Frequency control is essential to maintain the stability and reliability of power grids. For decades, generation side controllers, e.g., isochoronous governors and automatic generation controllers, have been used to stabilize the frequency of power systems, which, however, incur high operational costs. In smart grids, demand response can be used to control frequency and thus reduce the grids' dependency on expensive controllers. Despite of its economic advantages, the synchronization problem, which is due to the simultaneous responses of smart appliances, becomes the main barrier to implementing frequency responsive demand control in reality. In this paper, we propose a distributed control algorithm for smart appliances, based on the randomized frequency monitoring and a baseline hysteresis algorithm, to solve the synchronization problem. We provide analytical results to characterize the influence of distributed demand response on the system frequency dynamics. Finally, we validate our analysis and demonstrate the effectiveness of our proposed algorithm via simulations on the Ireland power system.
Consider a static wireless network that has two tiers with different priorities: a primary tier vs. a secondary tier. The primary tier consists of randomly distributed legacy nodes of density $n$, which have an absolute priority to access the spectrum. The secondary tier consists of randomly distributed cognitive nodes of density $m=n^β$ with $β\geq 2$, which can only access the spectrum opportunistically to limit the interference to the primary tier. By allowing the secondary tier to route the packets for the primary tier, we show that the primary tier can achieve a throughput scaling of $λ_p(n)=Θ(1/\log n)$ per node and a delay-throughput tradeoff of $D_p(n)=Θ(\sqrt{n^β\log n}λ_p(n))$ for $λ_p(n)=O(1/\log n)$, while the secondary tier still achieves the same optimal delay-throughput tradeoff as a stand-alone network.
This paper studies the transmit strategy for a secondary link or the so-called cognitive radio (CR) link under opportunistic spectrum sharing with an existing primary radio (PR) link. It is assumed that the CR transmitter is equipped with multi-antennas, whereby transmit precoding and power control can be jointly deployed to balance between avoiding interference at the PR terminals and optimizing performance of the CR link. This operation is named as cognitive beamforming (CB). Unlike prior study on CB that assumes perfect knowledge of the channels over which the CR transmitter interferes with the PR terminals, this paper proposes a practical CB scheme utilizing a new idea of effective interference channel (EIC), which can be efficiently estimated at the CR transmitter from its observed PR signals. Somehow surprisingly, this paper shows that the learning-based CB scheme with the EIC improves the CR channel capacity against the conventional scheme even with the exact CR-to-PR channel knowledge, when the PR link is equipped with multi-antennas but only communicates over a subspace of the total available spatial dimensions. Moreover, this paper presents algorithms for the CR to estimate the EIC over a finite learning time. Due to channel estimation errors, the proposed CB scheme causes leakage interference at the PR terminals, which leads to an interesting learning-throughput tradeoff phenomenon for the CR, pertinent to its time allocation between channel learning and data transmission. This paper derives the optimal channel learning time to maximize the effective throughput of the CR link, subject to the CR transmit power constraint and the interference power constraints for the PR terminals.
No abstract is provided for this article.
Six-dimensional movable antenna (6DMA) is a promising technology to fully exploit spatial variation in wireless channels by allowing flexible adjustment of three-dimensional (3D) positions and rotations of antennas at the transceiver. In this paper, we investigate the practical low-complexity design of 6DMA-enabled communication systems, including transmission protocol, statistical channel information (SCI) acquisition, and joint position and rotation optimization of 6DMA surfaces based on the SCI of users. Specifically, an orthogonal matching pursuit (OMP)-based algorithm is proposed for the estimation of SCI of users at all possible position-rotation pairs of 6DMA surfaces based on the channel measurements at a small subset of position-rotation pairs. Then, the average sum logarithmic rate of all users is maximized by jointly designing the positions and rotations of 6DMA surfaces based on their SCI acquired. Different from prior works on 6DMA which adopt alternating optimization to design 6DMA positions/rotations with iterations, we propose a new sequential optimization approach that first determines 6DMA rotations and then finds their feasible positions to realize the optimized rotations subject to practical antenna placement constraints. Simulation results show that the proposed sequential optimization significantly reduces the computational complexity of conventional alternating optimization, while achieving comparable communication performance. It is also shown that the proposed SCI-based 6DMA design can effectively enhance the communication throughput of wireless networks over existing fixed (position and rotation) antenna arrays, yet with a practically appealing low-complexity implementation.
With the fast development of Radio Frequency Identification(RFID) and tag usage,security has become the key issue for RFID related applications.In this paper,a new RFID secure protocol is proposed,which uses a synchronized random number created in the backend system,for tag authentication.After tag successful authentication each time,both tag and random number update synchronously.Meanwhile,the performance and security of the protocol are analyzed theoretically.Also the BAN logic is used to prove its security in further.The result show that this protocol can provide authentication between tag and reader,moreover,it can resist attacks such as replay,location tracking,traffic analysis,counterfeiting,denial of service,and illegal access,etc.From the implementation point,it just uses Hash and exclusive XOR operations,which reduces the computing complexity and makes it fitting for low price tags applications.
Millimeter-wave (mmWave) communication has emerged as a promising candidate for next-generation wireless systems due to the availability of large bandwidth, while cloud radio access network (CRAN), in which low-complexity remote radio heads (RRHs) are deployed to serve users in a distributed manner, is a cost-effective solution to achieve network densification. However, for a CRAN operating over a large bandwidth in the mmWave frequencies, the fronthaul links would be easily saturated by the large amount of sampled and quantized signals to be transferred between RRHs and the central processor. To tackle this problem, we propose in this paper a new architecture for mmWave CRAN with advanced lens antenna arrays at the RRHs. With the energy focusing property, lens antenna arrays are effective in exploiting the angular sparsity of the mmWave channel to simplify the signal processing required to achieve high data rates with multiple antennas, even when the channel is frequency selective. We consider the uplink transmission in a mmWave CRAN with lens antenna arrays and propose a low-complexity quantization bit allocation scheme for multiple antennas at each RRH to meet the stringent fronthaul rate constraint. We compare the proposed mmWave CRAN using lens antenna arrays, with a conventional CRAN using uniform planar arrays at the RRHs, and show that the proposed design achieves significant throughput gains with much lower complexity.
A Linearly Time-varying (LTV) channel estimation model with Inter-carrier Interference (ICI) mitigation is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems in this paper. The proposed method utilizes an iterative procedure with lower complex ICI calculation to mitigate ICI in time-varying channel estimation. It can evidently reduce the complexity of conventional iterative methods for ICI mitigation which has to find invert of matrix. Simulation results show that the proposed method reaches a compromise between complexity and estimation accuracy. It has approximative performance with conventional iterative methods while reducing the complexity, and obtains lower estimation deviation than typical LTV model without iterative procedure.
Multiuser diversity (MD), as a fundamental property of fading wireless networks, has been widely applied in today's wireless communication systems. In this letter, we consider the newly emerging cognitive radio (CR) wireless network that communicates by sharing the spectrum with the existing primary radio (PR) network. Under the assumption that the CR transmit terminal protects the PR transmission by applying the interference-power constraint at the PR receiver, this letter demonstrates several new forms of multiuser diversity in the spectrum sharing CR networks, named {\it multiuser interference diversity} (MID), which are resulted by the mutual interferences between the CR and PR networks and are thus not present in the conventional wireless networks. Three types of CR multiuser networks are considered, including the multiple-access channel (MAC), broadcast channel (BC), and parallel-access channel (PAC), for which this letter characterizes the transmit MID (T-MID), receive MID (R-MID), and combined T-MID and R-MID, respectively. It is shown that thanks to the new discovered MID, the MD in each CR network of interest can be substantially larger than that in the conventional networks, while their resultant diversity gain ratio is upper-bounded by some determinable value that is constant regardless of the number of CR users.
This paper studies the energy management in coordinated multipoint (CoMP) systems powered by smart grids, where each base station (BS) with local renewable energy generation is allowed to implement two-way energy trading with the grid. Due to the uneven renewable energy supply and communication energy demand over distributed BSs, as well as the difference in the prices for their buying/selling energy from/to the grid, it is beneficial for the cooperative BSs to jointly manage their energy trading with the grid and energy consumption in CoMP-based communication for reducing the total energy cost. Specifically, we consider the downlink transmission in one CoMP cluster by jointly optimizing the BSs' purchased/sold energy units from/to the grid and their cooperative transmit precoding to minimize the total energy cost subject to the given quality-of-service (QoS) constraints for the users. First, we obtain the optimal solution to this problem by developing an algorithm based on techniques from convex optimization and uplink-downlink duality. Next, we propose a suboptimal solution of lower complexity than the optimal solution, where zero-forcing (ZF)-based precoding is implemented at the BSs. Finally, through extensive simulations, we show the performance gain achieved by our proposed joint energy trading and communication cooperation schemes in terms of energy cost reduction, as compared with conventional schemes that separately design communication cooperation and energy trading.
RF signals enabled wireless information and power transfer (WIPT) is a cost-effective technique to achieve two-way communications and at the same time provide energy supplies for low-power wireless devices. However, the information transmission in WIPT is vulnerable to eavesdropping by energy receivers. To achieve secrecy communications with information nodes while satisfying the energy transfer requirement of energy receivers, an efficient solution is to exploit dual use of the energy signals also as useful interference or artificial noise to interfere with the energy receivers, thus preventing their potential information eavesdropping. Toward this end, this article provides an overview on the joint design of energy and information signals to achieve energy-efficient and secure WIPT under various practical setups, including simultaneous WIPT, wireless powered cooperative relaying and jamming, and wireless powered communication networks. We also present some research directions that are worth pursuing in the future.
Simultaneous information and power transfer over the wireless channels potentially offers great convenience to mobile users. Yet practical receiver designs impose technical constraints on its hardware realization, as practical circuits for harvesting energy from radio signals are not yet able to decode the carried information directly. To make theoretical progress, we propose a general receiver operation, namely, dynamic power splitting (DPS), which splits the received signal with adjustable power for energy harvesting and for information decoding. Moreover, we propose two types of practical receiver architectures, namely, separated versus integrated information and energy receivers. The integrated receiver integrates the front-end components of the separated receiver, thus achieving a smaller form factor. The rate-energy tradeoff for these two architectures are characterized by a so-called rate-energy (R-E) region. Numerical results show that the R-E region of the integrated receiver is superior to that of the separated receiver when more harvested power is desired.
Although prior works have exploited the UAV's mobility to enhance the wireless communication performance under different setups, the fundamental capacity limits of UAV-enabled/aided multiuser communication systems have not yet been characterized. To fill this gap, we consider in this paper a UAV-enabled two-user broadcast channel (BC), where a UAV flying at a constant altitude is deployed to send independent information to two users at different fixed locations on the ground. We aim to characterize the capacity region of this new type of BC over a given UAV flight duration, by jointly optimizing the UAV's trajectory and transmit power/rate allocations over time, subject to the UAV's maximum speed and maximum transmit power constraints. First, to draw essential insights, we consider two special cases with asymptotically large/low UAV flight duration/speed, respectively. For the former case, it is shown that a simple hover-fly-hover (HFH) UAV trajectory with time division multiple access (TDMA) based orthogonal multiuser transmission is capacity-achieving, while in the latter case, the UAV should hover at a fixed location that is nearer to the user with larger achievable rate and in general superposition coding (SC) based non-orthogonal transmission with interference cancellation at the receiver of the nearer user is required. Next, we consider the general case with finite UAV speed and flight duration. We show that the optimal UAV trajectory should follow a general HFH structure, i.e., the UAV successively hovers at a pair of initial and final locations above the line segment of the two users each with a certain amount of time and flies unidirectionally between them at the maximum speed, and SC is generally needed.
Simultaneous information and power transfer over the wireless channels potentially offers great convenience to mobile users. Yet practical receiver designs impose technical constraints on its hardware realization, as practical circuits for harvesting energy from radio signals are not yet able to decode the carried information directly. To make theoretical progress, we propose a general receiver operation, namely, dynamic power splitting (DPS), which splits the received signal with adjustable power ratio for energy harvesting and information decoding, separately. Three special cases of DPS, namely, time switching (TS), static power splitting (SPS) and on-off power splitting (OPS) are investigated. The TS and SPS schemes can be treated as special cases of OPS. Moreover, we propose two types of practical receiver architectures, namely, separated versus integrated information and energy receivers. The integrated receiver integrates the front-end components of the separated receiver, thus achieving a smaller form factor. The rate-energy tradeoff for the two architectures are characterized by a so-called rate-energy (R-E) region. The optimal transmission strategy is derived to achieve different rate-energy tradeoffs. With receiver circuit power consumption taken into account, it is shown that the OPS scheme is optimal for both receivers. For the ideal case when the receiver circuit does not consume power, the SPS scheme is optimal for both receivers. In addition, we study the performance for the two types of receivers under a realistic system setup that employs practical modulation. Our results provide useful insights to the optimal practical receiver design for simultaneous wireless information and power transfer (SWIPT).
To support large-scale deployment of unmanned aerial vehicles (UAVs) in the future, a new wireless communication paradigm, namely, cellular-connected UAV, has recently received an upsurge of interest in both academia and industry. Specifically, cellular base stations (BSs) and spectrum are reused to serve UAVs as new aerial user equipments (UEs) for meeting their communication requirements. However, compared to traditional terrestrial UEs, the high altitude of UAVs results in more frequent line-of-sight (LoS) channels with both their associated and non-associated BSs in a much wider area, which causes stronger aeri-al-ground interference to both UAVs and terrestrial UEs. As such, conventional techniques designed for mitigating the terrestrial interference become ineffective in coping with the new and more severe UAV-terrestrial interference. To tackle this challenge, we propose in this article new interference mitigation solutions for achieving spectral efficient operation of the cellular network with co-existing UAVs and terrestrial UEs. In particular, we exploit the powerful sensing capability of UAVs and inactive BSs in the network for interference mitigation/cancellation. Numerical results are presented to verify the efficacy of the proposed solutions and show their significant spectrum efficiency gains over terrestrial interference mitigation techniques.
