Transceiver Designs to Improve Spectrum Utilization in MIMO Interference Channels

2015 ◽  
Vol 1 ◽  
pp. 47
Author(s):  
Le Ty Khanh ◽  
Ha Hoang Kha ◽  
Nguyen Minh Hoang
Keyword(s):  
Multiple Input Multiple Output ◽  
Primary User ◽  
Radio Spectrum ◽  
Interference Channels ◽  
Spectrum Utilization ◽  
Secondary Users ◽  
Interference Level ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Interference Channels

This paper is concerned with a multiple-input multiple-output (MIMO) multi-user wireless networks in which multiple secondary users (SUs) can share the same radio spectrum with a single primary user (PU). The design problems of the transceivers in such MIMO interference channels are to find the precoding matrices at the transmitters and the receiving matrices at the receivers to minimize the mean square error (MSE) or to maximize the sum-rate of the SUs while guaranteeing the interference power at the PU receiver below an acceptable threshold. In this paper, we consider to design the transceivers using the interference alignment techniques. The objective is to align the interference at the SUs and maintain an acceptable leakage interference level from the SUs into the signal subspace of the PU receiver. Due to the nonlinearity and nonconvexity of the underlaying problems, we develop an alternating algorithm which efficiently solves a convex optimization in each iteration. The numerical results are provided to validate the performance of our algorithm.

scholarly journals Secure Beamforming in 5G-Based Cognitive Radio Network

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1260
Author(s):  
Hyils Sharon Magdalene Antony ◽  
Thulasimani Lakshmanan
Keyword(s):  
Cognitive Radio ◽  
Information Exchange ◽  
Cognitive Radio Network ◽  
Multiple Input Multiple Output ◽  
Primary User ◽  
Radio Network ◽  
Secrecy Rate ◽  
Secondary Users ◽  
Input Multiple Output ◽  
The Impact

Cognitive radio network (CRN) and non-orthogonal multiple-access (NOMA) is a significant system in the 5G wireless communication system. However, the system is an exceptional way for the cognitive users to secure a communication from the interferences in multiple-input multiple-output (MIMO)-NOMA-based cognitive radio network. In this article, a new beamforming technique is proposed to secure an information exchange within the same cells and neighboring cells from all intervened users. The interference is caused by an imperfect spectrum sensing of the secondary users (SUs). The SUs are intended to access the primary channels. At the same time, the primary user also returns to the channel before the SUs access ends. This similar way of accessing the primary channel will cause interference between the users. Thus, we predicted that the impact of interferences would be greatly reduced by the proposed technique, and that the proposed technique would maximize the entire secrecy rate in the 5G-based cognitive radio network. The simulation result provides better evidence for the performance of the proposed technique.

scholarly journals Use Hierarchical Codebook to Improve the Primary User Detection in the Cognitive Radio’s Cooperative Spectrum Sensing

2021 ◽  
Vol 5 (6) ◽  
pp. 22-28
Author(s):  
Hoai Trung Tran
Keyword(s):  
Spectrum Sensing ◽  
Channel Model ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Primary User ◽  
Mimo Channel ◽  
High Signal ◽  
Secondary Users ◽  
Input Multiple Output

Currently, the cognitive network is receiving much attention due to the advantages it brings to users. An important method in cognitive radio networks is spectrum sensing, as it allows secondary users (SUs) to detect the existence of a primary user (PU). Information of probability of false detection or warning about the PU is sent to a fusion center (FC) by the SUs, from which the FC will decide whether or not to allow the SUs to use the PU spectrum to obtain information. The transmission of information with a high signal to noise ratio (SNR) will increase the FC's ability to detect the existence of the PU. However, researchers are currently focusing on probabilistic formulas assuming that the channel is known ideally or there is nominal channel information at the FC; moreover, one model where the FC only knows the channel correlation matrix. Furthermore, studies are still assuming this is a simple multiple input – multiple output (MIMO) channel model but do not pay much attention to the signal processing at the transmitting and receiving antennas between the SUs and the FCs. A new method introduced in this paper when combining beamforming and hierarchical codebook makes the ability to detect the existence of the PU at the FC significantly increased compared to traditional methods.

Optimal Beam-Forming Design in Cognitive Relay Networks under Interference Threshold

2013 ◽  
Vol 850-851 ◽  
pp. 561-566
Author(s):  
Zi Jun Liu ◽  
Zhan Gao ◽  
Guo Xin Li ◽  
Hai Tao Zhang
Keyword(s):  
Multiple Input Multiple Output ◽  
Relay Networks ◽  
Primary User ◽  
Primary Data ◽  
Mimo Antenna ◽  
Cognitive Relay Networks ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Optimal Beam ◽  
Cognitive User

Recently, a new model for cognitive radio networks appears, in which a cognitive user (CU) can relay the primary data stream to improve the performance of the primary user s communication. Traditionally, the transmitter of the cognitive users will send data to the receiver of the cognitive users and relay the data sent from the primary user (PU) in different time slots. However, Multiple Input Multiple Output (MIMO) provides a remarkable increase in the spectral efficiency, which can transmit multiple independent data streams in a time slot with MIMO antenna. Based on the MIMO technique, we propose a novel framework, in which the cognitive user near by the primary user is equipped with MIMO antenna. In this paper, we search for the maximum sum-rate of the cognitive user, limiting the interference to the primary users. Simulation results show that the proposed method can really improve the performance of the cognitive relay networks.

scholarly journals Rank-Constrained Beamforming for MIMO Cognitive Interference Channel

2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Duoying Zhang ◽  
Yao Zhang ◽  
Zujian Wu ◽  
Huiqin Du
Keyword(s):  
Spectrum Sharing ◽  
Optimization Problems ◽  
Multiple Input Multiple Output ◽  
Interference Channel ◽  
Cognitive Interference ◽  
Secondary Users ◽  
Interference Temperature ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Rank Constraints

This paper considers the spectrum sharing multiple-input multiple-output (MIMO) cognitive interference channel, in which multiple primary users (PUs) coexist with multiple secondary users (SUs). Interference alignment (IA) approach is introduced that guarantees that secondary users access the licensed spectrum without causing harmful interference to the PUs. A rank-constrained beamforming design is proposed where the rank of the interferences and the desired signals is concerned. The standard interferences metric for the primary link, that is,interference temperature, is investigated and redesigned. The work provides a further improvement that optimizes the dimension of the interferences in the cognitive interference channel, instead of the power of the interference leakage. Due to the nonconvexity of the rank, the developed optimization problems are further approximated as convex form and are solved via choosing the transmitter precoder and receiver subspace iteratively. Numerical results show that the proposed designs can improve the achievable degree of freedom (DoF) of the primary links and provide the considerable sum rate for both secondary and primary transmissions under the rank constraints.

Performance Analysis of Ground Moving Target Detection for Airborne MIMO Radar

2012 ◽  
Vol 229-231 ◽  
pp. 1414-1418
Author(s):  
Cong Cong Li ◽  
Jun Li ◽  
Chao Hai Li ◽  
Wen Jun Huang
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Experimental Simulation ◽  
Moving Target ◽  
Interference Level ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Slow Moving ◽  
Ground Moving Target Detection ◽  
Ground Moving Target Indication

The performance of a Ground Moving Target Indication (GMTI) radar is determined by the interference level of the clutter to a large extent. With the longer illumination and the larger aperture, Multiple-Input, Multiple-Output (MIMO) radar greatly enhances the ability to detect the slow-moving target. This paper compares MIMO radar with conventional phased-array radar in terms of signal to clutter and noise ratio (SCNR) performance. Moreover, the paper proves the fact that the improvement of SCNR with MIMO techniques is not only limited in the antenna configuration of the side-looking but also non-sidelooking array-antenna. The analysis of mianlobe clutter and sidelobe clutter levels can greatly simplify the computation of the total clutter. Finally, the experimental simulation is been given.

Optimal RF Beamforming for MIMO

2013 ◽  
pp. 165-172
Author(s):  
Javad Ahmadi-Shokouh
Keyword(s):  
Cognitive Radio ◽  
Computer Simulations ◽  
Interference Cancellation ◽  
Multiple Input Multiple Output ◽  
Spatial Multiplexing ◽  
Secondary Users ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results ◽  
Beamforming Technique

Secondary receivers in Multiple-Input Multiple-Output (MIMO) Cognitive Radio (CR) networks combat interference from primary transmitters while equipped with whitening filters. However, when the MIMO secondary users are employing Radio Frequency (RF) beam-forming networks at the transmitter/receiver front ends to improve the MIMO transmission performance, the whitening filters cannot perform interference cancellation. In this chapter, transmit/receive optimum RF beamforming is proposed for a MIMO spatial multiplexing system. The performance of the optimally designed RF beamforming technique is evaluated over a Rician channel via computer simulations. Simulation results are assessed for different RF beamforming structures and the number of primary transmitters causing interference on the secondary receiver.

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