Primary Base Station Research Articles

Joint Video Packet Scheduling, Subchannel Assignment and Power Allocation for Cognitive Heterogeneous Networks

In this paper, a joint video scheduling, subchannel assignment, and power allocation problem in cognitive heterogeneous networks are modeled as a mixed integer non-linear programming (MINLP), which maximizes the minimum video transmission quality among different secondary mobile terminals (MTs) subject to the total available energy at each secondary, the total interference power at each primary base station, the total available capacity at each radio interface of each secondary MTs, and the video sequence encoding characteristic. In order to solve it, we decompose the original MINLP as joint subchannel and power allocation problem and video packet scheduling problem. Then, we model the joint subchannel and power allocation problem as a max–min fractional programming, and transform it as a convex optimization problem. Finally, we utilize dual decomposition method to design a joint subchannel and power allocation algorithm, and propose a video packet scheduling scheme based on auction theory to maximize the video quality for each secondary MT. Simulation results demonstrate that the proposed framework not only improves the video transmission quality significantly, but also guarantees the fairness among different secondary MTs.

Massive MIMO in Spectrum Sharing Networks: Achievable Rate and Power Efficiency

Massive multiple input multiple output (MIMO) is one of the key technologies for fifth generation and can substantially improve energy and spectrum efficiencies. This paper explores the potential benefits of massive MIMO in spectrum sharing networks. We consider a multiuser MIMO primary network, with N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> -antenna primary base station (PBS) and K single-antenna primary users (PUs), and a multiple-input-single-output secondary network, with N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> -antenna secondary base station and a single-antenna secondary user. Using the proposed model, we derive a tight closed-form expression for the lower bound on the average achievable rate, which is applicable to arbitrary system parameters. By performing large-system analysis, we examine the impact of large number of PBS antennas and large number of PUs on the secondary network. It is shown that, when N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> and K grow large, N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> must be proportional to ln K or larger, to enable successful secondary transmission. In addition, we examine the impact of imperfect channel state information on the secondary network. It is shown that the detrimental effect of channel estimation errors is significantly mitigated as N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> grows large.

Novel sensing and joint beam and null steering based resource allocation for cross-tier interference mitigation in cognitive femtocell networks

Cognitive radios and femtocell networks are gaining much popularity due to the formers ability to carry out unlicensed transmission in licensed bands and the latter’s ability to increase the indoor capacity by bringing the transmitter and receiver closer to each other. The combination of the two provides us with a joint benefit of unlicensed transmission and increased system capacity. However, deployments of such cognitive radio based femtocell networks (CRFN) can pose some severe cross-tier interference towards the primary system. In this paper, we propose a novel spectrum sensing technique based on Uniform Linear array (ULA) combined with Genetic Algorithm to detect not only the presence of a Primary user but also estimate its parameters such as range, frequency, angle of arrival and amplitude. Furthermore, a joint beamforming and null steering technique is proposed to maximize the signal to interference plus noise ratio (SINR) towards the secondary user equipment (SUE) while minimizing the interference towards the primary Base Station (PBS). We are reutilizing the sensed uplink (UL) frequency of the Primary users for the downlink (DL) transmission; the cognitive femtocell base station (CFBS) calculates such weight vector that aims at sending the maximum signal power towards the femto user and null in the direction of PBS.

Secure Communication in OFDMA-Based Cognitive Radio Networks: An Incentivized Secondary Network Coexistence Approach

In this paper, we propose a secure cooperative communications scheme for orthogonal frequency-division multiple-access (OFDMA) cognitive radio networks (CRNs), where a primary base station (PBS) wants to transmit information to some distant primary users (PUs) in the presence of a set of passive eavesdroppers. In our model, the transmission is performed in two consecutive time slots; in the first time slot, the PBS transmits while the secondary users (SUs) and the eavesdroppers listen. In the second time slot, the SUs transmit while the PUs, the secondary base station (SBS), and the eavesdroppers listen. We consider two schemes for eavesdropping; in the first scheme, the eavesdroppers listen to transmissions from the PBS to the SUs, and in the second scheme, we assume that the eavesdroppers apply the maximal ratio combining approach on the received signals in the first and second time slots for the primary network. In the proposed model, the SUs are allowed to use the licensed spectrum of the PUs, as long as they help the PUs to satisfy their secrecy rate requirement. We assume a frame-based transmission where each frame is divided into two consecutive time slots of equal duration. In the first time slot, the PBS transmits while the SUs and the eavesdroppers listen. In the second time slot, the selected SUs relay the PBS information to the distant PUs. Meanwhile, the SUs use the remaining resources to transmit their own information to the SBS while the eavesdroppers listen to this transmission. We formulate our proposed schemes as an optimization problem and solve it by dual Lagrange approach. We evaluate our proposed scheme in various situations using simulations and show the efficiency of the proposed scheme. An important aspect of the proposed paradigm is that replacing the conventional average interference threshold constraint by the primary secrecy rate constraint does not only decrease the secondary average secrecy rate with respect to the conventional case but can actually provide significantly higher secondary average secrecy rate as well.

Non-Orthogonal Random Access in MIMO Cognitive Radio Networks: Beamforming, Power Allocation, and Opportunistic Transmission.

We study secondary random access in multi-input multi-output cognitive radio networks, where a slotted ALOHA-type protocol and successive interference cancellation are used. We first introduce three types of transmit beamforming performed by secondary users, where multiple antennas are used to suppress the interference at the primary base station and/or to increase the received signal power at the secondary base station. Then, we show a simple decentralized power allocation along with the equivalent single-antenna conversion. To exploit the multiuser diversity gain, an opportunistic transmission protocol is proposed, where the secondary users generating less interference are opportunistically selected, resulting in a further reduction of the interference temperature. The proposed methods are validated via computer simulations. Numerical results show that increasing the number of transmit antennas can greatly reduce the interference temperature, while increasing the number of receive antennas leads to a reduction of the total transmit power. Optimal parameter values of the opportunistic transmission protocol are examined according to three types of beamforming and different antenna configurations, in terms of maximizing the cognitive transmission capacity. All the beamforming, decentralized power allocation, and opportunistic transmission protocol are performed by the secondary users in a decentralized manner, thus resulting in an easy implementation in practice.

Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks.

In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only promote the secondary users to meet the maximum communication needs, but also to maximize the utilization of spectrum resources, however, research in this area is lacking, so from the viewpoint of meeting the demand of network communication, this paper designs a two stage model to solve spectrum leasing and allocation problem in cognitive radio sensor networks (CRSNs). In the first stage, the secondary base station collects the secondary network communication requirements, and rents spectrum resources from several primary base stations using the Bertrand game to model the transaction behavior of the primary base station and secondary base station. The second stage, the subcarriers and power allocation problem of secondary base stations is defined as a nonlinear programming problem to be solved based on Nash bargaining. The simulation results show that the proposed model can satisfy the communication requirements of each user in a fair and efficient way compared to other spectrum sharing schemes.

Simultaneous wireless energy transfer and spectrum sharing with primary data relaying in cognitive radio networks

Spectrum sharing and energy harvesting (EH) are promising techniques to enhance the spectrum and energy efficiency of wireless networks. In this paper, we propose a spectrum sharing scheme based on the cooperative energy and data transfer in both the time and space domains. When the primary base station (PB) transfers energy to the primary user (PU), the secondary user (SU) can transmit its own data simultaneously, and the interference of secondary data transmission becomes beneficial to improve the EH efficiency of the PU. Furthermore, the SU can assist the primary data relaying using the Alamouti coding technique to improve the link robustness through introducing the space diversity. With the energy and data cooperation from the SU, the primary data can be more quickly and reliably delivered, and hence more opportunities can be achieved for the spectrum sharing. Considering the dependence of the energy and data transfer, the throughput of both systems is investigated. The time allocation between EH and data transmission can be numerically determined by maximizing the throughput of secondary system under the throughput constraint of primary system. Performance results are presented to validate our theoretical analysis and provide some guidelines for the network configuration.

Securing cognitive radio with a combined approach of beamforming and cooperative jamming

The authors consider secret communication through a relay-assisted cognitive interference channel in which primary and secondary base stations (SBSs), respectively, communicate with the primary and secondary receivers (PU-Rx and SU-Rx) in the presence of multiple eavesdroppers. An SBS is allowed to transmit simultaneously with the primary base station (PBS). They propose three cooperative jamming (CJ) schemes based on the available channel state information at the base stations and the relay. The proposed CJ schemes are designed to create additional interference in the direction of eavesdroppers without creating any interference to the PU-Rx and the SU-Rx. A combined approach of beamforming and zero-forcing precoding is developed at the PBS, the SBS and the relay to cancel out jamming interference at the PU-Rx and the SU-Rx. The secrecy rate of SU-Rx is calculated with the constraint of maintaining interference temperature at the PU-Rx under a certain threshold. Compared with the direct transmission schemes that are available in the literature, the authors’ results show that the approach which combined beamforming and CJ significantly improves the secrecy rate of the cognitive interference channel.

Modified hybrid interference cancellation algorithm for uplink cognitive radio transmission based on overloaded DS-CDMA

In this paper, cognitive radio network architecture based on overloaded direct sequence code division multiple access (O-DS-CDMA) is proposed. In this method, secondary users are enabled to share the available bandwidth with the existing primary users. Two sets of orthogonal Gold codes are used to support the primary and secondary users simultaneously. Orthogonality between the spreading codes is lost due to non-zero cross correlation between the codes and timing synchronisation error in the uplink transmission, which causes interference among primary and secondary users. In this paper, a modified hybrid parallel/successive interference cancellation algorithm is proposed for the primary and secondary user base station receivers with multiple antennas, to suppress the interference among the users. Interferences among same group users are cancelled using parallel interference cancellation and the interferences between groups are cancelled using successive interference cancellation. The simulation results show that, the proposed modified interference cancellation algorithm improves the BER performance of the system significantly.

Achievable Rates of UAV-Relayed Cooperative Cognitive Radio MIMO Systems

We study the achievable rate of an uplink MIMO cognitive radio system where the primary user (PU) and the secondary user (SU) aim to communicate to the closest primary base station (BS) via a multi-access channel through the same unmanned aerial vehicle (UAV) relay. The SU message is then forwarded from the primary BS to the secondary network with a certain incentive reward as a part of the cooperation protocol between both the networks. A special linear precoding scheme is proposed to enable the SU to exploit the PU free eigenmodes. We analyze two scenarios in which the UAV relay gain matrix is either fixed or optimized. We derive the optimal power allocation that maximizes the achievable rate of the SU respecting power budget, interference, and relay power constraints. Numerical results highlight the cognitive rate gain of our proposed scheme with respect to various problem parameters. We also highlight the effect of UAV altitude on the SU and PU rates. Finally, when the relay matrix is optimized, we show that the PU rate is remarkably enhanced and that the SU rate is only improved at high-power regime.

Spectrum Forecast Using Propagation Losses of the Okumura-Hata Model

Radioelectric spectrum occupancy forecast has proven to be useful in the design of wireless systems because of its ability to harness spectrum opportunities like Cognitive Radio (CR). This paper proposes the development of a model that identifies the spectrum opportunities in the channel of a mobile cellular network for an urban environment using the received signal power forecast. The proposed model integrates the Okumura-Hata (O-H) large-scale propagation model with a wavelet neural model. The model results, obtained through simulations, show that the wavelet neural model forecasts with a high degree of precision and that the CR user may forecast the power level that will be received from the primary Base Station (BS) at different distances, which is consistent with the observed behavior in experiments carried out in wireless systems of this type. Finally, the duty cycle is also presented.

Joint detection scheme for cooperative spectrum sensing in cognitive radio network

In this paper, a new architecture of cognitive radio network (CRN) is presented for future dynamic spectrum sharing in time-variant flat fading (TVFF) channels. We consider a practical scenario where secondary users (SUs) are able to access the idle spectrum by secondary user routers (SU_Rs). Managed by a fusion center (FC), SU_Rs can work together to capture the idle spectrum, and then assign to the SUs. Besides, it is imperative to guarantee the wireless communication quality between primary base station (P_BS) and SU_Rs. Therefore, a new cooperative spectrum sensing (CSS) algorithm is suggested to recursively estimate the channel state information (CSI) while capturing the idle licensed band. The united mathematics model relies on a dynamic state-space model (DSM) and a Bernoulli filters (BF) algorithm. TVFF channels are modeled as finite-state Markov channel (FSMC). In order to reduce complexity of CSS, the particles are manipulated and reconstructed. Experimental simulations demonstrate that, by exploiting dynamic CSI, sensing performance of the new CSS algorithm will surpass the traditional schemes and this new architecture can be used in a realistic spectrum sharing system.

Secondary VoIP Capacity in Opportunistic Spectrum Access Networks with Friendly Scheduling

In conventional cognitive radio, the primary network usually remains unchanged. In some cases, however, the primary network operator may wish to accommodate secondary user access. In this paper, we assess the secondary user VoIP capacity when primary basestation scheduling is designed to be secondary network friendly. Friendliness is measured by the number of connections that can be supported subject to typical quality of service constraints in the presence of delay tolerant primary traffic. An offline scheduler is first derived that maximizes friendliness using an integer linear program formulation. We show that this schedule can be found using a minimum cost flow graph construction in time complexity that is polynomial in the number of time slots. Two online scheduling algorithms are then compared that achieve various levels of friendliness. The first algorithm operates by having the primary network temporally shape its residual capacity subject to satisfying its own packet deadline constraints. The second algorithm assumes virtual secondary calls and applies scheduling to both primary traffic and virtual secondary traffic. Results are presented for a variety of parameters that show the degree to which friendly scheduling can improve secondary user VoIP capacity compared to non-friendly primary scheduling.

A capacity-aware MIMO-beamforming approach for cognitive radio enabled smart grid systems

This paper proposes an adaptive multiple input multiple output-beamforming scheme (MIMO-BF) for cognitive radio enabled broad band smart grid (SG) systems concurrently sharing the same spectrum with the primary network (PN) and employing orthogonal frequency-division multiplexing with space division multiple access (OFDM-SDMA) technologies. The proposed algorithm uses gradient search of the channel capacity to seek, iteratively, the optimal transmit weight vectors that maximise the MIMO channel capacity for each cognitive user of the SG network, while controlling the interference levels to the PN. We evaluate the symbol error rate (SER) and system capacity performances of the proposed cognitive OFDM-SDMA system and show by simulation that they outperform cognitive systems based on opportunistic approaches. It is also shown that when the SG system is using the proposed schemes it has better control on the interference at the primary base station than the one based on opportunistic capacity-aware.

Throughput Analysis for the Cognitive Uplink Under Limited Primary Cooperation

This paper studies the achievable throughput performance of the cognitive uplink under a limited primary cooperation scenario wherein the primary base station cannot feed back all interference channel gains to the secondary base station. To cope with the limited primary cooperation, we propose a feedback protocol called $K$ -out-of- $N$ feedback protocol, in which the primary base station feeds back only the $ {K_{N}}$ smallest interference channel gains, out of $N$ of them, to the secondary base station. We characterize the throughput performance under the $K$ -out-of- $N$ feedback protocol by analyzing the achievable multiuser diversity gains (MDGs) in cognitive uplinks for three different network types. Our results show that the proposed feedback mechanism is asymptotically optimum for interference-limited (IL) and individual-power-and-interference-limited (IPIL) networks for a fixed positive $K_{N}$ . It is further shown that the secondary network throughput in the IL and IPIL networks (under both the full and limited cooperation scenarios) logarithmically scales with the number of users in the network. In total-power-and-interference-limited (TPIL) networks, on the other hand, the $K$ -out-of- $N$ feedback protocol is asymptotically optimum for $ {K_{N}}= N^\delta $ , where $\delta \in \left ({0,1}\right )$ . We also show that, in TPIL networks, the secondary network throughput under both the limited and full cooperation scales logarithmically double with the number of users in the network. These results indicate that the cognitive uplink can achieve the optimum MDG even with limited cooperation from the primary network. They also establish the dependence of pre-log throughput scaling factors on the distribution of fading channel gains for different network types.

Cooperative Caching in Dynamic Shared Spectrum Networks

This paper considers co-operation between primary and secondary users in shared spectrum radio networks via caching. We first consider a network with one channel shared between a single macro (primary) base station and multiple micro (secondary) base stations. Secondary base stations can cache some primary files and thereby satisfy content requests generated from nearby primary users. For this co-operative scenario, we develop two caching and scheduling policies under which the set of primary and secondary request generation rates that can be supported increases from the case without cooperation. The first of these algorithms, fixed primary caching policy (FPCP), provides more gain in the set of supportable request generation rates. However under this algorithm primary packet transmissions from secondary base stations have the same priority of access as secondary packets and thus might suffer in terms of delay. In the second algorithm, variable primary caching policy (VPCP), primary packet transmissions from the secondary base stations have higher priority of access than that of secondary packets. We find that the set of request generation rate vectors for which all queues in the network are stable under each of these algorithms is greater than that under any non-cooperative algorithm. We conduct extensive simulations to compare the performance of both algorithms against that of an optimal nonco-operative algorithm. Finally, we extend the analysis to a network with multiple channels.

Secure D2D Communication in Large-Scale Cognitive Cellular Networks: A Wireless Power Transfer Model

In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multiantenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the primary base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, three wireless power transfer (WPT) policies are proposed: 1) co-operative power beacons (CPB) power transfer, 2) best power beacon (BPB) power transfer, and 3) nearest power beacon (NPB) power transfer. To characterize the power transfer reliability of the proposed three policies, we derive new expressions for the exact power outage probability. Moreover, the analysis of the power outage probability is extended to the case when PBs are equipped with large antenna arrays. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), where the receiver with the strongest channel is selected; and 2) nearest receiver selection (NRS), where the nearest receiver is selected. To assess the secrecy performance, we derive new analytical expressions for the secrecy outage probability and the secrecy throughput considering the two receiver selection schemes using the proposed WPT policies. We presented Monte carlo simulation results to corroborate our analysis and show: 1) secrecy performance improves with increasing densities of PBs and D2D receivers due to larger multiuser diversity gain; 2) CPB achieves better secrecy performance than BPB and NPB but consumes more power; and 3) BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead. A pivotal conclusion is reached that with increasing number of antennas at PBs, NPB offers a comparable secrecy performance to that of BPB but with a lower complexity.

Wireless Energy Harvesting in Cognitive Massive MIMO Systems with Underlay Spectrum Sharing

The achievable sum rate of a wireless-powered multi-cell/multi-user cognitive radio massive multiple-input multiple-output system with underlay spectrum sharing is investigated. The secondary user nodes can harvest energy from the primary user transmissions, and then access and utilize the primary network spectrum for information transmission. The signal-to-interference-plus-noise ratio and achievable sum rate are derived for two specific antenna configurations: 1) unlimited base-station antenna arrays and 2) limited base-station antenna arrays. Furthermore, the optimal time-switching factor and the energy-rate trade-off are quantified in closed-form. The asymptotic analysis reveals that the secondary system can be operated by using its maximum harvested energy when the number of primary base-station antennas grows without bound without hindering the primary transmission.

Maximum SINR-Based Receive Combiner for Cognitive MU-MIMO Systems

In this correspondence, we seek to maximize the signal-to-interference-plus-noise ratio (SINR) of cognitive users (CUs) by designing an optimal receive combiner (ORC), taking into account interference from the primary base station (PBS) to CUs [inter-PBS interference (IPI)], multiuser interference (MUI) among CUs, and desired channel gains. By employing the Rayleigh–Ritz quotient result, we formulate an optimal receiver design and then determine the ORC by solving tfshe derived standard eigenvalue problem. The ORCs are derived as closed forms according to the presence or absence of interference beam information at each CU. When the interference beam information is available, the maximum SINR is given as the largest eigenvalue of the received SINR. In the absence of interference beam information, the ORC based on prediction is proposed based on the prediction of the worst IPI and MUI directions and asymptotically analyzed in terms of the number of transmit antennas. Simulation results demonstrate that the ORC maximizes the sum rate of the cognitive multiuser multiple-input/multiple-output system compared with the reference receive combiners.

Strive for the spectrum sharing by transferring energy and relaying data for the primary user

AbstractThrough harvesting energy from the environment, the wireless system can be sustainable and work for a long time. The spectrum sharing is promising to cope with the contradiction between the shortage of spectrum and the ever‐growing transmission requirements. Jointly considering the energy and spectrum efficiencies, we proposed in this work an energy harvesting (EH)‐based spectrum sharing scheme. The cognitive radio network with one primary link and one secondary link is studied, where the primary base station (BS) serves its primary user (PU), and the secondary access point (AP) intends to communicate with a secondary user. The PU should harvest the wireless energy for the uplink data transmission, while all the other terminals have the stable power supply. The AP can wirelessly transfer energy to the PU along with the BS to improve the EH efficiency, and further, it can relay the primary data to the BS to improve the spectrum efficiency. The energy and data cooperation from the AP can significantly enhance the throughput of primary system, and hence, more spectrum can be released for the secondary data transmission. The resource allocation between the two systems for the energy transfer and data relaying is determined through maximising the throughput of secondary link while guaranteeing the performance of primary link. Under the peak power constraint, the system performance is analysed considering the dependence of the downlink energy transfer and the uplink data relaying. Numerical results are provided to reveal the impacts of various parameter settings to the system performance. Copyright © 2015 John Wiley &amp; Sons, Ltd.