Performance Analysis of Spectrum Sensing With Multiple Primary Users

Cognitive Radio Network is a form of communication where licensed frequency band of the Primary users (PUs) are made available to the Secondary user (SU) with constraint interference to the PUs. In this work, we have investigated a novel model considering interweave approach for spectrum access, with multiple primary users and single secondary user (SU). Multiple antennas have been considered at both the primary users as well as the secondary users. The activity of primary users are modeled as Poisson process. In addition, we also propose a new approach of sensing for a MIMO cognitive radio network using energy detection. The proposed method provides a closed form expression for probability of detection (P d ) and probability of false alarm (P f ) in a Multiple Input Multiple Output (MIMO) channel. Further, the throughput of secondary user as well as interference on primary users caused due to secondary user transmissions, has been computed for the proposed model.

A generalized order user selection scheme for cognitive networks with imperfect channel estimation and 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.

We present an analytical framework to assess the link layer throughput of multichannel Opportunistic Spectrum Access (OSA) ad hoc networks. Specifically, we focus on analyzing various combinations of collaborative spectrum sensing and Medium Access Control (MAC) protocol abstractions. We decompose collaborative spectrum sensing into layers, parametrize each layer, classify existing solutions, and propose a new protocol called Truncated Time Division Multiple Access (TTDMA) that supports efficient distribution of sensing results in "k out of N" fusion rule. In case of multichannel MAC protocols we evaluate two main approaches of control channel design with (i) dedicated and (ii) hopping channel. We propose to augment these protocols with options of handling secondary user (SU) connections preempted by primary user (PU) by (i) connection buffering until PU departure and (ii) connection switching to a vacant PU channel. By comparing and optimizing different design combinations we show that (i) it is generally better to buffer preempted SU connections than to switch them to PU vacant channels and (ii) TTDMA is a promising design option for collaborative spectrum sensing process when k does not change over time.

In this paper, we investigate outage performance of dual-hop cognitive AF relay networks with multiple primary users (PUs) and heterogeneous non-identical parameters, including non-identical Rayleigh fading channels, non-identical interference power constraints of PUs, and non-identical noise powers in signals. To overcome the analysis complexity resulted from the consideration of heterogeneous non-identical parameters completely, we conduct our analysis in two steps. In the first step, we focus on networks with non-identical Rayleigh fading channels but with identical interference power constraints and identical noise powers. As analysis results, both the exact closed-form expression and asymptotic closed-form expression of the cumulative distribution function of equivalent end-to-end signal-to-noise ratio of the network are obtained. Then in the second step, we propose a method for transforming networks with heterogeneous non-identical parameters into new networks with identical interference power constraints and identical noise powers meanwhile guaranteeing that outage performance of the two networks before and after the transformation are identical. Hence, outage performance of networks with heterogeneous non-identical parameters can be obtained by applying the analysis results in the fist step to the corresponding transformed networks. Numerical simulations validate the correctness of our analysis, and the simulations also indicate that taking multiple PUs and the diversity of the parameters into consideration is of key importance in obtaining a more accurate estimation of outage performance of such networks.

Cognitive Radio (CR) aims to provide efficient utilization of the scarcely available radio spectrum. Spectrum sensing is indispensable to identify spectrum holes. Inaccurate sensing results in interference to PU. Therefore, sensing accuracy is an important parameter. Cooperative Spectrum Sensing (CSS) is an efficient technique to improve the sensing accuracy. It makes use of cooperation between Secondary Users (SUs) to detect the presence of Primary User (PU). Game theoretical models help in understanding and modeling interaction among users. In this paper, a CR network with multiple PUs and SUs is considered. CSS is modeled as hedonic coalition formation game where SUs sensing the same channel form coalitions. The coalitions are formed on the basis of probability of detection. For each PU, the SUs which have maximum probability of detection form coalition and cooperatively make the final sensing decision by making use of OR rule. Channel estimation for ST-SR link is done using WARP testbed. The sensing accuracy and energy consumption for the coalitions when link is modeled using free space pathloss model and using WARP testbed are found out. Simulation results show that CSS modeled using hedonic coalition formation has better sensing accuracy than non-cooperative sensing.

In this report, we point out on a system in which secondary user (SU) transmitter communicates with a SU receiver via a secondary relay (SR) under the interference from multiple primary users (PUs). Power allocated to SU transmitter on the basis of two constraints of PU, viz., outage threshold and outage transmission rate. In this case, performance of PU does not degrade due to these tolerable constraints. Direct link does not occur between the SU transmitter and receiver because of shadowing. A SR used to link the SU transmitter to SU receiver that is based on decode-and-forward (DF) scheme. Outage probability (OP) calculated by considering the interferences from all PUs at SR and secondary receiver. We see that the performance of SU network does not always degrade after the consideration of interferences from all PUs and thus, SU transmitter reliably communicates with its receiver under the specific range of primary transmit power of PUs in this system model. Results of this model are verified by the MATLAB simulation.

In this paper, we present an analytical study for the performance of a two-tier primary-secondary network based on IEEE 802.11 DCF mechanism. It is assumed that multiple primary users (PUs) and secondary users (SUs) coexist in the radio environment and share a single band such that the SUs are allowed to contend only if they sense the channel idle for a certain period of time. First, we derive the PUs' medium access delay in the presence of SUs. Then, assuming an exponential packet inter-arrival time for the primary network, and using M/G/1 queue modeling, we determine the collision probability and throughput for the primary and secondary networks, as well as the PUs' average total delay including the queuing delay. Numerical along with simulation results show how the performance in the primary network, with given packet arrival rate, can be affected as functions of the sensing time, packet payload size and population size of the SUs. The findings of this work can be used effectively to study the performance of any IEEE 802.11 based primary-secondary network, such as cognitive radio networks where SUs may exploit a primary channel opportunistically based on a predefined policy, as well as to optimize the performance of distributed cognitive radio MAC protocols.

This work is directed towards a symbiotic architecture called Cognitive Relaying with Time Incentive (CRTI) for multiple Primary Users (PUs) in a Cognitive Radio network. The rationale of CRTI is that the PU with a weak transmission link seeks cooperation from the cognitive Secondary User (SU) nodes in its vicinity, and in return rewards them with an incentive time for their own communication. Since each PU has its own distinct bandwidth of operation, it is crucial to decide the most favorable use of the spectrum when relaying through the SU network. We propose two schemes-Band-Restricted Relaying and All-Band Relaying to achieve this objective. Cross-layer optimization problems are formulated for the relaying schemes which create the time incentive, as well as for the SUs to efficiently access this incentive. The proposed schemes are compared, and simulation results are furnished to demonstrate their differences and individual merits from the PU and SU's perspective.

We study the subcarrier, bit and power allocation problem for multiuser OFDM-based multi-cell cognitive radio (CR) systems in which one or more spectrum holes exist between multiple primary user (PU) frequency bands. The cognitive radio users (CRUs) are able to share any portion of the frequency band with other CRUs and the PUs as long as this does not interfere unduly with the PUs' transmissions. Both cochannel interference (CI) from other CRUs as well as mutual interference (MI) between the CRUs and the PUs are considered. The resource allocation problem is formulated as a multi-dimensional knapsack problem and a relatively simple, greedy max-min algorithm is proposed to solve it. Simulation results show that the max-min algorithm yields solutions which are close to (within 5% of) optimal. Sharing of the whole band can provide a substantial performance improvement over schemes which use guard bands to protect PU frequency bands and do not allow CRUs to use the PU bands.

Spectrum sharing and power allocation are interesting issues in cognitive radio networks. In our paper, we introduce a pricing scheme to demonstrate the spectrum sharing scenario between primary users and secondary users. We demonstrate the joint optimal allocation scheme of both spectrum and power for secondary users buying spectrum from multiple primary users. The joint optimal allocation scheme maximizes secondary users' utilities while primary users' utilities meet certain requirements. Moreover, we illustrate a distributed resource allocation scheme to jointly optimize usage of power and spectrum when each secondary user does not know others' buying strategies. Our simulation results show that under some utility requirements, the joint optimized resource allocation scheme has 3dB gain over that under even resource allocation.

In this paper, we discuss a method to construct a radio environment map (REM) in an environment with multiple primary users (PUs). The REM provides statistical information about the PU activity at each location. It enables the secondary user to access the licensed band dynamically. We derive the measurement architecture based on the “crowd-sourcing” scheme to gather large-scale measurement data with inexpensive sensor nodes. The PU detection or identification scheme is key part of the REM construction then there are multiple PUs in the environment. However, it is difficult to identify multiple PUs in an individual user terminal. Therefore, the PU detection or identification problem is solved at the REM servers using the Hidden Markov Model (HMM), which is a time-series-based machine learning technique. The proposed HMM method classifies the measurement data depending on the combined state of each transmitter, which can be either active or idle. The results show that the proposed method exhibits better performance than the existing unsupervised clustering method.

A cognitive radio (CR) network refers to a secondary network operating in a frequency band originally licensed/allocated to a primary network consisting of one or multiple primary users (PUs). A fundamental challenge for realizing such a system is to ensure the quality of service (QoS) of the PUs as well as to maximize the throughput or ensure the QoS, such as signal-to-interference-plus-noise ratios (SINRs), of the secondary users (SUs). In this paper, we study single-input multiple output multiple access channels (SIMO-MAC) for the CR network. Subject to interference constraints for the PUs as well as peak power constraints for the SUs, two optimization problems involving a joint beamforming and power allocation for the CR network are considered: the sum-rate maximization problem and the SINR balancing problem. For the sum-rate maximization problem, zero-forcing based decision feedback equalizers are used to decouple the SIMO-MAC, and a capped multi-level (CML) water-filling algorithm is proposed to maximize the achievable sum-rate of the SUs for the single PU case. When multiple PUs exist, a recursive decoupled power allocation algorithm is proposed to derive the optimal power allocation solution. For the SINR balancing problem, it is shown that, using linear minimum mean-square-error receivers, each of the interference constraints and peak power constraints can be completely decoupled, and thus the multi-constraint optimization problem can be solved through multiple single-constraint sub-problems. Theoretical analysis for the proposed algorithms is presented, together with numerical simulations which compare the performances of different power allocation schemes.

We propose an adaptive resource allocation algorithm for a multiple-input multiple-output (MIMO) orthogonal frequency division multiple access (OFDMA) based downlink cognitive radio network (CRN). The CRN has multiple secondary users (SUs) coexisting with multiple primary users (PUs). The aim is to maximize the total data throughput of SUs while ensuring interference leakage to PUs is below a threshold and quality of services (QoS) for SUs such as data rates and bit error rate (BER) are met. The algorithm optimally allocates radio resources such as subcarrier, spatial beams, powers and bits to each user using an integer linear programming (ILP) framework. The performance of the algorithm has been evaluated using simulation results.

In this work it is considered a ultra wideband cognitive radio network where multiple secondary users (SUs) communicate with an access point (AP) in an opportunistic way. The SUs adopt a distributed medium access control (MAC) scheme based on time contention through random medium access. One or multiple primary users (PUs) may become active in the entire band or in part of it, which may impact in the communications of the SUs. Departing from a classical random access scheme for the SUs, it is derived a solution to estimate the level of activity of the PUs through the observation of different data available at the MAC layer of each SU. Differently from the majority of the works already proposed, no physical spectrum sensing is needed to estimate the activity of the PUs since the estimation only relies on data collected at the MAC layer. Based on the level of PUs' activity detected by each SU, it is proposed a solution to regulate the SU's medium access in order to guarantee a given level of protection to the PUs. The formal methodology is evaluated through simulation and several results confirm the effectiveness of our proposal.