Top PDF Low Error Rate Data Transmission in Cognitive Radio Networks

Low Error Rate Data Transmission in Cognitive Radio Networks

Low Error Rate Data Transmission in Cognitive Radio Networks

E-mail: nandhume@gmail.com ABSTRACT Cognitive Radio (CR) has become a hopeful technology to enhance the spectrum utilization through spectrum sharing between licensed user (primary user) and unlicensed user (secondary user). An vital rule mandated for the development of such frameworks are to develop solutions that don’t require any changes to the existing primary user (PU) infrastructure. An Orthogonal Frequency Division Multiplexing (OFDM) is typically worn advancements in present wireless communication systems which has the possibility of fulfilling the demand for cognitive radios intrinsically or with slight changes. In this paper, Space time block codes is used. The various antennas used on both ends for trustworthy data broadcast and interference nulling schemes. These codes can accomplish full broadcast diversification determined via the number of broadcast antennas. The MIMO is worn for enhancing the power of a wireless link, to determine the issue for lower BER and achieve a superior performance.
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Self Organising Cognitive Radio Networks

Self Organising Cognitive Radio Networks

It was highlighted in [6], [51], and [94] that the power amplifier uses a significant portion of the energy used in a Macro-cell base station. The high amount of power is used to reach highly shadowed and high path loss destinations. The measurements conducted in [95] on network interface card (NIC) concluded that the RF power level should be at its lowest since it reduces the power consumption of power amplifier and it was also noted in [96] that the battery life is inversely proportional to the transmit power. Therefore to maximise the battery life (or total fixed amount of energy consumed in the case of externally powered nodes), each node has to reduce transmit power to a fixed level, which in some circumstances may result in a lower, but more energy efficient data rate per unit bandwidth. For these reasons, the scope of the energy consumption model of a device is limited to the transmission/reception components of wireless devices and combining all the various electronic components into a single module. The proposed radiated energy consumption model will be highly affected by the external radio environment unlike that of [20], [21].
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Error rate analysis of cognitive radio transmissions with imperfect channel sensing

Error rate analysis of cognitive radio transmissions with imperfect channel sensing

With this motivation, we in this paper study the symbol error rate performance of cognitive radio transmissions in the presence of imperfect channel sensing decisions. We assume that secondary users first sense the channel in order to detect the primary user activity before initiating their own transmis- sions. Following channel sensing, secondary users employ two different transmission schemes depending on how they access the licensed channel: sensing-based spectrum sharing (SSS) and opportunistic spectrum access (OSA). In the SSS scheme [18], cognitive users are allowed to coexist with primary users in the channel as long as they control the interference by adapting the transmission power according to the channel sensing results. More specifically, secondary users transmit at two different power levels depending on whether the channel is detected as busy or idle. In the OSA scheme [19], cognitive users are allowed to transmit data only when the channel is detected as idle, and hence secondary users exploit only the silent periods in the transmissions of primary users, called as spectrum opportu- nities. Due to the assumption of imperfect channel sensing, two types of sensing errors, namely false alarms and miss detections, are experienced. False alarms result in inefficient utilization of the idle channel while miss-detections lead to cognitive users’ transmission interfering with primary user’s signal. Such interference can be limited by imposing interference power constraints.
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Optimal Policy of Cross-Layer Design for Channel Access and Transmission Rate Adaptation in Cognitive Radio Networks

Optimal Policy of Cross-Layer Design for Channel Access and Transmission Rate Adaptation in Cognitive Radio Networks

The transmission model for every CR user is shown in Figure 1. At the data link layer, for the transmission capacity analysis, the infinite bu ff er of the transmitter is assumed to be continually backlogged with packets that must be transmit- ted to the base station and the channel selection is decided by every CR user. At the physical layer, the CR users operate over the selected parallel block fading channels and send data to the CR base station. These channels compose one (or a part of) licensed channel. To maximize the spectral e ffi ciency, adaptive modulation (AM) [20] is utilized for each selected channel. In centralized case, the base station makes the whole decision. In decentralized case, the intelligent controller in each CR user performs cross-layer channel selection and rate selection in frame-by-frame manner. Furthermore, the intel- ligent controller should include some extra function blocks. First, the controller should calculate the immediate reward and cost for the optimal policy design. Second, in order to reduce complexity, the function block of action set reduction and state aggregation should be included in the intelligent controller. Finally, in the case that the traffic load parameters of licensed users are unknown, the controller should estimate them.
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Spectrum sharing in cognitive radio networks

Spectrum sharing in cognitive radio networks

In a cell-wide scenario, we quantified the expected interference and outage prob- ability for a randomly placed PUE and SBS. The additional PUE outage is low compared to the natural outage of the macrocell, indicating the potential for mul- tiple FC activity. The results indicate that the sensing requirement can be relaxed in the case of a single FC with cell radii > 1500m. Conservative setting of the sensing threshold (0dB) reduces SBS transmission opportunities and in the case of small cells makes the FC as good as useless (always off). To quantify the SBS trans- mission opportunities in a shadow fading environment, a heuristic approximation is presented for the distance distribution between two uniformly scattered points. The resulting unwieldily expression for the transmission opportunity is simplified to a Skew Normal Distribution using central moment matching. This hypothesis is verified through the Kolmogorov- Smirnov goodness of fit test with an error of less than 2%.
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Spectrum Sensing and Error Rate Analysis by Cognitive Radio Users using Welchs Power Spectral for High Data Rate Applications

Spectrum Sensing and Error Rate Analysis by Cognitive Radio Users using Welchs Power Spectral for High Data Rate Applications

With the increasing demand for high quality of services (Qos) and data rates there occurs spectrum overcrowding due to the prevalent use of static spectrum allocation methods which does not allow unlicensed users to use licensed spectrum. There are two types of users- primary user and secondary user. Primary users are licensed user whereas secondary users are unlicensed user. Sometimes the spectrum is unused by the primary user, the spectrum becomes unutilized. With the consideration of increasing demand of spectrum by the users, by using cognitive radio we are able to maintain the demands in the nearby future. Cognitive radio allows the secondary users to use the spectrum which is unutilized by the primary users. Spectrum sensing is the core of cognitive radio which means detection of free spectrum. For detection purpose Energy detection technique is used. Initially conventional periodogram technique is used for the better transmission and reception of signal. In this survey we are defined to prove that Welch’s power spectral density technique is more efficient than conventional periodogram technique.
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On the effect of false alarm rate on the performance of cognitive radio networks

On the effect of false alarm rate on the performance of cognitive radio networks

In [18], continuous time Markovian process (CTMP) is used to model PU traffic in opportunistic spectrum access (OSA) systems. However, for analyzing SU’s behavior, dis- crete time queuing was used. In contrary to our work, the underlying assumption made therein is that sensing and data transmission cannot be carried out simultane- ously and therefore the SU has to periodically suspend its data transmission in order to perform spectrum sens- ing. The problems with this technique are the overheads associated with the scheduling and synchronization of the suspension periods among SUs as well as the frequent interruption in the SU’s data transmission. Additionally, the SU can only detect a reappearing PU during the sus- pension period, even if the PU reappeared before the suspension period. This work also differs from our study because it only supports CRNs with one channel and the assumption that the spectrum sensing is perfect.
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Applications and Opportunities for Cognitive Radio and Networks

Applications and Opportunities for Cognitive Radio and Networks

∑ (2) The delay performance of the proposed cognitive MAC is shown in Fig. 3. All SUs use the same sensing window [0, 31] without service differentiation. As it is very complicated to track the number of SUs in each data channel due to highly dynamic spectrum access in CR networks, we use the average number of SUs to estimate the contention level in each channel. It can be seen that the analytical results approximate the simulation ones well. It can be seen that the average delay of voice/video traffic increases with the number of SUs. The delay of voice packets are low because small voice packets are more likely to be transmitted opportunistically when PUs are inactive. For video traffic with much larger payloads, the probability of transmission failure becomes high as a PU is more likely to turn on and interfere with the SU during a longer transmission time of a video packet. When a transmission fails, an SU will switch to the next channel for sensing and retransmission, which results in a longer delay. It is also shown that in comparison with fractional (FRC) scheme which senses the channel in the descending order of the average channel available time, the proposed QC MAC achieves much lower delay because SUs always select a proper set of channels that assure high probability of successful frame transmissions, while only the average channel utilization is considered in FRC.
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Video Transmission using Priority Scheduling for Improvement of QoS in Cognitive Radio Networks

Video Transmission using Priority Scheduling for Improvement of QoS in Cognitive Radio Networks

Using network simulator random 100 to 400 cognitive nodes were randomly generated and simulation results were obtained. Two data traffic rates have been analyzed in this proposed scheme: Hypertext Transfer Protocol and File Transfer Protocol. Here HTTP uses variable bit rate where as constant bit rate is used by FTP for data transmissions. The Broadcast Protocol for CRNs (BRACER) and the QoS-Based Prioritization Model (QBPM) are the two existing approaches which are compared with the proposed scheme. The QoS parameters of overhead rate, delivery ratio, throughput, end-to-end delay, network efficiency and probability of collision are analyzed to determine the performance of CRN. Table1 shows the parameters of routing and their range.
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An Extensive Review on Cognitive Radio Networks

An Extensive Review on Cognitive Radio Networks

Despite the fact that the call handoff plans have been researched altogether in cell systems, there exist numerous tests that must be examined for the improvement of range handover techniques.[1,2] The range handover methodology ought to be straightforward and low confused, which ensures continuous operation and snappy choices. The execution assessment of a range handover methodology ought to be investigated by numerical demonstrating. The first and key assignment is to perform correct and quick range sensing, so as to focus the range inhabitance of authorized essential clients (Pus) and recognize transmission chances for optional CRs. Range sensing confronts significant tests from the debasing impacts of remote channel blurring. A solitary CR client will most likely be unable to exactly sense and catch the transmission of an essential framework because of channel blurs [3]. The point when a missed identification emerges, the CR client might unwittingly transmit over the same channel utilized by animated Pus, bringing about impeding obstruction to legacy administrations. Henceforth, multi CR helpful sensing is proposed to successfully battle blurring by means of client spatial differences [4, 5]. The point when channel state data (CSI) from the Pus to CR recipients might be gained, the CRs can together gauge the basic transmitted range of the essential framework from their exclusively accepted estimation vectors, which is the broadly contemplated agreeable estimation issue. The point when the CSI is distracted, CRs can just choose the range inhabitance of the PU frameworks, showed by the nonzero backing of the transmitted rang Cognitive radio (CR) is a key engineering for lightening wasteful range usage under the current static range assignment arrangement.
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Bit Error Rate of Underlay Decode-and-Forward Cognitive Networks with Best Relay Selection

Bit Error Rate of Underlay Decode-and-Forward Cognitive Networks with Best Relay Selection

end, the involved SUs can typically operate in three different modes: interweave; overlay; and underlay [3]. Due to the advan- tageous feature of low implementation complexity, the under- lay mode has recently attracted a notable deal of attention, e.g. [3–17] and the references therein. In this mode, SUs must adap- tively control their transmit power in order for the induced in- terference to be strictly maintained within levels that can be tol- erated by PUs. This ultimately leads to the drastically shortened transmission range of SUs, which can be compensated in turn with the aid of cooperative relaying techniques [18]. Indeed, by taking advantage of intermediate users − so called relays − lo- cated between the source and the destination to relay source in- formation, underlay relaying cognitive networks can overcome the aforementioned drawback thanks to the resulting short range communication with low path-loss effects. The relays can op- erate according to various cooperative relaying schemes such as the decode-and-forward (DF) and amplify-and-forward (AF) [19]. In the former scheme, the relays decode the received sig- nal and then re-encode the decoded information before relaying it to the destination. In the latter scheme, the relays just am- plify the received signal and forward it to the destination. It is recalled here that cooperative relaying with selection of a single relay among a set of possible candidates requires less system resources, such as bandwidth and power, than multi-relay as- sisted transmission while maintaining the same diversity order [3, 20–23].
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Voice Capacity and Data Response Time in Cognitive Radio Networks

Voice Capacity and Data Response Time in Cognitive Radio Networks

Introduction elastic data service. A performance analysis of elastic data traffic in non-cognitive networks is carried out in [66]. Different bandwidth sharing techniques based on maximum throughput, min-max fairness, proportional fairness, and weighted fairness are considered in the analysis. The mean response time evaluation of elastic data traffic flows is studied for cellular/WLAN integrated networks in [29] . The network supports streaming and elastic data traffic flows, and the data files are served in processor sharing service discipline. A mean response time approximation for the SRPT service discipline under a heavy traffic condition is given in [67] (and references there in). In all these works, the short-term mean channel rate available for a data user does not vary with time, and therefore the long-term mean channel rate is used for the response time analysis. However, in CRNs the channel availability for SUs varies with time due to the interruptions by the PUs (bursty PU traffic), and the short-term mean channel availability deviates from the long-term mean channel availability. Therefore, the effect of the transmission interruptions caused by the PUs should be considered in the analysis. In [27], the mean throughput and delay of transmission control protocol (TCP) and constant bit rate connections are analyzed for CRNs with on-off PU behaviors. However, there aren’t many research efforts devoted on the performance analysis of elastic data traffic over CRNs. From the viewpoint of the SUs in a CRN, the available channel time can be considered as a ser- vice with break downs. The expected queue lengths and related operating characteristics of a queuing station with breakdown are studied in [68], which can also be applied in the context of CRNs. Further, the relationship between the queuing station with breakdown and a single server queuing system with preemptive priorities is also studied. However, the work in [68] is limited to the FCFS service discipline, which is not always the best service discipline. In all these works, the mean of the response time is considered as the service quality parameter, due to the complexity of analyzing its probability distribution.
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A Sensing Error Aware MAC Protocol for Cognitive Radio Networks

A Sensing Error Aware MAC Protocol for Cognitive Radio Networks

protocols to fully capitalize CR’s potential. In order to exploit transmission opportunities in licensed bands, the tension between primary user protection and secondary user spectrum access should be judiciously balanced. Spectrum sensing and spectrum access are the two key CR functions. Important design factors include (i) how to identify transmission opportunities, (ii) how secondary users determine, among the licensed channels, which channel(s) and when to access for data transmission, and (iii) how to avoid harmful interference to primary users under the omnipresent of spectrum (or, channel) sensing errors. These are the problems that should be addressed in the medium access control (MAC) protocol design for CR networks. Although very good understandings on the availability process of licensed channels have been gained recently [4, 5], there is still a critical need to develop analytical models that take channel sensing errors into account for guiding the design of CR MAC protocols.
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Utility-maximizing data dissemination in socially selfish cognitive radio networks

Utility-maximizing data dissemination in socially selfish cognitive radio networks

In this paper, we consider social selfishness of secondary users in cognitive radio networks, based on which we design a joint end-to-end rate control, routing, and channel allocation protocol that can maximize the overall throughput utility of multiple unicast sessions. Our design is rooted in Lyapunov optimization theory [16], where utility maximization and net- work stability are achieved by back-pressure scheduling of transmissions among packet queues at the network nodes. We incorporate social selfishness of users in their transmission scheduling of packets belonging to different by-passing data sessions, according to the social ties between the users and the source/destination of each session. In particular, social prefer- ence of a user is novelly addressed by allocating differentiated buffer sizes and relay rates to different data sessions.
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An efficient transmission mode selection based on reinforcement learning for cooperative cognitive radio networks

An efficient transmission mode selection based on reinforcement learning for cooperative cognitive radio networks

and the destination. They evaluate the performance of their algorithm based on the per- fect and the estimated CSI for both amplify-and forward (AF) and decode-and-forward (DF) protocols. In [5], the authors propose a joint relay selection (RS) with opportunistic source selection for an AF-based network in terms of outage probability and BER. Simi- larly in [6], the optimal RS scheme for maximizing the effective signal-interference-to- noise-ratio (SINR) is proposed, which significantly improves the system performance of full-duplex relaying. In [7] the authors propose a detect-and-forward (DetF) RS system and derive the average bit error probability by using the closed-form relay link SNR, and shows BER performance with SNR. Energy-efficient multi relay selection with power allocation strategy according to the total transmission power constraint is studied in [9] which achieve high energy efficiency performance in both low and high SNR region. However, all of the relay selection schemes from [4–7] only consider a single metric such as BER or SER. Since actual wireless systems aim to achieving a multilateral metric for QoS, the existing schemes could not support in practice.
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Low Complexity Energy-Efficient Collaborative Spectrum Sensing for Cognitive Radio Networks

Low Complexity Energy-Efficient Collaborative Spectrum Sensing for Cognitive Radio Networks

terference to the PU within a target level. Moreover, the policy function was obtained using very simple real-time linear calculation which maps the instantaneous SINR to a proper en- ergy threshold. Simulation results revealed that the proposed method achieves a higher SU throughput compared to the fixed threshold based energy detector, while maintaining great stability in the probability of detection and probability of false alarm. In addition, the pro- posed algorithm in [47] was considered the detection error rate as a criterion to assess the performance of spectrum sensing algorithm. An optimal adaptive threshold level was de- termined to minimize the spectrum sensing error for given spectrum sensing constraint for a single CR. However, the individual CR user may not give accurate sensing results due to shadowing, multipath fading and hidden terminal problems of the wireless communication channel. Therefore, in [48] to deal with these problems, the proposed adaptive threshold approach had been analyzed under the cooperative spectrum sensing (CSS). Simulation re- sults showed that the probability of detection clearly improved when more than one CR involved in the spectrum sensing. However, all previously mentioned algorithms did not consider a compromise between detection performance and incurred energy consumption for CSS system.
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Sensing Algorithm for Cognitive Radio Networks based on Random Data Matrix

Sensing Algorithm for Cognitive Radio Networks based on Random Data Matrix

Conventional fixed spectrum allocation policy leads to low spectrum usage in many of the frequency bands. Cognitive radio, first proposed in [1], is a promising technology to exploit the under-utilized spectrum in an opportunistic manner [2]. One application of cognitive radio is spectral reuse, which allows secondary networks/users to use the spectrum allocated/licensed to the primary users when they are not active [3]. To do so, the secondary users are required to frequently perform channel sensing, i.e., detecting the presence of the primary users. If the primary users are found to be inactive, the secondary users can use the spectrum for communications. On the other hand, whenever the primary users become active, the secondary users have to detect the presence of those users in high probability, and vacate the channel within certain amount of time. One communication system using the spectrum reuse concept is IEEE 802.22 wireless regional area networks (WRAN) [4], which operates on the VHF/UHF bands that are currently allocated for TV broadcasting services and other services such as wireless microphone. To ensure that there will be no harmful interference to the primary user, the secondary users need to periodically detect (sense) the presence of the primary user. To do so, each medium access control frame consists of two sub frames - a channel sensing sub frame and a data transmission sub frame. There are several factors that prevent the spectrum sensing from operating in a reliable manner. One factor is that the strength of the primary users’ signals could be very weak when they reach the secondary users. This is due to the fact that wireless propagation suffers from multipath fading and shadowing loss. Therefore, the signal-to- noise ratio (SNR) of the primary users’ signal could be very
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A Low Cost Time Hopping Impulse Radio System for High Data Rate Transmission

A Low Cost Time Hopping Impulse Radio System for High Data Rate Transmission

The system that we are considering is a TH-IR system. We first describe “classical” TH-IR [4]. Each data bit is repre- sented by several short pulses; the duration of the pulses es- sentially determines the bandwidth of the (spread) system. For the single-user case, it would be sufficient to transmit a single pulse per symbol. However, in order to achieve good MA properties, we have to transmit a whole sequence of pulses. Since the UWB transceivers are unsynchronized, so- called “catastrophic collisions” can occur, where pulses from several transmitters arrive at the receiver, almost simultane- ously. If only a single pulse would represent one symbol, this would lead to a bad signal-to-interference ratio (SIR), and thus to a high bit error probability BER. These catastrophic collisions are avoided by sending a whole sequence of pulses instead of a single pulse. The transmitted pulse sequence is different for each user, according to a so-called TH code. Thus, even if one pulse within a symbol collides with a signal component from another user, other pulses in the sequence will not. This achieves an interference suppression gain that is equal to the number of pulses in the system. Figure 1 shows the operating principle of a generic TH-IR system. We see that the possible positions of the pulses within a symbol fol- low certain rules: the symbol duration is subdivided into N f
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CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks

CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks

Because CORA does not make use of MRR capabilities, after retrieving a random data rate R r, this rate will be used by all frame transmissions up to the next quality feedback loop iteration. This means that, for each packet, the seven frame transmission attempts (that is, retry count) will be performed using the same R r rate. If this rate does not work (as with a high rate in a low-quality link), then all frame transmis- sion attempts will fail, and the packet will be reported as discarded to the upper layers. In this case, the TCP protocol will interpret this as network congestion and will reduce the throughput. This is the main reason for CORA’s poor perfor- mance, especially just after the link-quality decreases (note that after t = 70 s, CORA’s throughput increases somewhat). On the contrary, CogTRA uses MRR. If the first four attempts fail (two for the random R r rate, and two for best rate so far), then the rate with the best success probability is used, pos- sibly resulting in a frame transmission success that avoids all performance degradation caused by the TCP protocol. Another CORA behavior that can be observed involves the instability in selecting random rates under average-quality signal. This is an immediate consequence of the high stan- dard deviation value, which is automatically adjusted by the ASA improvement in CogTRA.
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Error rate detection due to primary user emulation attack in cognitive radio networks

Error rate detection due to primary user emulation attack in cognitive radio networks

characteristic as primary signal. It causes SU has a difficulty to identify vacant spectrum. Malicious user does not utilize those vacant bands for its own communication purposes. They only transmit fake primary signal in vacant bands to obstruct SU from detecting original one. The existing works related to this issue have been done. Smart attacker was introduced in [17]. The authors use Markov chain technique to model the activities of attackers. Then, energy detection of attackers was investigated in [18]. The authors used NI-USRP 2922 devices to derive probability of detection and false alarm. Chen et al in [19] investigated the attackers which is considered as interference to result inaccurate position of primary user location. The authors implemented directional antenna to explore position of primary transmitter. The used parameter like angle, arrival time, and strength of signal is explored to detect an accurate position. An analytical of successful probability to attact primary user location was firstly studied by authors in [20]. Fading was considered into account to calculate successful probability of attackers and define a lower limit by applying Fenton’s and Markov approximation, respectively. CR signaling was introduced by authors in [21] to ease accessing available spectrum efficiently. The investigation proved that the framework is able to maximize SU transmission rate with low probility of miss detection and probability of false alarm. Using the statistical characteristic of users to prevent PUEA issue was proposed by Ghaznavi et al [22].
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