Adaptive OFDM Beamformer with Constrained Weights for Cognitive Radio

Lian, Xiaohua; Nikookar, H.; Ligthart, L.P.; Zhou, Jianjiang

doi:10.1109/vetecs.2009.5073362

Cited by 10 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in Fig. 4, if one set of weight w i for the ith OFDM subcarrier is computed, others will be deduced by mapping them into different frequency bands via transformation matrix T. Thus the beamforming calculation will be performed only K times for all K SS, which requires less computation load and consumes less time [24].…”

Section: Uplink and Downlink Adaptive Beamforming For I-wimaxmentioning

confidence: 99%

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

Lian

Nikookar

Ligthart

2011

Wireless Pers Commun

Self Cite

View full text Add to dashboard Cite

In this paper, we introduce Adaptive Beamforming (AB) and Distributed Beamforming (DB) as two efficient techniques for Intelligent WiMAX (I-WiMAX). I-WiMAX is a new maritime communication system, consisting of Smart Radio (SR) principles and mobile WiMAX based on the IEEE 802.16e standard. Adopting AB, the same spectrum can accommodate more users by directing the main beam towards desired users while antenna pattern nulls towards others. To reduce the channel interferences caused by spectrum reusing, the Null Broadening (NB) method is required for downlink beamforming of I-WiMAX. A new NB method is presented in this paper with iterative weights computing for different OFDM subcarriers. Considering the spatial channel model seen at Subscriber Stations (SS) based on the von Mises distribution, the coverage range of one Base Station (BS) is dramatically enlarged by employing the NB technique. Meanwhile, assuming those SS which are within the coverage range as nodes of a relay network, the DB technique is introduced to forward signals to distant SS by forming the main beams towards them instead of deploying more BS to increase the communication range. It is proven in this paper that DB can successfully do the job. To reuse the spectrum, two DB methods are presented by directing different beams towards different required directions at the same time. With the AB and DB techniques, reliable I-WiMAX links can be established for long distances, with more optimum spectrum use and less infrastructure.

show abstract

Section: Uplink and Downlink Adaptive Beamforming For I-wimaxmentioning

confidence: 99%

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

Lian

Nikookar

Ligthart

2011

Wireless Pers Commun

Self Cite

View full text Add to dashboard Cite

show abstract

“…SUs transmit signals through the null-space of the channels seen between SUs and the PU base station. Lian et al [6] also use null steering for SUs to avoid interference to PUs. Furthermore, Zarrebini-Esfahani et al [19] control interference to PUs, located outside but within the close vicinity of cognitive cell borders, by beamforming, i.e., null steering, to enhance cell-edge user coverage in cellular CRNs.…”

Section: Introductionmentioning

confidence: 99%

On effects of imperfect channel state information on null space based cognitive MIMO communication

Sodagari¹

2015

2015 International Conference on Computing, Networking and Communications (ICNC)

View full text Add to dashboard Cite

Abstract-In cognitive radio networks, when secondary users transmit in the null space of their interference channel with primary user, they can avoid interference. However, performance of this scheme depends on knowledge of channel state information for secondary user to perform inverse waterfilling. We evaluate the effects of imperfect channel estimation on error rates and performance degradation of primary user and elucidate the tradeoffs, such as amount of interference and guard distance. Results show that, based on the amount of perturbation in channel matrices, performance of null space based technique can degrade to that of open loop MIMO. Outcomes presented in this paper also apply to null space based MIMO radar waveform design to avoid interference with commercial communication systems, operating in same or adjacent bands.Index Terms-ognitive radio, MIMO communications, null space projection, channel state information, perturbation theory.ognitive radio, MIMO communications, null space projection, channel state information, perturbation theory.C

show abstract

“…In fact it will be hidden to them and will be visible only to the respective target of cognitive users. Cognitive radio utilizes 2 International Journal of Distributed Sensor Networks beamforming techniques to generate main beam along the direction of cognitive user and nulls towards primary users as discussed in [9,10]. The cognitive user will be effective only when it cleverly occupied the vacant spectrum efficiently [11,12] in accordance with the latest spectrum sharing or accessing technique.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Sharing in Cognitive Radio Using GSC with Suppressed Sidelobes

Hussain

Malik

Khan

et al. 2014

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Cognitive radio system is an innovative technology in the wireless communication that has the capability to smartly communicate with each other by opportunistically exploiting the vacant spectrum of primary users. In this work we present a new idea of sidelobe suppression applicable for cognitive users on transmitter and receiver sides. In case of spectrum sharing with the primary users by suppressing the side-lobes at the transmitter and receiver side, the cognitive users will be able to increase the throughput without cooperating the permissible interference temperature limit of the license spectrum. We suggest two generalized sidelobe cancellers (GSCs) that operate in parallel. The first GSC planned to attain the two conflicting objective at the same moment: firstly maximize the cognitive users self throughput; secondly minimize the interference generated by cognitive users at each primary receiver. The second GSC generates two main beams at the positions of the highest amplitude sidelobes of the first one. The values of main beams are equal to the two sidelobe peaks. The subtraction of the outputs of the two GSCs, results in the suppression of the highest pair of sidelobes. This process is repeated iteratively to result in an adaptive algorithm. Simulation results are there to provide the effectiveness of the proposed algorithm.

show abstract

Adaptive OFDM Beamformer with Constrained Weights for Cognitive Radio

Cited by 10 publications

References 11 publications

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

On effects of imperfect channel state information on null space based cognitive MIMO communication

Spectrum Sharing in Cognitive Radio Using GSC with Suppressed Sidelobes

Contact Info

Product

Resources

About