Rate and Energy Efficient Power Control in a Cognitive Radio Ad Hoc Network

Montejo‐Sánchez, Samuel; Souza, Richard Demo; Fernández, Evelio; Reguera, Vitalio Alfonso

doi:10.1109/lsp.2013.2251630

Cited by 34 publications

(16 citation statements)

References 15 publications

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“…When the instantaneous channel coefficients are not available, an average EE is defined as the ratio of the average transmission rate (or throughput) to the average transmit and consumed circuitry power (or energy) [2,7,[39][40][41]47]. For example, for an SC SISO scenario where an SU overlays a PU and concurrent transmission is required, the average EE is defined as [40] …”

Section: Energy Efficiency (Ee) Metricsmentioning

confidence: 99%

“…In such a case, transmit power [1,27,34,35,40,45], signal-to-interference-plus-noise ratio (SINR) threshold [22], frequency bands/subcarriers [9,25,44,49], and/or packet length [38] are optimized separately or jointly in order to improve the CR system energy efficiency.…”

Section: Sensing-less Energy-aware Resource Allocationmentioning

confidence: 99%

“…Other systems that adapt the power may not employ OFDM(A) to access the available spectrum in CR networks [1,22,35,40]. In such cases, single carrier for SISO systems [40] or MIMO systems [1,22,35] can be used.…”

Section: Power Allocation Of Single Carrier Systemsmentioning

confidence: 99%

“…In such cases, single carrier for SISO systems [40] or MIMO systems [1,22,35] can be used. For example, an interference-limited spectrum sharing CR ad-hoc network is considered in [40], where simultaneous transmission between an SU pair and a PU pair is requested. A forbidden transmission region around the PU receiver is defined, where no SU transmission is allowed to guarantee the PU QoS.…”

Section: Power Allocation Of Single Carrier Systemsmentioning

confidence: 99%

See 3 more Smart Citations

Energy-Aware Cognitive Radio Systems

Bedeer

Amin

Dobre

et al. 2016

Energy Management in Wireless Cellular and Ad-Hoc Networks

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The concept of energy-aware communications has spurred the interest of the research community in the most recent years due to various environmental and economical reasons. It becomes indispensable for wireless communication systems to shift their resource allocation problems from optimizing traditional metrics, such as throughput and latency, to an environmental-friendly energy metric. Although cognitive radio systems introduce spectrum efficient usage techniques, they employ new complex technologies for spectrum sensing and sharing that consume extra energy to compensate for overhead and feedback costs. Considering an adequate energy efficiency metric-that takes into account the transmit power consumption, circuitry power, and signaling overhead-is of momentous importance such that optimal resource allocations in cognitive radio systems reduce the energy consumption. A literature survey of recent energy-efficient based resource allocations schemes is presented for cognitive radio systems. The energy efficiency performances of these schemes are analyzed and evaluated under power budget, co-channel and adjacentchannel interferences, channel estimation errors, quality-of-service, and/or fairness constraints. Finally, the opportunities and challenges of energy-aware design for cognitive radio systems are discussed.

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Section: Energy Efficiency (Ee) Metricsmentioning

confidence: 99%

Section: Sensing-less Energy-aware Resource Allocationmentioning

confidence: 99%

Section: Power Allocation Of Single Carrier Systemsmentioning

confidence: 99%

Section: Power Allocation Of Single Carrier Systemsmentioning

confidence: 99%

See 2 more Smart Citations

Energy-Aware Cognitive Radio Systems

Bedeer

Amin

Dobre

et al. 2016

Energy Management in Wireless Cellular and Ad-Hoc Networks

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“…In some research related to resource allocation with SS, it has been shown that transmit power control can improve the efficiency of spectrum utilization and protect PUs [14][15][16][17][18][19][20][21][22][23][24]. In fact, proper transmit power control can protect PUs without spectrum sensing and increase opportunities of SS by SUs [20].…”

Section: Introductionmentioning

confidence: 99%

Analysis of transmit power setting technique for cognitive radio networks

Umebayashi

Lehtomäki

Suliman

2016

J Wireless Com Network

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We investigate a method to set the maximum allowable transmit power for a secondary base station in dynamic spectrum sharing among secondary users and primary users. In conventional methods, location information is assumed. Thus, the maximum allowable transmit power can be set by considering the shadowing between the secondary base station and the primary user receivers to satisfy a constraint. Specifically, the probability that the interference from secondary base station exceeds the acceptable level must be less than the constraint target probability. We assume that the location information is not available at the secondary network. Instead, the secondary base station uses the received signal strength from the primary user transmitter for distance estimation. In this case, we have to consider shadowing not only between the secondary base station and the primary user receivers, but also between the primary user transmitter and the secondary receiver(s). We also need to account for the uncertainty of the distance. In order to satisfy the constraint target probability, we proposed a two-step approach to setting the maximum allowable transmit power where a transmission decision margin and a transmit power margin are utilized. To reduce these margins, we also propose cooperative maximum allowable transmit power setting method utilizing also received signal strength values from several secondary users. Simulation results confirm the validity of the analysis and show the effectiveness of the proposed cooperative maximum allowable transmit power setting method, i.e., the capacity based on cooperative maximum allowable transmit power setting method is significantly better than that of non-cooperative maximum allowable transmit power setting method. In addition, we show a proper size of radius of additional separation area to protect primary users by the numerical results.

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Energy‐efficient outage‐constrained power allocation based on statistical channel knowledge for dual‐hop cognitive relay networks

Bordon

Montejo‐Sánchez

Mafra

et al. 2015

Int J Communication

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This paper investigates the power allocation problem in decode-and-forward cognitive dual-hop systems over Rayleigh fading channels. In order to optimize the performance of the secondary network in terms of power consumption, an outage-constrained power allocation scheme is proposed. The secondary nodes adjust their transmit power subject to an average interference constraint at the primary receiver and an outage probability constraint for the secondary receivers while having only statistical channel knowledge with respect to the primary nodes. We compare this approach with a power allocation scheme based on instantaneous channel state information under a peak interference constraint. Analytical and numerical results show that the proposed approach, without requiring the constant interchange of channel state information, can achieve a similar performance in terms of outage probability as that of power allocation based on instantaneous channel knowledge. Moreover, the transmit power allocated by the proposed approach is considerably smaller than the power allocated by the method based on instantaneous channel knowledge in more than 50% of the time.perspective [11] but also from the economic point of view. Therefore, minimizing the energy consumption for wireless data transmission becomes one of the most important design goals in WSNs, aiming at maximizing the battery lifetime. Because the transmit power is a relevant fraction of the total consumed energy, power allocation (PA) plays an important role towards achieving the aforementioned goal. Related worksSeveral recent works investigate the outage behavior of cooperative cognitive networks under different relaying protocols, number of available relays, channel models, and interference conditions, as for instance, [12][13][14][15][16][17][18]. In [12], it is investigated the outage performance of a multi-relay network under Rayleigh fading channels in a noise-limited environment, as well as the impact of imperfect channel state information (CSI) on the system performance. The authors in [13] carry out an analysis about the capacity and outage behavior of a decode-and-forward (DF) dual-hop system in a scenario where the SUs are subject to interference imposed by the PU. Similar to [13], the presence of PU interference is also considered in [14], but the authors show that increasing the number of relays can compensate the performance degradation caused by the PU interference. The diversity order and outage performance of a single relay dual-hop system in a noise-limited scenario under Nakagamim fading are investigated in [15]. Considering the presence of multiple primary transmitters (PTs) and receivers, the outage performance of DF systems is evaluated in [16]. In all these works, the transmit power of the SUs is adjusted to its maximum allowed value such that the peak interference at the primary receiver (PR) remains below the required constraint. However, this approach requires global CSI at the secondary network, of all the related channel coefficients, but perf...

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Rate and Energy Efficient Power Control in a Cognitive Radio Ad Hoc Network

Cited by 34 publications

References 15 publications

Energy-Aware Cognitive Radio Systems

Energy-Aware Cognitive Radio Systems

Analysis of transmit power setting technique for cognitive radio networks

Energy‐efficient outage‐constrained power allocation based on statistical channel knowledge for dual‐hop cognitive relay networks

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