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In today's digital world, interaction with online platforms is ubiquitous, and thus content moderation is important for protecting users from content that do not comply with pre-established community guidelines. Having a robust content moderation system throughout every stage of planning is particularly important. We study the short-term planning problem of allocating human content reviewers to different harmful content categories. We use tools from fair division and study the application of competitive equilibrium and leximin allocation rules. Furthermore, we incorporate, to the traditional Fisher market setup, novel aspects that are of practical importance. The first aspect is the forecasted workload of different content categories. We show how a formulation that is inspired by the celebrated Eisenberg-Gale program allows us to find an allocation that not only satisfies the forecasted workload, but also fairly allocates the remaining reviewing hours among all content categories. The resulting allocation is also robust as the additional allocation provides a guardrail in cases where the actual workload deviates from the predicted workload. The second practical consideration is time dependent allocation that is motivated by the fact that partners need scheduling guidance for the reviewers across days to achieve efficiency. To address the time component, we introduce new extensions of the various fair allocation approaches for the single-time period setting, and we show that many properties extend in essence, albeit with some modifications. Related to the time component, we additionally investigate how to satisfy markets' desire for smooth allocation (e.g., partners for content reviewers prefer an allocation that does not vary much from time to time, to minimize staffing switch). We demonstrate the performance of our proposed approaches through real-world data obtained from Meta.

Non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission has recently received significant research attention due to its outstanding ability of serving grant-free (GF) users with grant-based (GB) users' spectrum, which greatly improves the spectrum efficiency and effectively relieves the massive access problem of 5G and beyond networks. In this paper, we first study the outage performance of the greedy best user scheduling SGF scheme (BU-SGF) by considering the impacts of Rayleigh fading, path loss, and random user locations. In order to tackle the admission fairness problem of the BU-SGF scheme, we propose a fair SGF scheme by applying cumulative distribution function (CDF)-based scheduling (CS-SGF), in which the GF user with the best channel relative to its own statistics will be admitted. Moreover, by employing the theories of order statistics and stochastic geometry, the outage performances of both BU-SGF and CS-SGF schemes are analyzed. Theoretical results show that both schemes can achieve full diversity orders only when the served users' data rate is capped, which severely limits the rate performance of SGF schemes. To further address this issue, we propose a distributed power control strategy to relax such data rate constraint, and derive analytical expressions of the two schemes' outage performances under this strategy. Finally, simulation results validate the fairness performance of the proposed CS-SGF scheme, the effectiveness of the power control strategy, and the accuracy of the theoretical analyses.

This paper considers a two-user non-orthogonal multiple access (NOMA) based infrastructure-to-vehicle (I2V) network, where one user requires reliable safety-critical data transmission and the other pursues high-capacity services. Leveraging only slow fading of channel state information, we aim to maximize the expected sum throughput of the capacity hungry user subject to a constraint on the payload delivery success probability of the reliability sensitive user, by jointly optimizing the transmit powers, target rates, and decoding order. We introduce a dual variable and formulate the optimization as an unconstrained single-objective sequential decision problem. Then, we design a dynamic programming based algorithm to derive the optimal policy that maximizes the Lagrangian. Afterwards, a bisection search based method is proposed to find the optimal dual variable. The proposed strategy is shown by numerical results to be superior to the baseline approaches from the perspectives of expected return, performance region, and objective value.

Age of Information (AoI), which measures the time elapsed since the generation of the last received packet at the destination, is a new metric for real-time status update tracking applications. In this paper, we consider a status-update system in which a source node samples updates and sends them to an edge server over a delay channel. The received updates are processed by the server with an infinite buffer and then delivered to a destination. The channel can send only one update at a time, and the server can process one at a time as well. The source node applies generate-at-will model according to the state of the channel, the edge server, and the buffer. We aim to minimize the average AoI with \emph{independent and identically distributed} transmission time and processing time. We consider three online scheduling policies. The first one is the optimal long wait policy, under which the source node only transmits a new packet after the old one is delivered. Secondly, we propose a peak age threshold policy, under which the source node determines the sending time based on the estimated peak age of information (PAoI). Finally, we improve the peak age threshold policy by considering a postponed plan to reduce the waiting time in the buffer. The AoI performance under these policies is illustrated by numerical results with different parameters.

Multiple-input multiple-output (MIMO) systems greatly increase the overall throughput of wireless systems since they are capable of transmitting multiple streams employing the same time-frequency resources. However, this gain requires an appropriate precoder design and a power allocation technique. In general, precoders and power allocation schemes are designed assuming perfect channel estate information (CSI). Nonetheless, this is an optimistic assumption since real systems only possess partial or imperfect CSI at the transmitter (CSIT). The imperfect CSIT originates residual inter-user interference, which is detrimental for wireless systems. In this paper, two adaptive power allocation algorithms are proposed, which are more robust against CSIT imperfections than conventional techniques. Both techniques employ the mean square error as the objective function. Simulation results show that the proposed techniques obtain a higher performance in terms of sum-rate than conventional approaches.

Multi-functional and reconfigurable multiple-input multiple-output (MR-MIMO) can provide performance gains over traditional MIMO by introducing additional degrees of freedom. In this paper, we focus on the capacity maximization pattern design for MR-MIMO systems. Firstly, we introduce the matrix representation of MR-MIMO, based on which a pattern design problem is formulated. To further reveal the effect of the radiation pattern on the wireless channel, we consider pattern design for both the single-pattern case where the optimized radiation pattern is the same for all the antenna elements, and the multi-pattern case where different antenna elements can adopt different radiation patterns. For the single-pattern case, we show that the pattern design is equivalent to a redistribution of power among all scattering paths, and an eigenvalue optimization based solution is obtained. For the multi-pattern case, we propose a sequential optimization framework with manifold optimization and eigenvalue decomposition to obtain near-optimal solutions. Numerical results validate the superiority of MR-MIMO systems over traditional MIMO in terms of capacity, and also show the effectiveness of the proposed solutions.

We consider the extra degree of freedom offered by the rotation of the reconfigurable intelligent surface (RIS) plane and investigate its potential in improving the performance of RIS-assisted wireless communication systems. By considering radiation pattern modeling at all involved nodes, we first derive the composite channel gain and present a closed-form upper bound for the system ergodic capacity over cascade Rician fading channels. Then, we reconstruct the composite channel gain by taking the rotations at the RIS plane, transmit antenna, and receive antenna into account, and extract the optimal rotation angles after investigating their impacts on the capacity. Moreover, we present a location-dependent expression of the ergodic capacity and investigate the RIS deployment strategy, i.e. the joint rotation adjustment and location selection. Finally, simulation results verify the accuracy of the theoretical analyses and deployment strategy. Although the RIS location has a big impact on the performance, our results showcase that the RIS rotation plays a more important role. In other words, we can obtain a considerable improvement by properly rotating the RIS rather than moving it over a wide area. For instance, we can achieve more than 200\% performance improvement through rotating the RIS by 42.14$^{\circ}$, while an 150\% improvement is obtained by shifting the RIS over 400 meters.

In recent years, there has been a growing interest in exploring the application of single-photon avalanche diode (SPAD) in optical wireless communication (OWC). As a photon counting detector, SPAD can provide much higher sensitivity compared to the other commonly used photodetectors. However, SPAD-based receivers suffer from significant dead-time-induced non-linear distortion and signal dependent noise. In this work, we propose a novel SPAD-based OWC system in which the non-linear distortion caused by dead time can be successfully eliminated by the pre-distortion of the signal at the transmitter. In addition, another system with joint pre-distortion and noise normalization functionality is proposed. Thanks to the additional noise normalization process, for the transformed signal at the receiver, the originally signal dependent noise becomes signal independent so that the conventional signal detection techniques designed for AWGN channels can be employed to decode the signal. Our numerical results demonstrate the superiority of the proposed SPAD-based systems compared to the existing systems in terms of BER performance and achievable data rate.

We study the problem of allocating a set $M$ of $m$ ${indivisible}$ items among $n$ agents in a fair manner. We consider two well-studied notions of fairness: envy-freeness (EF), and envy-freeness up to any good (EFX). While it is known that complete EF allocations do not always exist, it is not known if complete EFX allocations exist besides a few cases. In this work, we reformulate the problem to allow $M$ to be a multiset. Specifically, we introduce a parameter $t$ for the number of distinct ${types}$ of items, and study allocations of multisets that contain items of these $t$ types. We show the following: 1. For arbitrary $n$, $t$, a complete EF allocation exists when agents have distinct additive valuations, and there are ${enough}$ items of each type. 2. For arbitrary $n$, $m$, $t$, a complete EFX allocation exists when agents have additive valuations with identical ${preferences}$. 3. For arbitrary $n$, $m$, and $t\le2$, a complete EFX allocation exists when agents have additive valuations. For 2 and 3, our approach is constructive; we give a polynomial-time algorithm to find a complete EFX allocation.

In radar sensing and communications, designing Doppler resilient sequences (DRSs) with low ambiguity function for delay over the entire signal duration and Doppler shift over the entire signal bandwidth is an extremely difficult task. However, in practice, the Doppler frequency range is normally much smaller than the bandwidth of the transmitted signal, and it is relatively easy to attain quasi-synchronization for delays far less than the entire signal duration. Motivated by this observation, we propose a new concept called low ambiguity zone (LAZ) which is a small area of the corresponding ambiguity function of interest defined by the certain Doppler frequency and delay. Such an LAZ will reduce to a zero ambiguity zone (ZAZ) if the maximum ambiguity values of interest are zero. In this paper, we derive a set of theoretical bounds on periodic LAZ/ZAZ of unimodular DRSs with and without spectral constraints, which include the existing bounds on periodic global ambiguity function as special cases. These bounds may be used as theoretical design guidelines to measure the optimality of sequences against Doppler effect. We then introduce four optimal constructions of DRSs with respect to the derived ambiguity lower bounds based on some algebraic tools such as characters over finite field and cyclic difference sets.