In this paper, we propose a new random beamforming scheme for multiuser multiple-input single-output block fading channels, e.g., a wireless downlink in a cellular communication system. Unlike previous methods it achieves spatial multiplexing gain over the complete range of realistic signal-to-noise ratios (SNRs) even for moderate user numbers. The main shortcoming of the random beamforming schemes for multiple datastreams proposed so far is their interference limitation, especially under medium and high SNR. The key to mitigate this problem in our scheme is to allow feedback of each user's channel gain in each random beam. This information suffices to determine the sum-rate maximizing subset of beams and users at the base station. In this sense, our scheme, referred to as orthonormal random beamforming with systematic beam selection, can be considered as optimal among all random beamforming schemes that do not make use of additional preprocessing at the transmitter (apart from power normalization). It achieves a significant performance gain compared to previous schemes particularly for realistic SNR values
Intelligent reflecting surface (IRS) has recently emerged as an appealing technique to control the random and time-varying channels in wireless communications. In this paper, we consider a new multi-IRS aided multiuser system, where a multi-antenna base station (BS) serves multiple distributed users with the aid of two types of IRSs, which are deployed near the BS and distributed users, thus referred to as the BS-side IRSs and user-side IRSs, respectively. Under such hybrid IRS deployment, the IRS-user association is crucial for maximizing the network throughput, where each user can be associated with no IRS, a BS-side IRS only, a user-side IRS only, or both BS- and user-side IRSs. To solve this problem, we jointly optimize the IRSuser associations and IRSs' passive beamforming to maximize the minimum effective channel gain among all users. Simulation results demonstrate the effectiveness of the proposed association design for multi-IRS aided multiuser systems under the hybrid IRS deployment.
Problem localization is a critical part of providing crucial system management capabilities to modern distributed environments. One key open challenge is for problem localization solutions to scale for systems containing hundreds or even thousands of nodes, whilst still remaining fast enough to resp
Since radio signals carry both energy and information at the same time, a unified study on simultaneous wireless information and power transfer (SWIPT) has recently drawn a significant attention for achieving wireless powered communication networks. In this paper, we study a multiple-input single-output (MISO) multicast SWIPT network with one multi-antenna transmitter sending common information to multiple single-antenna receivers simultaneously along with opportunistic wireless energy harvesting at each receiver. From the practical consideration, we assume that the channel state information (CSI) is only known at each respective receiver but is unavailable at the transmitter. We propose a novel receiver mode switching scheme for SWIPT based on a new application of the conventional random beamforming technique at the multi-antenna transmitter, which generates artificial channel fading to enable more efficient energy harvesting at each receiver when the received power exceeds a certain threshold. For the proposed scheme, we investigate the achievable information rate, harvested average power and/or power outage probability, as well as their various trade-offs in both AWGN and quasi-static fading channels. Compared to a reference scheme of periodic receiver mode switching without random transmit beamforming, the proposed scheme is shown to be able to achieve better rate-energy trade-offs when the harvested energy target is sufficiently large. Particularly, it is revealed that employing one single random beam for the proposed scheme is asymptotically optimal as the transmit power increases to infinity, and also performs the best with finite transmit power for the high harvested energy regime of most practical interests, thus leading to an appealing low-complexity implementation. Finally, we compare the rate-energy performances of the proposed scheme with different random beam designs.
This article presents a new method for designing a dual‐band WLAN antenna using the higher order harmonic mode of a monopole antenna, the first‐order mode of which operates at the low‐frequency band of WLAN (2.4 GHz). After measuring the current distribution in the higher order antenna mode, we added a stub in a location where the electric field is strong. This added stub brought the resonant frequency into the higher WLAN frequency band. Further, the input impedance was controlled by controlling the width of the branch without affecting the low‐frequency band of the WLAN (the first‐order mode of the monopole antenna). This compact dual‐band antenna was designed to be the size of a universal serial bus dongle, and the −10 dB bandwidths are 700 MHz (2.3–3 GHz) at 2 GHz and 1 GHz (4.9–5.9 GHz) at 5 GHz, which cover the full WLAN dual bands. The proposed antenna achieves more than 50% efficiency in WLAN bands. © 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:1897–1902, 2013
Ultra-dense (UD) wireless networks and cloud radio access networks (CRAN) are two promising network architectures for the emerging 5G wireless communication systems. By jointly employing UD network with CRAN, a new appealing network solution is proposed, termed UD-CRAN, which can achieve ultra-high-throughput wireless connectivity. In UD-CRAN, a wireless fronthaul is practically favorable to connect a central processor (CP) with distributed remote radio heads (RRHs), due to its lower cost and higher flexibility to deploy. As the wireless fronthaul capacity is limited, it motivates considering the downlink transmission in a UD-CRAN where the wireless fronthaul is shared among the RRHs via time division multiple access~(TDMA), while the RRHs jointly transmit to the users via orthogonal frequency division multiple access (OFDMA). The joint resource allocation over the TDMA-based wireless fronthaul and OFDMA-based wireless transmission is investigated to maximize the weighted sum rate of all users. Although the problem is combinatorial and non-convex, we propose a Lagrange duality based solution, which can be efficiently computed with good accuracy. To further reduce the complexity, we also propose a greedy search based heuristic, which achieves close to optimal performance under practical setups. Finally, we compare the performance of proposed solutions with other benchmark schemes by simulations, which show significant throughput gains of the proposed joint resource allocation approach.
This paper studies the optimized training design for multiple-input single-output (MISO) wireless energy transfer (WET) systems in frequency-selective channels, where the frequency-diversity and energy-beamforming gains can be both reaped by properly learning the channel state information (CSI) at the energy transmitter (ET). By exploiting channel reciprocity, a two-phase channel training scheme is proposed to achieve the diversity and beamforming gains, respectively. In the first phase, pilot signals are sent from the energy receiver (ER) over a selected subset of the available frequency sub-bands, through which the sub-band that exhibits the largest sum-power over all the antennas at the ET is determined and its index is sent back to the ER. In the second phase, the selected sub-band is further trained by the ER, so that the ET obtains an estimation for the MISO channel and implement energy beamforming. We propose to maximize the net energy harvested at the ER, which is the total harvested energy offset by that used for the two-phase channel training. The optimal training design, including the number of sub-bands trained and the energy allocated for each of the two training phases, is derived.
Microgrids are key components of future smart grids, which integrate distributed renewable energy generators to efficiently serve the load locally. However, the intermittent nature of renewable energy generations hinders the reliable operation of microgrids. Besides the commonly adopted methods such as deploying energy storage system (ESS) and supplementary fuel generator to address the intermittency issue, energy cooperation among microgrids by enabling their energy exchange for sharing is an appealing new solution. In this paper, we consider the energy management problem for two cooperative microgrids each with individual renewable energy generator and ESS. First, by assuming that the microgrids' renewable energy generation/load amounts are perfectly known ahead of time, we solve the off-line energy management problem optimally. Based on the obtained solution, we study the impacts of microgrids' energy cooperation and their ESSs on the total energy cost. Next, inspired by the off-line optimization solution, we propose online algorithms for the real-time energy management of the two cooperative microgrids. It is shown via simulations that the proposed online algorithms perform well in practice, have low complexity, and are also valid under arbitrary realizations of renewable energy generations/loads. Finally, we present one method to extend our proposed online algorithms to the general case of more than two microgrids based on a clustering approach.
This letter studies a multiuser multiple-input single-output (MISO) intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, a multi-antenna base station (BS) transmits data along with energy to a set of users to decode data and harvest energy by adopting the power splitting (PS) simultaneously. The energy efficiency indicator (EEI) is introduced to trade off between data rate and harvested energy, which is maximized by jointly optimizing beamforming vectors at the BS, PS ratio at each user, and phase shifts at the IRS. To solve this non-convex optimization problem, we first adopt the majorization-minimization (MM) approach to construct a concave-convex fractional function which can be handled via the Dinkelbach algorithm and then propose an efficient algorithm for solving two subproblems based on the alternating optimization (AO). For the first subproblem, semi-definite relaxation (SDR), MM approach, and Dinkelbach algorithm are adopted, while for the second sub-problem, a new manifold approach is proposed to handle the unit-modulus constraints due to IRS passive reflection. Simulation results demonstrate the superior performance of our proposed algorithm compared to other baseline schemes.
In orthogonal frequency-division multiplexing (OFDM) digital communication systems, an uncorrected frequency offset can lead to a severe degradation of the system performance. The paper describes a technique to mitigate the influence of frequency offset on system performance by applying a weighted discrete Fourier transform (DFT) to a novel OFDM frequency-assignment scheme in which null carriers are regularly inserted among modulated data carriers. This frequency-assignment scheme makes possible the application of a window function at the demodulator to broaden the signal spectrum and renders the demodulated signal more immune to the influence of frequency offset. In addition, a variant of this frequency-assignment scheme also leads to a DFT-based measurement technique for easy and accurate determination of the frequency offset. Interpolation algorithms and frequency-assignment schemes suitable for both initial frequency acquisition and subsequent frequency tracking are described in detail. The Rife and Vincent (Class-I) windows (see Rife, D.C. and Vincent, G.A., Bell Syst. Tech. J., vol.49, p.197-228, 1976) are examined and their estimation results are obtained for an additive white Gaussian noise (AWGN) and a multipath fading channel.
Ultra-dense (UD) wireless networks and cloud radio access networks (CRAN) are two promising network architectures for the emerging fifth-generation wireless communication systems. By jointly employing them, a new appealing network solution is proposed in this paper, termed UD-CRAN. In a UD-CRAN, millimeter-wave (mmWave) wireless fronthaul is preferred for information exchange between the central processor and the distributed remote radio heads (RRHs), due to its lower cost and higher flexibility in deployment, compared with fixed optical links. This motivates our study in this paper on the downlink transmission in a mmWave fronthaul enabled, orthogonal frequency division multiple access (OFDMA)-based UD-CRAN. In particular, the fronthaul is shared among the RRHs via time division multiple access (TDMA), while the RRHs jointly transmit to the users on orthogonal frequency sub-channels using OFDMA. The joint resource allocation over the TDMA-based mmWave fronthaul and OFDMA-based wireless transmission is investigated to maximize the weighted sum rate of all users. Although the problem is non-convex, we propose a Lagrange duality-based solution, which can be efficiently computed with good accuracy. To further reduce the complexity, we also propose a greedy search-based heuristic, which achieves close to optimal performance under practical setups. Finally, we show the significant throughput gains of the proposed joint resource allocation approach compared with other benchmark schemes by simulations.
This paper studies the performance limits of multi-antenna wireless broadcasting systems for simultaneous information and power (energy) transfer. For the purpose of exposition, a three-node network is investigated, in which one receiver harvests energy and another receiver decodes information separately from the signals broadcast by a common transmitter. Two scenarios are examined, where the information receiver and energy receiver are separated and see different channels from the transmitter, or co-located and see the same channel from the transmitter. For the case of separated receivers, we derive the optimal transmission strategies to achieve different tradeoffs for maximal information rate versus energy transfer, which are characterized by the boundary of a so-called rate-energy (R-E) region. For the case of co-located receivers, we show an outer bound for the achievable R-E region, due to the potential limitation that practical circuits for harvesting energy from radio signals are not yet able to decode the carried information at the same time. Under this constraint, we propose two practical receiver designs for the co-located receivers, namely, time switching and power splitting, and characterize their achievable R-E regions in comparison with the outer bound.
