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TOC Alert for Publication# 4105970 2016June 23<![CDATA[Channel estimation for multi-input multi-output relay systems using the PARATUCK2 tensor model]]>10999510021050<![CDATA[Feasibly efficient cooperative spectrum sensing scheme based on Cholesky decomposition of the correlation matrix]]>10910031011645<![CDATA[Fairness enhanced dynamic routing and spectrum allocation in elastic optical networks]]>10910121020958<![CDATA[Construction of time-invariant rate-compatible-low-density parity-check convolutional codes]]>m, which is considered as the given encoding memory. The base code of this family is first obtained by modifying a given construction of a time-invariant LDPC convolutional code. Afterwards, the authors derive the other extended component codes by successively adding extra information bits into the base code. In particular, each component code in the family not only enables the property of fast encoding that can dramatically reduce the implementation complexity, but has the given encoding memory m for each parity-check bit that can remarkably improve the error performance as well. They also demonstrate that the Tanner graph for all the codes in the family is free of girth 4. Simulation results indicate that the proposed family of RC-LDPC convolutional codes collectively offers a desirable performance improvement as compared with the existing counterparts over the binary-input additive Gaussian noise channels under BP decoding.]]>10910211026556<![CDATA[Reliable routing in wireless sensor networks based on coalitional game theory]]>ad hoc on-demand distance vector routing and the method proposed by Kazemeyni. The results show that RCFR effectively enhances packet delivery ratio, decreases routing establishing time, balances energy consumption, and reduces average signalling overhead.]]>10910271034445<![CDATA[Hybrid user association for maximising energy efficiency in heterogeneous networks with human-to-human/machine-to-machine coexistence]]>10910351043654<![CDATA[Utility-based opportunistic spectrum access for cognitive radio sensor networks: joint spectrum sensing and random access control]]>JS^{2}RAC) in cognitive radio sensor networks (CRSNs). The JS^{2}RAC is formulated as a network utility maximisation problem, which aims to maximise the sum of utilities over all links in the network but subject to the primary user protection constraint, the energy constraint, and the physical constraint. Due to the non-separable and non-convex nature of the JS^{2}RAC problem, the authors propose a primal-decomposition-based iterative (PDI) algorithm which decomposes the JS^{2}RAC problem into a spectrum sensing subproblem and a random access control subproblem, and solve the two subproblems iteratively. Then, the authors prove the convergence of the PDI algorithm and show its distributed implementation in practice. Simulations demonstrate the fast convergence and the near-optimal nature of the PDI algorithm and show its significant improvement in the network utility of CRSNs in comparison with the method of optimising spectrum sensing and random access separately.]]>10910441052354<![CDATA[Design of optimised multiple partial recovery LT codes]]>d in each decoding step is calculated by an iterative optimisation algorithm. Under the proposed design, R(R < k) input symbols can be recovered from as few encoded symbols as possible in PR-LTC with message length k. Furthermore, multiple PR-LTC (M-PR-LTC) is proposed to recover several partial recovery point (PRPs) efficiently. The analysis process is divided into multiple stages, and the required number of encoded symbols with degree d in each decoding step is calculated by a cross-stage iterative optimisation algorithm. In addition, the interaction of each stage is adjusted by introducing a weight for each PRP. The PR-LTC and M-PR-LTC are evaluated and compared with the existing schemes. The simulation results demonstrate that PR-LTC and M-PR-LTC outperform other existing schemes in terms of average overhead, average degree of encoded symbols, memory usage, bit error rate and energy consumption.]]>10910531062879<![CDATA[Improving the quality of service for users in cognitive radio network using priority queueing analysis]]>10910631070995<![CDATA[Performance of multiple active-spatial modulation: information theoretic criteria over correlated Rayleigh fading channels]]>10910711079722<![CDATA[Recursive construction of optimal frequency-hopping sequence sets]]>10910801086160<![CDATA[Contract-auction based distributed resource allocation for cooperative communications]]>10910871095559<![CDATA[Performance analysis of free space optical communication in open-atmospheric turbulence conditions with beam wandering compensation control]]>Q-factor and bit error rate variation profiles are calculated using the signal statistics obtained from the eye-diagram. The performance improvements on the FSOC system due to the incorporation of BWC control are investigated and discussed in terms of various communication quality assessment key parameters.]]>10910961103740<![CDATA[Joint energy-efficient resource allocation and interference alignment for HetNets]]>10911041110466<![CDATA[Cross-layer aware joint design of sensing and frame durations in cognitive radio networks]]>109111111201004<![CDATA[Uplink symbol error rate analysis of multicell multiuser-multiple-input–multiple-output systems with minimum mean square error receiver under pilot contamination]]>10911211129477