Weight reduction and low power consumption are key requirements in the next generation of unmanned aerial vehicle (UAV) networks. Employing modulating retro-reflector (MRR)-based free space optical (FSO) technology is an innovative technique for UAV-to-ground communication in order to reduce the payload weight and power consumption of UAVs which leads to increased maneuverability and flight time of UAV. In this paper, we consider an MRR-based FSO system for UAV-to-ground communication. We will show that the performance of the considered system is very sensitive to tracking errors. Therefore, to assess the benefits of MRR-based UAV deployment for FSO communications, the MRR-based UAV FSO channel is characterized by taking into account tracking system errors along with UAV’s orientation fluctuations, link length, UAV’s height, optical beam divergence angle, effective area of MRR, atmospheric turbulence and optical channel loss in the double-pass channels. To enable effective performance analysis, tractable and closed-form expressions are derived for probability density function of end-to-end signal to noise ratio, outage probability and bit error rate of the considered system under both weak-to-moderate and moderate-to-strong atmospheric turbulence conditions. The accuracy of the analytical expressions is verified by extensive simulations. Analytical results are then used to study the relationship between the optimal system design and tracking system errors.

In this article, the performance of UAV-based mmW links is investigated when UAVs are equipped with square array antennas. The 3GPP antenna propagation patterns are used to model the square array antenna. It is shown that the square array antenna is sensitive to both horizontal and vertical angular vibrations of UAVs. In order to explore the relationship between the vibrations of UAVs and their antenna pattern, the UAV-based mmW channels are characterized by considering the large scale path loss, small scale fading along with antenna patterns as well as the random effect of UAVs' angular vibrations. To enable effective performance analysis, tractable and closed-form statistical channel models are derived for aerial-to-aerial (A2A), ground-to-aerial (G2A), and aerial-to-ground (A2G) channels. The accuracy of analytical models is verified by employing Monte Carlo simulations. Analytical results are then used to study the effect of antenna pattern gain under different conditions for the UAVs' angular vibrations for establishing reliable UAV-assisted mmW links in terms of achieving minimum outage probability. Simulation results show that the performance of UAV-based mmW links with directional antennas is largely dependent on the random fluctuations of hovering UAVs. Moreover, UAVs with higher antenna directivity gains achieve better performance at larger link length. However, for UAVs with lower stability, lower antenna directivity gains result in a more reliable communication link. Finally, based on the geometrical properties of a given region, we investigate the optimal antenna pattern along with the optimal aerial position for UAV relay to attain minimum outage probability.

A simple scheme is proposed to achieve the optimal degrees of freedom (DoF) of the temporally correlated two-user multiple-input-multiple-output interference channel with delayed channel state information at the transmitter (CSIT). The delayed CSIT is exploited for temporal alignment at the transmitters and spatial zero-forcing of interference at the receivers. The transmitters estimate the current CSIT using perfect delayed CSIT. For most antenna configurations, the proposed scheme achieves the optimal DoF-region of this channel by precoding (resp. decoding) over a finite number of time slots at each transmitter (resp. receiver). This is an improvement over existing achievable methods, which require infinite channel extensions (hence, infinite decoding delay) and involve complicated encoding and decoding procedures.

In interference channels (ICs), channel state information (CSI) can be utilized to design transmit signals that are optimally adapted to the state of the channels. This requires feeding CSI back to the transmitters. The CSI available at the transmitters (CSIT) is usually degraded, due to the limited capacity of the feedback link and the delays involved in the channel estimation and feedback. We discuss the scenario of fast fading and delayed CSIT, which is highly relevant in mobile environments with short channel coherence times. We consider the two-user multiple-input-multiple-output (MIMO) IC where the transmitters are provided with delayed CSIT. The DoF region for this channel was characterized by Vaze and Varanasi. We devise a simple and intuitive achievable scheme, which has a unified structure for different antenna configurations. We show that the proposed scheme also achieves the DoF region of the two-user MIMO broadcast channel (BC). In the IC, our scheme does not require the knowledge of direct channels at the transmitters. Moreover, we show that the amount of feedback can be further reduced by exploiting the invariances of the problem. Our approach can be helpful when analyzing more complicated networks.

A simple channel state information (CSI) feedback scheme is proposed for interference alignment (IA) over the K-user constant multiple-input-multiple-output interference channel (MIMO IC). The proposed technique relies on the identification of invariants in the IA equations, which enables the reformulation of the CSI quantization problem as a single quantization on the Grassmann manifold at each receiver. The scaling of the number of feedback bits with the transmit power sufficient to preserve the multiplexing gain that can be achieved under perfect CSI is established. We show that the CSI feedback requirements of the proposed technique are better (lower) than what is required when using previously published methods (including state-of-the-art codebook-based as well as analog feedback techniques), for system dimensions (number of users and antennas) of practical interest. Furthermore, we show through simulations that this advantage persists at low SNR, in the sense that the proposed technique yields a higher sum-rate performance for a given number of feedback bits. Finally, to complement our analysis, we introduce a statistical model that faithfully captures the properties of the quantization error obtained for random vector quantization (RVQ) on the Grassmann manifold for large codebooks; this enables the numerical (Monte Carlo) analysis of general Grassmannian RVQ schemes for codebook sizes that would be impractically large to simulate.

We consider the two-user Multiple-Input-Multiple-Output Interference Channel (MIMO-IC) with outdated channel state information at the transmitters (CSIT). For a fast- fading scenario, the degrees-of-freedom (DoF) region for this channel has been characterized by Vaze and Varanasi in [1]. We devise a simple achievable scheme, which has a unified structure for different antenna configurations. In the proposed scheme, matrices with random entries chosen from a continuous probability distribution are used in the process of designing the precoders. The unified structure of the precoders involving random matrices makes our scheme suitable for generalization to other networks.

This paper focuses on the two-user relay-assisted X channel with no channel state information (CSI) available at the transmitter side. Two relaying modes, namely half-duplex decode-and-forward (DF) and cognitive relays, are considered and the degrees of freedom (DoF) are characterized. It is shown that assisted by a half-duplex DF relay that is equipped with 2M antennas, the X channel with two M-antenna users has 4M/3 DoF, which is achievable through interference alignment (IA). Furthermore, it is shown that in this channel, an M-antenna cognitive relay (with non-causal access to information streams) provides 2M DoF using interference cancellation (IC) technique. In this setting, IC outperforms interference alignment in the cognitive relay mode, since the latter achieves 4M/3 DoF.

Cellular systems that employ time division duplexing (TDD) transmission are good candidates for implementation of interference alignment (IA) in the downlink since channel reciprocity enables the estimation of the channel state by the base stations (BS) in the uplink phase. However, the interfering BSs need to share their channel estimates via backhaul links of finite capacity. A quantization scheme is proposed which reduces the amount of information exchange (compared to conventional methods) required to achieve IA in such a system. The scaling (with the transmit power) of the number of bits to be exchanged between the BSs that is sufficient to preserve the multiplexing gain of IA is derived. Furthermore, assuming that the BSs have accurate estimates of their outgoing channels, new methods are proposed to further improve the performance of the network in a distributed manner.

In this paper link adaptation for interference alignment (IA) based on imperfect channel state information (CSI) is investigated. We consider a MIMO interference channel where the transmit and receive spaces are determined by IA. We look at maximizing a weighted sum of the average rates provided that a certain set of bit-error-rate and power constraints are satisfied by dynamically adjusting coding, modulation and powers. The problem is quite general and intractable. We resort to some approximations and provide simulations to show the accuracy of the approximations in the regimes with practical interest.

We introduce an iterative solution to the problem of interference alignment (IA) over MIMO channels based on a message-passing formulation. We propose a parameterization of the messages that enables the computation of IA precoders by a min-sum algorithm over continuous variable spaces - under this parameterization, suitable approximations of the messages can be computed in closed-form. We show that the iterative leakage minimization algorithm of Gomadam et al. is a special case of our message-passing algorithm, obtained for a particular schedule. Finally, we show that the proposed algorithm compares favorably to iterative leakage minimization in terms of convergence speed, and discuss a distributed implementation.

In this paper, interference alignment (IA) based on imperfect channel state information (CSI) is investigated. As the accuracy of the CSI at the transmitter side is crucial for IA, we analyze the statistics of the imperfect CSI and design an adaptive scheme based on the available imperfect CSI. We consider a multiple-input-multiple-output (MIMO) interference channel where the transmit and receive spaces are determined by IA. Using practical modulation schemes, we consider the maximization of a weighted sum of the average rates provided that a certain set of bit-error-rate and power constraints is satisfied by dynamically adapting coding, modulation, and power settings. The problem in such a general form is intractable. Therefore, we resort to some approximations and provide simulations to show the accuracy of the approximations in the regimes with practical interest.

Cellular systems that employ time division duplexing (TDD) transmission are good candidates for implementation of interference alignment (IA) in the downlink since channel reciprocity enables the estimation of the channel state by the base stations (BS) in the uplink phase. However, the interfering BSs need to share their channel estimates via backhaul links of finite capacity. A quantization scheme is proposed which reduces the amount of information exchange (compared to conventional methods) required to achieve IA in such a system. The scaling (with the transmit power) of the number of bits to be exchanged between the BSs that is sufficient to preserve the multiplexing gain of IA is derived1.

Network MIMO provides significant gains compared to transmission schemes based on the interference channel in cellular networks. However, the interference channel is adopted very often in particular due to data sharing limitations of network MIMO. These limitations are due to backhaul links which have finite capacity and also introduce delay. In interference channels, even though data is not exchanged between the transmitters, the global channel state information (CSI) needs to be shared in order to attain the degrees of freedom (DoF) of the channel. This highlights the necessity of reducing the amount of CSI exchange and relying more on local CSI to design the precoders in particular when the local CSI is accurate. In this contribution, cellular downlink transmission using time division duplexing (TDD) is considered where the base stations (BS) can estimate their own channels through reciprocity during the uplink phase. The interfering BSs share their channel estimates via backhaul links of finite capacity. We propose a distributed precoding method based on interference alignment (IA) which is shown to require relatively less CSI exchange compared to other methods.

A simple limited feedback scheme is proposed for interference alignment on the K-user Multiple-Input-Multiple-Output Interference Channel (MIMO-IC). The scaling of the number of feedback bits with the transmit power required to preserve the multiplexing gain that can be achieved using perfect channel state information (CSI) is derived. This result is obtained through a reformulation of the interference alignment problem in order to exploit the benefits of quantization on the Grassmann manifold, which is well investigated in the single-user MIMO channel. Furthermore, through simulations we show that the proposed scheme outperforms the naive feedback scheme consisting in independently quantizing the channel matrices, in the sense that it yields a better sum rate performance for the same number of feedback bits.