Average Interference Power Constraint Research Articles

Analysis of FD-NOMA Cognitive Relay System With Interference From Primary User Under Maximum Average Interference Power Constraint

Analysis of FD-NOMA Cognitive Relay System With Interference From Primary User Under Maximum Average Interference Power Constraint

Energy‐Efficient Outage Capacity in Sensing‐Based Spectrum Sharing Cognitive Radio Networks

Energy efficiency (EE) is an important metric for a Cognitive radio network (CRN). We focus on the EE maximization problem in a sensing-based spectrum sharing CRN for delay-sensitive applications. With the aid of one-dimension exhaustive search, fractional programming and Lagrange duality method, two energy-efficient optimal sensing time and power allocation policies are derived with the consideration of Average/Peak transmit power (ATP/PTP) constraints and Average interference power (AIP) constraints, respectively. Simulation results show that the proposed policies can achieve higher EE compared to the conventional spectrum sharing schemes.

Delay analysis for cognitive radio networks

In this article, we derive the waiting time and total delay of packets for cooperative cognitive radio networks. In the primary network, there are primary transmitter (PT) and receiver (PR). In the secondary network, there are a source, M relays and a destination. Our results are valid for any number of relays and different relaying protocols: opportunistic amplify and forward (AF), partial AF, reactive AF and reactive DF. The analysis is carried out for nodes with fixed and adaptive transmit power. For fixed transmit power (FTP), we cannot guarantee that interference to PR is less than threshold T. Therefore, some relays are inactive because they generate harmful interference to PR. For adaptive transmit power (ATP), the power of a relay node is fixed so that peak interference power (PIP) or average interference power (AIP) constraints are verified. We also take into account interference from the primary transmitter (PT) by analyzing the delays based on signal to interference plus noise ratio (SINR). © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Stability and Dynamic Control of Underlay Mobile Edge Networks

This paper studies the stability and dynamic control of underlay mobile edge networks. First, the stability region for a multiuser edge network is obtained under the assumption of full channel state information. This result provides a benchmark figure for comparing performance of the proposed algorithms. Second, a centralized joint flow control and scheduling algorithm is proposed to stabilize the queues of edge devices while respecting the average and instantaneous interference power constraints at the core access point. This algorithm is proven to converge to a utility point arbitrarily close to the maximum achievable utility within the stability region. Finally, more practical implementation issues such as distributed scheduling are examined by designing efficient scheduling algorithms taking advantage of communications diversity. The proposed distributed solutions utilize mini slots for contention resolution and achieve a certain fraction of the utility optimal point. The performance lower bounds for distributed algorithms are determined analytically. The detailed simulation study is performed to pinpoint the cost of distributed control for mobile edge networks with respect to centralized control.

Throughput of Cooperative HARQ protocols for Underlay Cognitive Radio Networks using Adaptive and Fixed Transmit Power

In this paper, we study theoretically and by simulations the throughput of cooperative hybrid automatic repeat request (HARQ) protocols for underlay cognitive radio networks (CRN). Both fixed and adaptive power transmission are studied. Different relay selection techniques with amplify and forward (AF) and decode and forward (DF) relaying are investigated. For fixed transmit power, some relays are not available due to interference constraints. The best relay is selected among the available ones. For adaptive transmit power, all relays adapt their power so that interference to primary receiver is always lower than a predefined threshold T. In this case, all relays will be available for retransmitting the secondary source packet. Both average interference power (AIP) and peak interference power constraints (PIP) are studied. We also analyse the effect of primary interference on secondary throughput.

Energy-Efficient Cooperative Spectrum Sensing With Reporting Errors in Hybrid Spectrum Sharing CRNs

Recently, cooperative spectrum sensing (CSS) in cognitive radio networks has been extensively researched. However, most of the studies mainly focus on maximizing the spectral efficiency while the energy consumption is generally ignored. However, since the secondary users (SUs) are usually battery-powered devices, energy saving is very important. This paper studies the mean energy efficiency (EE) maximization problem of the CSS system using the hybrid spectrum sharing (HSS) scheme. Specifically, the effects of imperfect spectrum sensing and reporting channel errors on the EE are considered. Our goal is to maximize the mean EE of SUs while maintaining the detection accuracy by jointly optimizing the sensing time and the number of cooperative SUs, subject to the SUs' average/peak transmission power constraints (ATPC/PTPC) and minimum data rate constraint, and the average interference power constraint of primary user. To address the non-convexity of the optimization problem, an energy-efficient iterative power allocation algorithm is developed. Simulations compare the achievable mean EE under ATPC/PTPC with three hard combining fusing rules using the HSS scheme and the opportunistic spectrum access (OSA) scheme, respectively; the results show that our proposed HSS scheme can obtain higher mean EE than the conventional OSA scheme and that the EE achieved under ATPC is better than that under PTPC. Moreover, among the three hard combining fusing rules, the Majority rule has the best EE.

Performance Assessment for Cognitive Cooperative Multiple Relays Network (CCMRN) With Imperfect Channel State Information

In the underlay spectrum sharing approach, cognitive radios have limited coverage area to keep interference protection for the licensed users. Multiple cooperative relays have shown benefit for allowing reliable communication with an increase in the radio coverage area. The performance of an underlay cognitive cooperative multiple relays network (CCMRN) is evaluated in case of imperfect channel state information (CSI). In this paper, CCMRN will be treated as a secondary network with multiple decode and forward relays, whereas the secondary user (SU) transmitter will select a single relay from the available set of relays. The relay selection process is based on obtaining maximum end-to-end effective capacity ( $C_{\text {eff}}$ ) as seen by the SU. By assuming cooperation between the licensed primary network and the unlicensed secondary network, the SU and the selective secondary relay can share the spectrum with occupying two orthogonal channels of two different primary users (PUs). According to the average interference power constraint of the PUs, the SU allowed maximum power transmission will be obtained. Network performance is assessed in terms of the SU maximum end-to-end $C_{\text {eff}}$ as well as outage probability ( $P_{\text {out}}$ ). Mathematical expressions for $C_{\text {eff}}$ and $P_{\text {out}}$ are derived for practical multipath Rayleigh faded channel. The analytical results illustrate the effect of the imperfect CSI on the performance metrics with applying various constraints such as available multiple relays group size, statistical delay quality of service, and average interference power.

Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach’s method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint.

Spectral and Energy Efficiency in Cognitive Radio Systems with Unslotted Primary Users and Sensing Uncertainty

This paper studies energy efficiency (EE) and average throughput maximization for cognitive radio systems in the presence of unslotted primary users. It is assumed that primary user activity follows an ON–OFF alternating renewal process. Secondary users first sense the channel possibly with errors in the form of miss detections and false alarms, and then, start the data transmission only if no primary user activity is detected. The secondary user transmission is subject to constraints on collision duration ratio, which is defined as the ratio of average collision duration to transmission duration. In this setting, the optimal power control policy which maximizes the EE of the secondary users or maximizes the average throughput while satisfying a minimum required EE under average/peak transmit power and average interference power constraints is derived. Subsequently, low-complexity algorithms for jointly determining the optimal power level and frame duration are proposed. The impact of probabilities of detection and false alarm, transmit and interference power constraints on the EE, average throughput of the secondary users, optimal transmission power, and the collisions with primary user transmissions are evaluated. In addition, some important properties of the collision duration ratio are investigated. The tradeoff between the EE and average throughput under imperfect sensing decisions and different primary user traffic are further analyzed.

Coupled Detection and Estimation Based Censored Spectrum Sharing in Cognitive Radio Networks

A novel spectrum sharing strategy based on coupled detection and estimation is proposed for cognitive radio networks. The proposed approach is able to tradeoff throughput for reduced interference at the primary user (PU) via censored transmissions. We derive the optimum censoring strategy that maximizes the throughput of the cognitive radio system under an average interference power constraint at the PU. We then extend the proposed framework to jointly optimize the censoring and the power allocation strategies of the secondary user (SU) that maximize the throughput of the secondary network under average transmit power and average interference power constraints. Finally, we provide extensive simulation results to demonstrate the enhanced performance of the proposed censoring based spectrum sharing approach.

Energy-Efficient Resource Allocation for OFDM-Based Cognitive Radio Networks with Imperfect Spectrum Sensing

In this study, energy-efficient (EE) resource allocation in orthogonal frequency division multiplexing-based cognitive radio networks with imperfect spectrum sensing is investigated. We present a new EE model by considering the sensing errors. Optimizing such an EE expression saves valuable resources, such as battery life, by selectively allocating power to underutilized subcarriers, and also achieves EE gain compared with general EE expression. Given that the primary user’s interference tolerance can be defined as either the Peak Interference Power (PIP) constraint or Average Interference Power (AIP) constraint for all subchannels, we compare the EE performance for the two interference power constraints. Finally, we propose an optimal EE resource allocation scheme based on the quasiconcave relation between the EE and transmit power. Simulations show that the new EE design improves EE compared with the conventional EE design, and the EE is higher with AIP constraint than that with PIP constrain under certain interference power.

Capacity in fading environment based on soft sensing information under spectrum sharing constraints

In this paper, the ergodic channel capacity for a secondary user is investigated using soft sensing information about primary user activity in a shared channel under joint peak transmit power and average received interference power constraints for Nakagami-m fading channel. The results of the proposed power adaptation scheme illustrate the effect of communication environment parameters and soft sensing information about primary user activity on the channel capacity of secondary user. In particular, the effect of cross link channel state information to maximize the channel capacity for the power adaptation scheme is emphasized by considering the Lagrangian optimization problem for joint peak transmit power and average interference power constraints. Moreover, the performance of the primary user is also investigated considering the interference of the secondary user to the primary in spectrum sharing environment in terms of transmission rate and average channel capacity.

Multimedia Transmission Over Cognitive Radio Channels Under Sensing Uncertainty

This paper studies the performance of hierarchical modulation-based multimedia transmission in cognitive radio (CR) systems with imperfect channel sensing results under constraints on both transmit and interference power levels. Unequal error protection (UEP) of data transmission using hierarchical quadrature amplitude modulation (HQAM) is considered in which high priority (HP) data is protected more than low priority (LP) data. In this setting, closed-form bit error rate (BER) expressions for HP data and LP data are derived in Nakagami-$m$ fading channels in the presence of sensing errors. Subsequently, the optimal power control that minimizes weighted sum of average BERs of HP bits and LP bits or its upper bound subject to peak/average transmit power and average interference power constraints is derived and a low-complexity power control algorithm is proposed. Power levels are determined in three different scenarios, depending on the availability of perfect channel side information (CSI) of the transmission and interference links, statistical CSI of both links, or perfect CSI of the transmission link and imperfect CSI of the interference link. The impact of imperfect channel sensing decisions on the error rate performance of cognitive transmissions is also evaluated. In addition, tradeoffs between the number of retransmissions, the severity of fading, and peak signal-to-noise ratio (PSNR) quality are analyzed numerically. Moreover, performance comparisons of multimedia transmission with conventional quadrature amplitude modulation (QAM) and HQAM, and the proposed power control strategies are carried out in terms of the received data quality and number of retransmissions.

Ergodic Sum-Rate Maximization for Fading Cognitive Multiple-Access Channels Without Successive Interference Cancelation

In this paper, the ergodic sum rate of a fading cognitive multiple-access channel (C-MAC) is studied, where a secondary network (SN) with multiple secondary users (SUs) transmitting to a secondary base station shares the spectrum band with a primary user (PU). An interference power constraint (IPC) is imposed on the SN to protect the PU. Under such a constraint and the individual transmit power constraint (TPC) imposed on each SU, we investigate the power allocation strategies to maximize the ergodic sum rate of a fading C-MAC without successive interference cancelation (SIC). In particular, this paper considers two types of constraints: 1) average TPC and average IPC and 2) peak TPC and peak IPC. For the first case, it is proved that the optimal power allocation is dynamic time-division multiple access (D-TDMA), which is exactly the same as the optimal power allocation to maximize the ergodic sum rate of the fading C-MAC with SIC under the same constraints. For the second case, it is proved that the optimal solution must be at the extreme points of the feasible region. It is shown that D-TDMA is optimal with high probability when the number of SUs is large. Moreover, we show that when the SUs can be sorted in a certain order, an algorithm with linear complexity can be used to find the optimal power allocation.

Power saving and improving the throughput of spectrum sharing in wideband cognitive radio networks

This paper considers a wideband cognitive radio network which can simultaneously sense multiple narrowband channels and thus aggregate the detected available channels for transmission and proposes a novel cognitive radio system that exhibits improved sensing throughput and can save power consumption of secondary user (SU) compared to the conventional cognitive radio system studied so far. More specifically, under the proposed cognitive radio system, we study the problem of designing the optimal sensing time and power allocation strategy, in order to maximize the ergodic throughput of the proposed cognitive radio system under two different schemes, namely the wideband sensing-based spectrum sharing scheme and the wideband opportunistic spectrum access scheme. In our analysis, besides the average interference power constraint at primary user, the average transmit power constraint of SU is also considered for the two schemes and then a subgradient algorithm is developed to obtain the optimal sensing time and the corresponding power allocation strategy. Finally, numerical simulations are presented to verify the performance of the two proposed schemes.

Downlink Capacity and Optimal Power Allocation in Hybrid Underlay–Interweave Secondary Networks

In this paper, the downlink capacity region of a secondary network in a multiuser spectrum sharing system is obtained for a hybrid underlay-interweave paradigm, where the current channel side information (CSI) of the channel between a secondary transmitter-receiver pair is assumed at the secondary transmitter, whereas the outdated CSI of the interference channel is available to the secondary transmitter. In the hybrid paradigm, the secondary network cycles through the interweave or the underlay paradigms depending on whether spectrum holes are detected or the primary network is active, respectively. The outdated CSI is described via a correlation model, and the interference outage probability constraint (IOPC) and the average interference power constraint are considered. In general, determining the boundary of this region is a nonconvex problem. To navigate around solving this nonconvex problem, we replace the IOPC with its equivalent constraint on the peak transmit power, and we propose a power allocation algorithm for solving the latter problem. Simulations show that utilizing the outdated CSI of the interference channel reduces the secondary network's capacity as compared with when the current CSI is utilized. This reduction is a function of the correlation between the current and outdated CSI values, the interference outage probability in the primary network, and imperfect spectrum sensing.

Optimal resource allocation for cooperative orthogonal frequency division multiplexing‐based cognitive radio networks with imperfect spectrum sensing

This study investigates sensing-based spectrum sharing access (SSSA) and sensing-based spectrum opportunistic access (SSOA) schemes in cooperative orthogonal frequency division multiplexing (OFDM)-based cognitive radio networks with imperfect spectrum sensing. The optimal resource allocation strategy, including sensing time and transmit power, is designed to maximise the ergodic throughput of the secondary system. For a two-hop cooperative communication in the secondary system, the authors adopt the amplify-and-forward relay protocol and enable the source and relay to sense the state of the primary user jointly. To protect the PU effectively from harmful interference, they consider the average interference power constraint in each hop. The total average transmit power constraint of the source and relay is considered. Two simplified versions for the SSSA and SSOA schemes are employed because of the complexity of the problem. They then propose two algorithms that acquire the optimal sensing time and power allocation for both schemes. Finally, simulation results are presented to compare the performance of the two schemes.

A Dynamic QoS Model for Improving the Throughput of Wideband Spectrum Sharing in Cognitive Radio Networks

This paper considers a wideband cognitive radio network (WCRN) which can simultaneously sense multiple narrowband channels and thus aggregate the detected available channels for transmission and studies the ergodic throughput of the WCRN that operated under: the wideband sensing-based spectrum sharing (WSSS) scheme and the wideband opportunistic spectrum access (WOSA) scheme. In our analysis, besides the average interference power constraint at PU, the average transmit power constraint of SU is also considered for the two schemes and a novel cognitive radio sensing frame that allows data transmission and spectrum sensing at the same time is utilized, and then the maximization throughput problem is solved by developing a gradient projection method. Finally, numerical simulations are presented to verify the performance of the two proposed schemes.

Channel capacity in fading environment with CSI and interference power constraints for cognitive radio communication system

In this paper, we have numerically computed the channel capacity in fading environment under average interference power constraint with two different adaptation policies for the spectrum sharing in cognitive radio communication systems such as power adaptation and rate and power adaptation for multilevel quadrature amplitude modulation format. However, the small scale fading effect over the transmit power of the secondary transmitter is explored. The rate and power of secondary transmitter is varied based upon the sensing information and channel state information of the secondary link. The channel capacity is maximized for these two policies by considering the Lagrange optimization problem for average interference power constraint.

QoS‐based power allocation for cognitive radios with AMC and ARQ in Nakagami‐m fading channels

AbstractThis paper presents power allocation schemes to maximize the effective capacity (EC) of a secondary user (SU) communications link using adaptive modulation and coding (AMC) in an underlay cognitive radio Nakagami‐m block‐fading environment to meet target quality‐of‐service (QoS) requirements in terms of delay‐outage probability and packet error rate constraints. The SU transmission parameters are chosen such that the primary user imposed interference power constraint (IPC) is satisfied. Three different types of IPCs, namely average interference power, peak interference power and interference power outage, are considered. For each IPC, the analytical solutions for choosing the AMC mode and power allocation in each fading block, and the corresponding SU achievable EC under given QoS requirements are derived. Furthermore, we investigate the performance of a hybrid automatic repeat request (ARQ)/AMC and obtain the closed‐form packet loss rate expression. Illustrative results show the effects of the IPC, fading duration and fading severeness on the SU achievable EC under given QoS requirements. It is shown that for loose delay‐outage requirements, average interference power and interference power outage constraints give higher SU EC than peak interference power constraint. However, for more stringent delay‐outage requirements, the SU achievable EC for the three IPC is significantly reduced. The results also indicate that ARQ is helpful to significantly reduce the packet loss rate for loose delay constraint. However, ARQ increases the delay and is not effective for stringent delay‐outage requirements. Copyright © 2014 John Wiley & Sons, Ltd.