This paper proposes a novel location information aided multiple intelligent reflecting surface (IRS) systems. Assuming imperfect user location information, the effective angles from the IRS to the users are estimated, which is then used to design the transmit beam and IRS beam. Furthermore, closed-form expressions for the achievable rate are derived. The analytical findings indicate that the achievable rate can be improved by increasing the number of base station (BS) antennas or reflecting elements. Specifically, a power gain of order NM2 is achieved, where N is the antenna number and M is the number of reflecting elements. Moreover, with a large number of reflecting elements, the individual signal to interference plus noise ratio (SINR) is proportional to M, while becomes proportional to M2 as non-line-of-sight (NLOS) paths vanish. Also, it has been shown that high location uncertainty would significantly degrade the achievable rate. Besides, IRSs should be deployed at distinct directions (relative to the BS) and be far away from each other to reduce the interference from multiple IRSs. Finally, an optimal power allocation scheme has been proposed to improve the system performance.

In this letter, an intelligent reflecting surface (IRS) enhanced full-duplex MIMO two-way communication system is studied. The system sum rate is maximized through jointly optimizing the source precoders and the IRS phase shift matrix. Adopting the idea of Arimoto-Blahut algorithm, the non-convex optimization problem is decoupled into three sub-problems, which are solved alternatingly. All the sub-problems can be solved efficiently with closed-form solutions. In addition, practical IRS assumptions, e.g., discrete phase shift levels, are also considered. Numerical results verify the convergence and performance of the proposed scheme.

In this work, we study the statistically robust beamforming design for an intelligent reflecting surfaces (IRS) assisted multiple-input single-output (MISO) wireless system under imperfect channel state information (CSI), where the channel estimation errors are assumed to be additive Gaussian. We aim at jointly optimizing the transmit/receive beamformers and IRS phase shifts to minimize the average mean squared error (MSE) at the user. In particular, to tackle the non-convex optimization problem, an efficient algorithm is developed by capitalizing on alternating optimization and majorization-minimization techniques. Simulation results show that the proposed scheme achieves robust MSE performance in the presence of CSI error, and substantially outperforms conventional non-robust methods.

This letter investigates an active intelligent reflecting surface (IRS)-aided integrated sensing and communication (ISAC) system in the scenario of cloud radio access network (C-RAN). In the system, the active IRS is deployed to amplify and reflect the joint communication and sensing signals from the remote radio heads (RRHs). Our goal is to form the desired reflective beam pattern from the active IRS towards the sensing targets located in non-line-of-sight (NLoS) areas for the RRHs, while satisfying the signal-to-interference-plus-noise ratio (SINR) requirement for the communication users and the capacity limit for the fronthaul links between the baseband unit (BBU) pool and RRHs. Specifically, we propose an efficient joint design for the fronthaul compression and the beamforming of the RRHs and the active IRS. Via numerical simulations, the effectiveness of the proposed design is verified.

As human society develops, the population is growing explosively and water and land resources are gradually being exhausted due to pollution. Smart agriculture is regarded as having an essential role in addressing the above challenges. Smart agriculture can significantly improve the agro-ecological environment and the yield and quality of agricultural products, and it can reduce the usage of pesticides and chemical fertilizers, thus alleviating the pollution of farmland and improving the sustainability of agricultural activities. The key to smart agriculture is in utilizing information and communication technologies to make agricultural cultivation and production automatic and intelligent. Specifically, wireless communications play an active role in the development of agriculture, and every generation of wireless communication technology drives agriculture to a more intelligent stage. In this article, we first review the wireless technologies which have mature applications in agriculture. Moreover, it is of importance to exploit the up-to-date communication technologies to further promote agricultural development. Therefore, we have surveyed the key technologies in sixth-generation mobile communication systems, as well as their existing and potential applications in smart agriculture.

The universal filtered multi-carrier (UFMC) has been taken as a promising candidate for 5G waveform, where a finite impulse response (FIR) filter is employed to shape the waveform and enhance its resistance to inter-carrier interference (ICI). Previous studies have used the Dolph-Chebyshev filter due to its low side-lobe levels, but at the cost of low flexibility to filter performance control. Hence, this paper puts forward an effective scheme to design anti-interference filter for UFMC system, where the Nyquist condition (or sampling inter-symbol interference equivalently), the in-band distortion and the out-of-band emission are taken into consideration. First, this paper models the filter design as a constrained minimax optimization concerning above filter performance indexes. Then, the original nonconvex constraints on Nyquist condition are approximately transformed to a linear matrix inequation (LMI) and two linear inequations. Finally, the optimization problem is solved by the semi-definite programming (SDP). The numerical examples explicitly demonstrate the flexible performances tradeoff of the proposed method, in which the included filter performance indexes can be effectively controlled. Moreover, the bit-error-rate (BER) tests of the UFMC system confirms the effectiveness of our study, where the designed filters with smaller ISI show BER advantages over previous used filters.