Downlink Of Cognitive Radio Network Research Articles

Resource Allocation for Throughput Maximization in Cognitive Radio Network with NOMA

Spectrum resources are the precious and limited natural resources. In order to improve the utilization of spectrum resources and maximize the network throughput, this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonal multiple access (CRN-NOMA). NOMA, as the key technology of the fifth-generation communication (5G), can effectively increase the capacity of 5G networks. The optimization problem proposed in this paper aims to maximize the number of secondary users (SUs) accessing the system and the total throughput in the CRN-NOMA. Under the constraints of total power, minimum rate, interference and SINR, CRN-NOMA throughput is maximized by allocating optimal transmission power. First, for the situation of multiple sub-users, an adaptive optimization method is proposed to reduce the complexity of the optimization solution. Secondly, for the optimization problem of nonlinear programming, a maximization throughput optimization algorithm based on Chebyshev and convex (MTCC) for CRN-NOMA is proposed, which converts multi-objective optimization problem into single-objective optimization problem to solve. At the same time, the convergence and time complexity of the algorithm are verified. Theoretical analysis and simulation results show that the algorithm can effectively improve the system throughput. In terms of interference and throughput, the performance of the sub-optimal solution is better than that of orthogonal-frequency-division-multiple-access (OFDMA). This paper provides important insights for the research and application of NOMA in future communications.

Linear Precoding for the Downlink of Cognitive Radio Network

In this paper, a multiple-input–single-output (MISO) overlay cognitive radio (CR) network is considered in which a primary base station (PBS) and a cognitive base station (CBS) share the same spectrum to transmit the information. We consider a novel linear precoding technique to cannel the interferences which is bring about by the CBS’s transmission. Three theorems about the design of the precoding and decoding matrices are put forward. With the linear precoding and decoding, the BER performance of the PBS and CBS are improved significantly. At the same time, the capacity of the PBS and CBS channels are analyzed.

Resource allocation for heterogeneous services in multiuser cognitive radio networks

SUMMARYThis paper considers a downlink cognitive radio network consisting of one cognitive base station and multiple secondary users (SUs) that shares spectrum with a primary network. Unlike most of previous studies that focus on the SUs that carry only one type of service, in this paper, the SUs that carry heterogeneous services are considered. Specifically, the SUs are classified by service types, that is, the SUs that carry nonreal‐time services and the SUs that carry real‐time services. The QoS of the nonreal‐time SUs is guaranteed by the minimum mean rate constraint, whereas the QoS of the real‐time SUs is guaranteed by the minimum instantaneous rate constraint. Under this setup, a joint subchannel, rate, and power allocation scheme based on dual optimization method is proposed to minimize the mean transmit power consumption of the cognitive base station. The complexity of the proposed scheme is linear in the number of subchannels and the number of SUs. Extensive simulation results are provided to validate the proposed resource allocation scheme. Copyright © 2012 John Wiley & Sons, Ltd.

Per-Subcarrier Antenna Selection for H.264 MGS/CGS Video Transmission Over Cognitive Radio Networks

In this paper, the problem of efficiently allocating wireless resources to support multiple scalable video sequences over a downlink cognitive radio network is addressed. We consider the coarse grain scalable (CGS) and medium grain scalable (MGS) extension of the H.264 standard as the encoding method and propose to perform a per-subcarrier transmit antenna selection such that spatial diversity is exploited. We formulate the problem of optimally allocating subcarriers and antennas among secondary users as a binary integer program, where optimality is defined in terms of the aggregate visual quality of received video sequences of all cognitive users. The proposed formulation caters to the staircase rate-distortion characteristics of CGS/MGS sequences and avoids allocating more resources than are necessary to attain a given visual quality. However, due to the high computational complexity involved in solving this hard integer program using discrete programming solvers, we reduce the resource allocation problem to a subset-sum problem. Although it remains -hard in general, we present two efficient methods to solve this subset-sum problem based on its structure. Simulation results demonstrate that the methods proposed lead to a solution that is close to the optimal. Moreover, we demonstrate that having multiple antennas at the cognitive base station reduces the outage probability of secondary users.

Power Allocation Schemes For Downlink Cognitive Radio Networks With Opportunistic Sub-channel Access

This paper considers a downlink cognitive radio (CR) network where one secondary user (SU) and one primary user (PU) share the same base station (BS). The spectrum of interest is divided into a set of independent, orthogonal subchannels. The communication of the PU is of high priority and the quality of service (QoS) is guaranteed by the minimum rate constraint. On the other hand, the communication of the SU is of low priority and the SU opportunistically accesses the subchannels that were previously discarded by the PU during power allocation. The BS assigns fractions ?? and ?? of the total available transmit power to the PU and the SU respectively. Two power allocation schemes with opportunistic subchannel access are proposed, in which the optimal values of ??’s are also obtained. The objective of one scheme is to maximize the rate of the SU, and the objective of the other scheme is to maximize the sum rate of the SU and the PU, both under the PU minimum rate constraint and the total transmit power constraint. Extensive simulation results are obtained to verify the effectiveness of the proposed schemes.

SINR Balancing Technique for Downlink Beamforming in Cognitive Radio Networks

We propose a novel signal to interference and noise (SINR) balancing technique for a downlink cognitive radio network (CRN) wherein multiple cognitive users (also referred to as secondary users (SUs)) coexist and share the licensed spectrum with the primary users (PUs) using the underlay approach. The proposed beamforming technique maximizes the worst SU SINR while ensuring that the interference leakage to PUs is below specific thresholds. Due to the additional interference constraints imposed by PUs, the principle of uplink-downlink duality used in the conventional downlink beamformer design cannot be directly applied anymore. To circumvent this problem, using an algebraic manipulation on the interference constraints, we propose a novel SINR balancing technique for CRNs based on uplink-downlink iterative design techniques. Simulation results illustrate the convergence and the optimality of the proposed beamformer design.

Joint beamforming and scheduling in the downlink of cognitive radio networks

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization. In this paper, we consider a system where a licensed radio spectrum is shared by a primary network and a secondary network. Based on the subspace theory, a novel low-complexity algorithm for secondary user selection has been proposed. On the basis of the scheduling scheme, we jointly consider transmit beamforming, scheduling and power allocation, and subsequently present a complete set of solution for secondary network downlink. Simulation results has shown that our proposed scheme not only can limit the introduced interference at primary users within the tolerable range, but also can achieve high sum-rate throughput of secondary network, simultaneously. Furthermore, as is proved by simulation results, our scheme is very robust due to the fact that only a little tolerable performance drop is introduced when simple but nonoptimal equal power allocation is adopted.