare this approach with a power allocation scheme based on instantaneous channel state information under a peak interference constraint. Analytical and numerical results show that the proposed approach, without requiring the constant interchange of channel state information, can achieve a similar performance in terms of outage probability as that of power allocation based on instantaneous channel knowledge. Moreover, the transmit power allocated by the proposed approach is considerably smaller than the power allocated by the method based on instantaneous channel knowledge in more than 50% of the time. Copyright © 2015 John Wiley & Sons, Ltd.     

Routing Algorithm for Maximizing Lifetime of Wireless Sensor Network for Broadcast Transmission

This paper addresses the problem of optimal resource allocation in a multi-hop cognitive radio networks. The objective of the present work is to search for the shortest possible path from the source to the destination and explores the scope of the Bellman–Ford and the Dijkstra’s algorithms due to their low runtime complexity and ease of implementation in routing. Searching for the shortest path focuses on minimization to the outage probability, while satisfying simultaneously the limits of the total transmit power and the interference threshold to the primary user (PU). Fuzzy c-means clustering is used to speed up the route selection process for both the routing algorithms. Network lifetime is also studied for both the algorithms considering the link failure situation. Simulation results show that the proposed scheme not only minimizes the outage probability over the existing power allocation strategies but also reduces interference to the PU. Results also show that network lifetime is increased and faster route selection is possible.