No abstract

In this paper, we propose an adaptive orthogonal frequency-division multiplexing (OFDM) index modulation (IM) scheme for two-hop relay networks. In contrast to the traditional OFDM IM scheme with a deterministic and fixed mapping scheme, in this proposed adaptive OFDM IM scheme, the mapping schemes between a bit stream and indices of active subcarriers for the first and second hops are adaptively selected by a certain criterion. As a result, the active subcarriers for the same bit stream in the first and second hops can be varied in order to combat slow frequency-selective fading. In this way, the system reliability can be enhanced. Additionally, considering the fact that a relay device is normally a simple node, which may not always be able to perform mapping scheme selection due to limited processing capability, we also propose an alternative adaptive methodology in which the mapping scheme selection is only performed at the source and the relay will simply utilize the selected mapping scheme without changing it. The analyses of average outage probability, network capacity and symbol error rate (SER) are given in closed form for decode-and-forward (DF) relaying networks and are substantiated by numerical results generated by Monte Carlo simulations. Index Terms

In this paper, we propose a novel scheme termed layered orthogonal frequency division multiplexing with index modulation (L-OFDM-IM) to increase the spectral efficiency (SE) of OFDM-IM systems. In L-OFDM-IM, all subcarriers are first divided into multiple layers, each determining the active subcarriers and their modulated symbols. The IM bits are carried on the indices of the active subcarriers of all layers, which are overlapped and distinguishable with different signal constellations so that the number of the IM bits is larger than that in traditional OFDM-IM. A low-complexity detection is proposed to alleviate the high burden of the optimal maximumlikelihood detection at the receiver side. A closed-form upper bound on the BER, the achievable rate and diversity order are derived to characterize the performance of L-OFDM-IM. To enhance the diversity performance of L-OFDM-IM, we further propose coordinate interleaving L-OFDM-IM (CI-L-OFDM-IM), which interleaves the real and imaginary parts of the modulated symbols over two different subchannels. Computer simulations verify the theoretical analysis, whose results show that L-OFDM-IM outperforms the conventional OFDM-IM scheme. Moreover, it is also confirmed that CI-L-OFDM-IM obtains an additional diversity order in comparison with L-OFDM-IM.

In this paper, we propose a novel codebook design scheme for orthogonal frequency-division multiplexing with index modulation (OFDM-IM) to improve system performance. The optimization process can be implemented efficiently by the lexicographic ordering principle. By applying the proposed codebook design, all subcarrier activation patterns with a fixed number of active subcarriers will be explored. Furthermore, as the number of active subcarriers is fixed, the computational complexity for estimation at the receiver is reduced and the zero-active subcarrier dilemma is solved without involving complex higher layer transmission protocols. It is found that the codebook design can potentially provide a trade-off between diversity and transmission rate. We investigate the diversity mechanism and formulate three diversity-rate optimization problems for the proposed OFDM-IM system. Based on the genetic algorithm (GA), the method of solving these formulated optimization problems is provided and verified to be effective. Then, we analyze the average block error rate (BLER) and bit error rate (BER) of OFDM-IM systems applying the codebook design. Finally, all analyses are numerically verified by Monte Carlo simulations. In addition, a series of comparisons are provided, by which the superiority of the codebook design is thereby confirmed.

With the development of smart grid, demand-side resources (DSR) will play an increasingly important role in the power balance of supply and demand. In addition, the requirement of a low-carbon smart grid means some policy backgrounds, such as carbon emissions trading (CET), should not be ignored. Under these circumstances, it is a good idea to construct a novel unit commitment (UC) model. This paper proposes a model that not only takes advantage of various resources on the demand side, such as electric vehicles, demand response, and distributed generation, but also reflects the effects of CET on generation schedule. Then, an improved particle swarm optimization (IPSO) algorithm is applied to solve the problem. In numerical studies, we analyze the impacts of DSR and CET on the results of UC, respectively. In addition, two meaningful experiments are conducted to study the approaches to allocate emission quotas and the effects of price transmission mechanism. Index Terms-Carbon emission quotas, carbon emissions trading (CET), demand response (DR), distributed generation (DG), electric vehicle (EV), improved particle swarm optimization (IPSO), smart grid, unit commitment (UC). NOMENCLATURE Index bIndex of bus. i Index of generating unit. j Index of electric vehicle (EV). t Index of hour. Variables and Functions DGa t Distributed generation (DG) used by its owners at time t. DGb t Output of grid-connected DG at time t. DGC Total cost (TC) of DG. DRC TC of demand response (DR). Emission of unit i at time t. E V2G,t Emission of vehicle-to-grid (V2G) at time t. FC i Fuel cost of unit i. I i,t On/off status of unit i at time t. Iter Current number of iteration. pc Probability of crossover. P i,t Output of unit i at time t. pm Probability of mutation. SC i,t Start-up cost of unit i at time t. SoC t,j State of charge of EV j at time t. TC TC of unit commitment (UC). V2GC TC of V2G. V2G t Output of V2G at time t. V2G t,j Output of V2G of EV j at time t. X on i,t , X off i,t Duration of continuously on/off of unit i at time t. η t Penetration rate of DG at time t.

Millimetre wave (mmWave) is a promising technology to meet the ever-growing data traffic in the future. A major challenge of mmWave communications is the high path loss. In order to overcome this issue, mmWave systems often adopt beamforming techniques, which require robust channel estimation and beam tracking algorithms to maintain an adequate quality of service. This paper proposes a framework of channel estimation and beam tracking for mmWave communications. The proposed framework is designed for vehicular to infrastructure communication but can be extended to other applications as well. First, we propose a multi-stage adaptive channel estimation algorithm called robust adaptive multi-feedback (RAF). The algorithm is based on using the estimated channel coefficient to predict a lower bound for the required number of measurements. Our simulations demonstrate that compared with the existing algorithms, RAF can achieve the desired probability of estimation error (PEE), while on average reducing the feedback overhead by 75.5% and the total channel estimation time by 14%. Second, after estimating the channel in the first step, the paper follows by investigating the extended Kalman filter (EKF) for beam tracking in vehicular communications. A crucial part of EKF is the calculation of Jacobian matrices. We show that the model used in the previous work, which was based on the angles of arrival and departure, is not suitable for vehicular communications. This is due to the complexity in the calculation of Jacobian matrices. A new model is proposed for EKF in mmWave vehicular communications which is based on position, velocity and channel coefficient. Closed-form expressions are derived for the Jacobians used in EKF which facilitate the implementation of the EKF tracking algorithm in the proposed model. Finally, we provide an extensive number of simulations to substantiate the robustness of the framework as well as presenting the analytical results on the PEE of the RAF algorithm.Index Terms-Millimeter wave, multiple-input multiple-output (MIMO), channel estimation, beamforming, analog beamforming, beam tracking, Extended Kalman filter (EKF).

Quadrature spatial modulation (QSM) is recently proposed to increase the spectral efficiency (SE) of SM, which extends the transmitted symbols into in-phase and quadrature domains. In this paper, we propose a generalized QSM (GQSM) scheme to further increase the SE of QSM by activating more than one transmit antenna in in-phase or quadrature domain. A low-complexity detection scheme for GQSM is provided to mitigate the detection burden of the optimal maximum-likelihood (ML) detection method. An upper bounded bit error rate is analyzed to discover the system performance of GQSM. Moreover, by collaborating with the non-orthogonal multiple access (NOMA) technique, we investigate the practical application of GQSM to cooperative vehicular networks and propose the cooperative GQSM with OMA (C-OMA-GQSM) and cooperative GQSM with NOMA (C-NOMA-GQSM) schemes. Computer simulation results verify the reliability of the proposed low-complexity detection as well as the theoretical analysis, and show that GQSM outperforms QSM in the entire SNR region. The superior BER performance of the proposed C-NOMA-GQSM scheme make it a promising modulation candidate for next generation vehicular networks.

No abstract