Age of information, as a metric measuring the data freshness, has drawn increasing attention due to its importance in many data update applications. Most existing studies have assumed that there is one single channel in the system. In this work, we are motivated by the plethora of multi-channel systems that are being developed, and investigate the following question: how can one exploit multi-channel resources to improve the age performance? We first derive a policy-independent lower bound of the expected long-term average age in a multi-channel system. The lower bound is jointly characterized by the external arrival process and the channel statistics. Since direct analysis of age in multi-channel systems is very difficult, we focus on the asymptotic regime, when the number of users and number of channels both go to infinity. In the many-channel asymptotic regime, we propose a class of Maximum Weighted Matching policies that converge to the lower bound near exponentially fast. In the many-user asymptotic regime, we design a class of Randomized Maximum Weighted Matching policies that achieve a constant competitive ratio compared to the lower bound. Finally, we use simulations to validate the aforementioned results.

FlexRadio, a recent breakthrough in wireless Multi-RF technology, has introduced a new way to unify MIMO and full-duplex into a single framework with a fully flexible design. FlexRadio allows a wireless node to use an arbitrary number of RF chains to support transmission and reception, which makes MIMO and full-duplex subset configurations of FlexRadio. This new architecture has greatly changed the feasibility constraint in wireless networks, which makes the design of high performance MAC layer algorithms even more challenging. First, the RF chain becomes a new resource that needs to be allocated across the network, and the optimal configuration depends not only on the network topology and flow demand, but also on the number of available RF chains at each node. Second, it is not clear how to jointly allocate links and RF chain resources based on the arrival rates and queueing dynamics. In this paper, we introduce a new virtual link model to characterize the feasibility constraint from the perspective of contending RF chain usage. Based on this novel model, a distributed CSMA-like framework is developed to fully leverage the flexibility of RF chain resource allocation.

Each camera on digital devices is made of hundreds of thousands of sensors, with which it can separate and capture the light from spatial points in a fine-grain manner, enabling high-rate data transfer from the digital display to the camera, i.e. screen-camera communication. Compared with RF (Radio Frequency) technologies, visible light approaches are more convenient and secure.

An essential step for achieving multiplexing gain in MIMO downlink systems is to collect accurate channel state information (CSI) from the users. Traditionally, CSIs have to be collected before any data can be transmitted. Such a sequential scheme incurs a large feedback overhead, which substantially limits the multiplexing gain especially in a network with a large number of users. In this paper, we propose a novel approach to mitigate the feedback overhead by leveraging the recently developed Full-duplex radios. Our approach is based on the key observation that using Full-duplex radios, when the base-station (BS) is collecting CSI of one user through the uplink channel, it can use the downlink channel to simultaneously transmit data to other (non-interfering) users for which CSIs are already known. By allowing concurrent channel probing and data transmission, our scheme can potentially achieve a higher throughput compared to traditional schemes using Half-duplex radios. The new flexibility introduced by our scheme, however, also leads to fundamental challenges in achieving throughout optimal scheduling. In this paper, we make an initial effort to this important problem by considering a simplified group interference model. We develop a throughput optimal scheduling policy with complexity O((N/I)I), where N is the number of users and I is the number of user groups. To further reduce the complexity, we propose a greedy policy with complexity O(N log N) that not only achieves at least 2/3 of the optimal throughput region, but also outperforms any feasible Half-duplex solutions. We derive the throughput gain offered by Full-duplex under different system parameters and show the advantage of our algorithms through numerical studies.

There have been recent attempts to develop scheduling schemes for downlink transmission in a single cell of a multi-channel (e.g., OFDM-based) cellular network. These works have been quite promising in that they have developed low-complexity index scheduling policies that are delay-optimal (in a large deviation rate-function sense). However, these policies require that the channel is ON or OFF in each time-slot with a fixed probability (i.e., there is no memory in the system), while the reality is that due to channel fading and doppler shift, channels are often time-correlated in these cellular systems. Thus, an important open question is whether one can find simple index scheduling policies that are delay-optimal even when the channels are time-correlated. In this paper, we attempt to answer this question for time-correlated ON/OFF channels. In particular, we show that the class of oldest packets first (OPF) policies that give a higher priority to packets with a large delay is delay rate-function optimal under two conditions: 1) The channel is non-negatively correlated, and 2) The distribution of the OFF period is geometric. We use simulations to further elucidate the theoretical results.

We study the multicast capacity under a network model featuring both node's mobility and infrastructure support. Combinations between mobility and infrastructure, as well as multicast transmission and infrastructure, have already showed effective ways to increase multicast capacity. In this work, we jointly consider the impact of the above three factors on network capacity. We assume that$m$static base stations and$n$mobile users are placed in an ad hoc network. A general mobility model is adopted, such that each user moves within a bounded distance from its home-point with an arbitrary pattern. In addition, each mobile node serves as a source of multicast transmission, which results in a total number of$n$multicast transmissions. We focus on the situations in which base stations actually benefit the capacity improvement, and find that multicast capacity in a mobile hybrid network falls into several regimes. For each regime, reachable upper and lower bounds are derived. Our work contains theoretical analysis of multicast capacity in hybrid networks and provides guidelines for the design of real hybrid systems combing cellular and ad hoc networks.