Performance Analysis of Secondary Users in Dynamic Spectrum Access under Interference Temperature Constraints

Spectrum is one of the most precious radio resources. With the increasing demand for wireless communication, efficiently using the spectrum resource has become an essential issue. With the Federal Communications Commission's (FCC) spectrum policy reform, secondary spectrum sharing has gained increasing interest. One of the policy reforms introduces the concept of an interference temperature - the total allowable interference in a spectral band. This means that secondary users can use different transmit powers as long as the sum of these power is less than the interference threshold. In this paper, we study two problems in secondary spectrum access with minimum signal to interference noise ratio (quality of service (QoS)) guarantee under an interference temperature constraint. First, when all the secondary links can be supported, a nonlinear optimization problem with the objective to maximize the total transmitting rate of the secondary users is formulated. The nonlinear optimization is solved efficiently using geometric programming techniques. The second problem we address is, when not all the secondary links can be supported with their QoS requirement, it is desirable to have the spectrum access opportunity proportional to the user priority if they belong to different priority classes. In this context, we formulate an operator problem which takes the priority issues into consideration. To solve this problem, first, we propose a centralized reduced complexity search algorithm to find the optimal solution. Then, in order to solve this problem distributively, we define a secondary spectrum sharing potential game. The Nash equilibria of this potential game are investigated. The efficiency of the Nash equilibria solutions are characterized. It is shown that distributed sequential play and an algorithm based on stochastic learning attain the equilibrium solutions. Finally, the performances are examined through simulations

In this paper we study the problem of quantifying the value of spectrum opportunities to secondary users in Dynamic Spectrum Access (DSA) systems. We especially focus on estimating the impact of key channel parameters, namely the activity patterns of the primary users on the expected quality of experience for secondary users accessing video streams over a DSA system. In our study we consider three basic types of video representing typical video content categorized according to scene change rate ranging from low-activity newscast to high-activity sports video. Through extensive simulations we show that given some information on the expected level of activity in the video, the duty cycle of the primary user alone can yield good predictors for the expected quality of experience of secondary users. Knowledge of the precise distributions of the primary user ON and OFF periods can be used to further enhance the precision of the prediction, but at least for exponential and log-normal channel access patterns the differences are rather small. Finally, we study the problem of determining the channel statistics that are needed to apply the predictor in an optimization setting. Our simulations show that high accuracy can be achieved in matter of minutes of estimation time, which is more than enough for practical deployments in typical urban environments.

A prototype Dynamic Spectrum Access (DSA) system is implemented, for ease of implementation, using the audio spectrum. In this setup, laptop PCs behave as two software defined radios (SDR), one a primary user (PU) and the other a secondary user (SU). The radios communicate digital information over the air, using the audio capabilities of standard soundcards. The PU, which is emulating the licensed user of an audio channel centered at 4 kHz, communicates using binary phase shift keying (BPSK) modulated data in periodic bursts. A cognitive radio (CR) based SU wishes to opportunistically occupy the PU channel during the inter-burst times, i.e. during the temporal ‘spectrum holes,’ while not interfering with the PU traffic. The PU link is implemented in MATLAB, while the SU is defined in GNU Radio with a separate Python control module defining its algorithm for spectrum sensing and hopping. The implementation of both communication links is described, as well as the initial performance evaluation of the preliminary system in terms of bit error rate performance of the PU with and without the presence of an active SU. The measured BER achieved for the best of the PU bursts with DSA was on the order of a few percent, just slightly higher than without DSA.

Cognitive radio (CR) and dynamic spectrum access (DSA) are the effective ways to solve the spectrum congestion problem. Three kinds of basic DSA approaches are respectively dynamic exclusive use, open sharing and hierarchical access. The hierarchical access model is perhaps the most compatible with solving the current spectrum congestion problem. So, in this paper, we will set up an overlay DSA system which is an effective approach of the hierarchical access model. Firstly, we make use of the spectrally modulated spectrally encoded (SMSE) framework to generate OFDM waveforms for the secondary user (SU) which can be considered as the overlay waveform. Then we use the signal which is generated by the walkie-talkie to access the overlay DSA system as a primary user (PU) or an interference signal. The universal software radio peripheral (USRP) and spectrum analyzer are used to generate and analyze the power spectrum density (PSD) of the coexistence of a SU and a PU or an interference signal. The experimental result demonstrates that the overlay DSA system can achieve the function of turning off the sub-carriers corresponding to the frequency of the PU. It also shows that the system can greatly improve the efficiency of the spectrum utilization due to dynamically allocate the spectrum.

The spectrum scarcity problem can be tackled by promoting a more efficient use of the radio spectrum. Spectrum sharing techniques like TV White Spaces (TVWS), Licensed Shared Access (LSA), and Spectrum Access System (SAS), are adequate solutions for this problem and there exist already regulation and standardization efforts worldwide. To evaluate the coexistence between primary and secondary spectrum users, a Long Term Evolution (LTE) multi-cell simulator has been designed, which employs a generic spectrum sharing technique, Dynamic Spectrum Access (DSA), in order to obtain additional network capacity. As a way to bring attention and confidence of the telecommunications sector regarding the benefits that this technology may bring, the analysis is done in terms of interference suffered by incumbents (primary users) and capacity by secondary users. Results have confirmed the unfeasibility of co-channel coexistence for moderate distances between the cordless camera service (incumbent) and LTE network (secondary user) due to high interference. However, for adjacent bands, a gain of 40% in the secondary users’ capacity is possible following more restrictive interference protection requirements and 30% gain with the smaller frequency separation between primary and secondary operating frequencies.

One of the major challenges in Dynamic Spectrum Access (DSA) systems is to guarantee a required level of Quality of Service (QoS) to secondary users of the spectrum. In this paper, we propose efficient algorithms for deriving optimal policies for the sensing / transmitting trade-off in hardware-constrained DSA systems. Unlike previous approaches which seek to maximize mean data rate for the secondary users, the proposed algorithms derive policies which minimize the probability of excessive queuing delays. Large Deviations (LD) asymptotics are used to approximate the probability of interest and policies maximizing the associated LD exponent are proposed. Although dynamic programming is not able to identify the optimal policy in this case, much more efficient algorithms than exhaustive search are proposed. These algorithms are based on specific properties of the optimal policy which are described and proven in this paper.

In order to mitigate the problem of crowded radio spectrum, dynamic spectrum access (DSA) has become the solution and a research focal point. The number of works in wideband spectrum sensing is dramatically increasing recently due to its importance in cognitive radio (CR) networks. Most works assume that secondary users (SUs) are synchronous with the primary users' (PUs) network. However, in many practical systems the SUs will have no information about the PUs' communication protocols. Furthermore, it is also possible that communications among PUs are not based on synchronous operation. In order to address such problems, a contention-based wideband DSA algorithm with asynchronous cooperative spectrum sensing (CSS), called the DySac, is proposed. In this scheme, the SUs need not maintain synchronism with the PUs, and the SUs who intend to access the primary network compete among each other for available channels. Performance analysis and simulations are conducted to evaluate the proposed DySac.

Traditional centralized electromagnetic spectrum monitoring platforms collect energy detection data from time, frequency and space dimensions. This method has high data redundancy. Combining the propagation loss characteristics and the signal direction finding (DF) data of each detection node, we focus on the signal source compressed parameter estimation. We propose a minimum average distance (MAD) method to improve the accuracy of collaborative detection in Cognitive Radio Network (CRN). The collaborative estimated data is stored in the blockchain structure to establish the distributed electromagnetic spectrum database (BC-DSDB). Based on the consensus mechanism Proof of High Confidence (POHC), the detection nodes maintain BC-DSDB independently. To regulate the rational utilization of electromagnetic spectrum resources, we propose the Spectrum Resource Currency (SRC) to evaluate the priority of the secondary user (SU) for dynamic spectrum access. When a spectrum collision event occurs between SUs, the spectrum time slice resources can be allocated according to the SRC. The experimental results show that BC-DSDB accurately describes the distribution of electromagnetic spectrum resources based on the propagation loss characteristics. At the same time, the redundancy of spectral data storage is reduced. SUs can quickly formulate dynamic spectrum access policies based on BC-DSDB and SRC in distributed cognitive radio networks.

Dynamic spectrum access (DSA), enabled by cognitive radio technologies, has become a promising approach to improve efficiency in spectrum utilization, and the spectrum auction is one important DSA approach, in which secondary users lease some unused bands from primary users. However, spectrum auctions are different from existing auctions studied by economists, because spectrum resources are interference-limited rather than quantity-limited, and it is possible to award one band to multiple secondary users with negligible mutual interference. To accommodate this special feature in wireless communications, in this paper, we present a novel multi-winner spectrum auction game not existing in auction literature. As secondary users may be selfish in nature and tend to be dishonest in pursuit of higher profits, we develop effective mechanisms to suppress their dishonest/collusive behaviors when secondary users distort their valuations about spectrum resources and interference relationships. Moreover, in order to make the proposed game scalable when the size of problem grows, the semi-definite programming (SDP) relaxation is applied to reduce the complexity significantly. Finally, simulation results are presented to evaluate the proposed auction mechanisms, and demonstrate the complexity reduction as well.

The purpose of this study is to determine a range of detection thresholds at which new dynamic spectrum access (DSA) devices can safely operate in unoccupied spectrum allocated to terrestrial television (TV) broadcasting and other services (i.e., the TV "white spaces"), without causing harmful interference to other authorized operations, which include digital and analog TV stations, wireless microphones and other services. Spectrum sensing data were collected at six different locations in Northern Virginia that were strategically chosen because they were within, outside and near the edges of the predicted service contours of digital TV stations serving the Washington, D.C. and Baltimore, MD metropolitan areas. We used a pair of DSA devices that jointly decide if a channel can be used or not. This emulates how SSC's and other DSA devices operate. The joint decision logic mitigates the propagation shadowing and hidden node problem. The separation between the DSA devices was less than approximately 10 km, which corresponds to the link range of a 10 W 802.16-based transmitter. The DSA detectors used a high sensitivity detector that is able to detect the ATSC pilot down to a -140 dBm level (ATSC signal power level of -128 dBm). The detector is not noise limited. "False alarms" are caused by detection of distant TV transmitters when the DSA system is located outside the Grade B contour. Based on analysis results from data recorded from six independent locations in Northern Virginia and 13 ATSC channels.

Dynamic spectrum access has been proposed to address the spectrum scarcity. Based on this access mode, secondary users are allowed to opportunistically operate when primary users are absent. Secondary Users are, however, required to relinquish the spectrum upon return of the incumbent spectrum holder. Although it improves spectrum utility, opportunistic spectrum access limits secondary users' access to exogenous spectrum holes vacated by primary users. We argue that spectrum holes should be endogenous, enabled by incentives to incumbent users to increase spectrum availability, while mitigating risk. To this end, we take a different perspective on dynamic spectrum sharing and propose a coopetive framework, whereby primary and secondary users engage in a cooperative, yet competitive, auction-driven spectrum sharing to enhance spectrum usage. In this framework, the primary users'spectrum is organized in three bands, namely exclusive usage, usage right and management right bands. Based on this structure, spectrum is traded as financial options to increase trading flexibility and capture the value primary and secondary users attach to spectrum access and usage. Spectrum trading between primary and secondary users is formalized as a utility maximization problem. Approximate solutions to this problem are derived and their performance is analyzed. The results show that spectrum trading, which combines revocable and exclusive leasing, provides higher utilities for both primary and secondary users.

Cognitive radio is an innovative technique for spectrum management which uses Dynamic Spectrum Access (DSA). DSA has the potential to mitigate the spectrum scarcity by letting the Secondary User (SU) access the idle spectrum unused by the Primary User (PU). DSA improves the spectrum efficiency via spectrum sensing and optimal spectrum access. Spectrum sensing should be perfect so that the SU does not cause interference to the PU. Moreover, the channel selected should be the best for maximising throughput of the SU. In this paper we consider a best channel selection problem in Cognitive Radio Networks (CRNs). The problem is modelled as optimal stopping problem where the controller at each state can stop or continue sensing based on the channel gains achieved. There is a Markovian relation given between the channel occupancies of PU. The stopping rule comes out to be simple threshold rule. The controller stops sensing when the channel gain exceeds the given threshold.

As the novel and effective approach to improving the utilization of the precious radio spectrum, cognitive radio technology is the key to realize the dynamic spectrum access (DSA) networks, where the secondary (unlicensed) users can opportunistically utilize the unused licensed spectrum in a way that confines the level of interference to the range the primary (licensed) users can tolerate. However, there are many new challenges associated with cognitive-radio-based DSA networks, such as the multi-channel hidden terminal problem and the fact that the time-varying channel availability differs for different secondary users, in the medium access control (MAC) layer. To overcome these challenges, we propose an efficient Cognitive Radio-EnAbled Multi-channel MAC (CREAM-MAC) protocol, which integrates the cooperative sequential spectrum sensing at physical layer and the packet scheduling at MAC layer, over the wireless DSA networks. Under the proposed CREAM-MAC protocol, each secondary user is equipped with a cognitive radio-enabled transceiver and multiple channel sensors. Our cooperative sequential spectrum sensing scheme improves the accuracy of spectrum sensing and further protects the primary users. The proposed CREAM-MAC enables the secondary users to best utilize the unused frequency spectrum while avoiding the collisions among secondary users and between secondary users and primary users. We develop the Markov chain model and M/GY/1 queueing model to rigorously study our proposed CREAM-MAC protocol for both the saturation networks and the non-saturation networks. We also conduct extensive simulations to validate our developed protocol and analytical models.

Modern wireless networks are notorious for being very dense, uncoordinated, and selfish, especially with greedy user needs. This leads to a critical scarcity problem in spectrum resources. The Dynamic Spectrum Access system (DSA) is considered a promising solution for this scarcity problem. With the aid of Unmanned Aerial Vehicles (UAVs), a post-disaster surveillance system is implemented using Cognitive Radio Network (CRN). UAVs are distributed in the disaster area to capture live images of the damaged area and send them to the disaster management center. CRN enables UAVs to utilize a portion of the spectrum of the Electronic Toll Collection (ETC) gates operating in the same area. In this paper, a joint transmission power selection, data-rate maximization, and interference mitigation problem is addressed. Considering all these conflicting parameters, this problem is investigated as a budget-constrained multi-player multi-armed bandit (MAB) problem. The whole process is done in a decentralized manner, where no information is exchanged between UAVs. To achieve this, two power-budget-aware PBA-MAB) algorithms, namely upper confidence bound (PBA-UCB (MAB) algorithm and Thompson sampling (PBA-TS) algorithm, were proposed to realize the selection of the transmission power value efficiently. The proposed PBA-MAB algorithms show outstanding performance over random power value selection in terms of achievable data rate.

In Dynamic Spectrum Access (DSA) policy, a secondary user (SU) is allowed to access the primary user (PU) channel when it is idle. This access has to be disruption free for the PU. Literature on DSA focuses on PU and SU signal interferences as the main source of disruption. However the idle state may result from a non-transmitting activity such as the case where the primary user is in the Backoff Window in CSMA/CA networks. This particular idle state can be wrongly seen as an opportunity for SU to access the channel. However, accessing the channel in this context will cause Hidden Collision (HC) and will decrease the primary user performance. In this paper, we extend our previous work on HC and propose to distinguish the PU behaviour, modeled as a three states process, from the channel evolution modeled as an ON/OFF process. To combine these two interdependent processes we use the Hidden Markov Model (HMM) and we propose a solution to predict the PU state and therefore reduce the hidden collision effect. As a proof of concept, our approach accuracy is evaluated using a set of inputs obtained from simulation. We demonstrate the ability of the model to predict accurately enough the PU state and reduce hidden collision.