Cache-aided MIMO communications aims to jointly exploit both coded caching (CC) and spatial multiplexing gains to enhance communication efficiency. In this paper, we analyze both the achievable degrees of freedom (DoF) under linear processing constraint and the finite-SNR performance of a MIMO-CC system with CC gain$t$, where a server with$L$transmit antennas communicates with$K$users, each equipped with$G$receive antennas. We first demonstrate that the enhanced DoF of$\max _{\beta, \Omega } \Omega \times \beta $is achievable with linear processing, where the number of users$\Omega $served in each transmission is fine-tuned to maximize DoF, and$\beta \le \min \left ({{G, {\scriptstyle \text {}^{\scriptstyle L \binom {\Omega -1}{t}}}\hspace {-0.224em}/\hspace {-0.112em}{\scriptstyle \big (1 + (\Omega {-} t - 1)\binom {\Omega -1}{t}}}}\right)\big)$represents the number of parallel streams decoded by each user. Then, we propose a new class of MIMO-CC schemes using a novel scheduling mechanism leveraging maximal multicasting opportunities to maximize delivery rates at given SNR levels while still adhering to linear processing constraints. This new class of schemes is paired with an efficient linear multicast beamformer design, resulting in a more practical, high-performance solution for integrating CC in future MIMO systems.

Coded caching leverages the differences in user cache memories to achieve gains that scale with the total cache size, alleviating network congestion due to high-quality content requests. Additionally, distributing transmitters over a wide area can mitigate the adverse effects of path loss. In this work, we consider a partially connected network where the channel between distributed transmitters (helpers) and users is modeled as a distributed multiple-input-multiple-output (MIMO) Gaussian broadcast channel. We propose a novel delivery scheme consisting of two phases: partitioning and transmission. In the partitioning phase, users with identical cache profiles are partitioned into the minimum number of sets, such that users within each set can successfully decode their desired message from a joint transmission enabled by MIMO precoding. To optimally partition the users, we employ the branch and bound method. In the transmission phase, each partition is treated as a single entity, and codewords are multicast to partitions with distinct cache profiles. The proposed delivery scheme is applicable to any partially connected network, and while the partitioning is optimal, the overall delivery scheme, including transmission, is heuristic. Interestingly, simulation results show that its performance closely approximates that of the fully connected optimal solution.

Integrating coded caching (CC) into multiple-input multiple-output (MIMO) communications can significantly enhance the achievable degrees of freedom (DoF) in wireless networks. This paper investigates a practical cache-aided asymmetric MIMO configuration with cache ratio$\gamma$, where a server equipped with$L$transmit antennas communicates with$K$users, each having$G_{k}$receive antennas. We propose three contentaware MIMO-CC strategies: the min-G scheme, which treats the system as symmetric by assuming all users have the same number of antennas, equal to the smallest among them; the Grouping scheme, which maximizes spatial multiplexing gain separately within each user subset at the cost of some global caching gain; and the Phantom scheme, which dynamically redistributes spatial resources using virtual or “phantom” antennas at the users, bridging the performance gains of the min-$G$and Grouping schemes. These strategies jointly optimize the number of users,$\Omega$, and the parallel streams decoded by each user,$\beta_{k}$, ensuring linear decodability for all target users. Analytical and numerical results confirm that the proposed schemes achieve significant DoF improvements across various system configurations.

Integrating coded caching (CC) into multi-input multi-output (MIMO) setups significantly enhances the achievable degrees of freedom (DoF). We consider a cache-aided MIMO configuration with a CC gain t, where a server with L Tx-antennas communicates with K users, each equipped with G Rx-antennas. Similar to existing works, we also extend a core CC approach, designed initially for multi-input single-output (MISO) scenarios, to the MIMO setup. However, in the proposed MIMO strategy, rather than replicating the transmit scheme from the MISO setup, the number of users Ω served in each transmission is fine-tuned to maximize DoF. As a result, an optimized DoF of maxβ,ΩΩβ is achieved, where $\beta \leq \min \left( {G,L\binom {\Omega - 1} t /1 + (\Omega - t - 1)\binom {\Omega - 1} t } \right)$ is the number of parallel streams decoded by each user. For the considered MIMO-CC setup, we also introduce an effective multicast transmit covariance matrix design for the symmetric rate maximization objective solved iteratively via successive convex approximation (SCA). Finally, numerical simulations verify the enhanced DoF and improved performance of the proposed design.

A novel coding design is proposed to enhance information retrieval in a wireless network of users with partial access to the data, in the sense of observation, measurement, computation, or storage. Information exchange in the network is assisted by a multi-antenna base station (BS), with no direct access to the data. Accordingly, the missing parts of data are exchanged among users through an uplink (UL) step followed by a downlink (DL) step. In this paper, new coding strategies, inspired by coded caching (CC) techniques, are devised to enhance both UL and DL steps. In the UL step, users transmit encoded and properly combined parts of their accessible data to the BS. Then, during the DL step, the BS carries out the required processing on its received signals and forwards a proper combination of the resulting signal terms back to the users, enabling each user to retrieve the desired information. Using the devised coded data retrieval strategy, the data exchange in both UL and DL steps requires the same communication delay, measured by normalized delivery time (NDT). Furthermore, the NDT of the UL/DL step is shown to coincide with the optimal NDT of the original DL multi-input single-output CC scheme, in which the BS is connected to a centralized data library.

Coded caching (CC) can substantially enhance network performance by leveraging memory as an additional communication resource. However, the use of CC is challenging in various practical applications due to dynamic user behavior. The existing solutions, based on shared caching, cannot directly handle all scenarios where users freely enter and depart the network at any time as they are constrained by specific conditions on network parameters. This paper proposes a universally applicable shared-caching scheme for dynamic setups without any restriction on network parameters. The closed-form expressions for the achievable degrees of freedom (DoF) are computed for the resulting generalized scheme, and are shown to achieve the existing optimal bounds of the shared-cache model. Furthermore, a successive-interference-cancellation-free extension based on a fast iterative optimized beamformer design is devised to optimize the use of excess spatial dimensions freed by cache-aided interference cancellation. Extensive numerical experiments are carried out to assess the performance of the proposed scheme. In particular, the results demonstrate that while a dynamic setup may achieve a DoF substantially lower than the optimal DoF of shared caching, our proposed scheme significantly improves the performance at the finite signal-to-noise ratio compared to unicasting, which only benefits from the local caching gain.

Human-computer interaction continuously evolves towards a genuinely immersive experience, submerging users in a three-dimensional (3D) virtual world. A realistic, immersive experience necessitates a highly reliable and agile wireless connection to support immense data transmission. Yet, there are abundant but underutilized memory resources available at the devices which can be harnessed as supplementary assets to reduce the excessive burden on the wireless medium. What is more, the use of Coded Caching (CC) techniques enables the cumulative cache memory of users in the network to be used as an additional communication resource. To this end, a location-dependent multi-antenna CC-based content delivery scheme tailored specifically for wireless extended reality applications is proposed in this paper. First, a novel memory allocation process is developed, enabling an appropriate trade-off between local and global caching gains. In this regard, the local caching gain is maximized when the memory is mostly dedicated to locations with poor connectivity conditions (absolute fairness). In contrast, the global caching gain is maximized when the memory is uniformly allocated among all the locations. As a result of the memory allocation process, unequal fractions of location-dependent multimedia content are cached by each user. Given the asymmetric cache placement, a novel algorithm is proposed to create suitable codewords for each user during the subsequent delivery phase, which simultaneously achieves a global and local caching gain. The proposed delivery scheme also combines global caching and spatial multiplexing gains using a weighted max-min multicast beamformer design with multi-rate modulation. Numerical experiments and mathematical analysis demonstrate significant performance gains, in terms of the 95-percentile expected delivery time, compared to unicast and multicast scenarios where either the local or global caching gain is maximized.

A location-aware multi-antenna coded caching scheme is proposed for applications with location-dependent data requests, such as wireless immersive experience, where users are immersed in a three-dimensional virtual world. The wireless connectivity conditions vary as the users move within the application area motivating the use of a non-uniform cache memory allocation process to avoid excessive delivery time for users located in wireless bottleneck areas. To this end, a location-aware placement and delivery array (LAPDA) is designed for cache-aided multiantenna data delivery with a fast converging, iterative linear beamforming process. The underlying weighted max-min transmit precoder design enables the proposed scheme to serve users in poor connectivity areas with smaller amounts of data while simultaneously delivering larger amounts to other users. Our new scheme is suitable for large networks due to its linear transceiver structure and it is not constrained by the number of users, cache size, or the number of antennas at the transmitter, unlike the existing schemes. Despite non-uniform cache placement, the proposed scheme still achieves a significant degree of coded caching gain that is additive to the multiplexing gain and greatly outperforms the conventional symmetric CC schemes in terms of both average and 95-percentile delivery time.

Coded caching (CC) schemes exploit the cumulative cache memory of the users and simple linear coding to turn unicast traffic (individual file requests) into a multicast transmission. For the originally proposed$K$-user single-server/single shared link network model, CC yields an$O(K)$gain with respect to conventional uncoded caching with the same per-user memory. While several information-theoretic optimality results for a variety of problems and carefully crafted network topologies have been proved, the gains and suitability of CC for practical scenarios such as content streaming over existing wireless networks have not yet been fully demonstrated. In this work, we consider CC for on-demand video streaming over WLANs where multiple users are served simultaneously by multiple spatially distributed access points (AP). Users sequentially request video “chunks”. The CC scheme operates above the IP layer, leaving the underlying standard physical layer and MAC layer untouched. The cache placement is completely asynchronous and decentralized, and the users are placed at random over the network coverage area. For such a system, we consider the region of achievable long-term average delivery rate (defined as the number of video chunks delivered per unit of time) and study the per-user rate distribution under proportional fairness scheduling. We also consider reduced complexity scheduling strategies and compare them with standard state-of-the-art techniques such as conventional (uncoded) caching and collision avoidance by allocating APs on different sub-channels (i.e., frequency reuse).

Coded caching (CC) techniques have been shown to be conveniently applicable in multi-input multi-output (MIMO) systems. In a K-user network with spatial multiplexing gains of L at the transmitter and G at every receiver, if each user can cache a fraction γ of the file library, a total number of GKγ+ L data streams can be served in parallel. In this paper, we focus on improving the finite-SNR performance of MIMOCC systems. We first consider a MIMO-CC scheme that relies only on unicasting individual data streams, and then, introduce a decomposition strategy to design a new scheme that delivers the same data streams through multicasting of G parallel codewords. We discuss how optimized beamformers could be designed for each scheme and use numerical simulations to compare their finite-SNR performance. It is shown that while both schemes serve the same number of streams, multicasting provides notable performance improvements. This is because, with multicasting, transmission vectors are built with fewer beamformers, leading to more efficient usage of available power resources.

A practical barrier to the implementation of cache-aided networks is dynamic and unpredictable user behavior. In dynamic setups, users can freely depart and enter the network at any moment. The shared caching concept has the potential to handle this issue by assigning K users to P caching profiles, where all ηpusers assigned to profile p store the same cache content defined by that profile. The existing schemes, however, cannot be applied in general and are not dynamic in the true sense as they put constraints on the transmitter-side spatial multiplexing gain α. Specifically, they work only if α ≤ minpηpor $\alpha \geq \hat \eta $, where in the latter case, γ is the normalized cache size of each user, $\hat \eta $is an arbitrary parameter satisfying $1 \leq \hat \eta \leq {\max _p}{\eta _p}$, and the extra condition of α ≥ Kγ should also be met. In this work, we propose a universal caching scheme based on the same shared-cache model that can be applied to any dynamic setup, extending the working region of existing schemes to networks with ${\min _p}{\eta _p} \leq \alpha \leq \hat \eta $ and removing any other constraints of existing schemes. We also derive the closed-form expressions for the achievable degrees-of-freedom (DoF) of the proposed scheme and show that it achieves the optimal DoF for uniform user distributions. Notably, it is the first scheme to achieve the optimal DoF of Kγ + α for networks with uniform user distribution, $\alpha > \hat \eta $, and non-integer $\frac{\alpha }{{\hat \eta }}$, without imposing any other constraints. Finally, we use numerical simulations to assess how non-uniform user distribution impacts the DoF performance and illustrate that the proposed scheme provides a noticeable improvement over unicasting for uneven distributions.

Efficient usage of in-device storage and computation capabilities are key solutions to support data-intensive applications such as immersive digital experiences. This paper proposes a location-dependent multi-antenna coded caching - based content delivery scheme tailored specifically for wireless immersive viewing applications. First, a novel memory allocation process incentivizes the content relevant to the identified wireless bottleneck areas. This enables a trade-off between local and global caching gains and results in unequal fractions of location-dependent multimedia content cached by each user. Then, a novel packet generation process is carried out during the subsequent delivery phase, given the asymmetric cache placement. During this phase, the number of packets transmitted to each user is the same, while the sizes of the packets are proportional to the corresponding location-dependent cache ratios. In this regard, each user is served with location-specific content using joint multicast beamforming and a multi-rate modulation scheme that simultaneously benefits from global caching and spatial multiplexing gains. Numerical experiments and mathematical analysis demonstrate significant performance gains compared to the state-of-the-art.

Immersive viewing, as the next-generation interface for human-computer interaction, is emerging as a wireless application. A genuinely wireless immersive experience necessitates immense data delivery with ultra-low latency, raising stringent requirements for future wireless networks. In this regard, efficient usage of in-device storage and computation capabilities is a potential candidate for addressing these requirements. In addition, recent advancement in multi-antenna transmission has significantly enhanced wireless communication. Hence, this paper proposes a novel location-based multi-antenna coded cache placement and delivery scheme. We first formulate a linear programming cache allocation problem to provide a uniform quality of experience in different network locations; then, cache-placement is done for each location independently. Subsequently, based on the users’ spatial realizations, a transmission vector is created considering diverse available memory at each user. Moreover, a weighted-max-min optimization is used for the beamformers to support different transmission rates. Finally, numerical results are used to show the performance of the proposed scheme.

Multi-antenna coded caching is known to combine a global caching gain that is proportional to the cumulative cache size found across the network, with an additional spatial multiplexing gain that stems from using multiple transmitting antennas. However, a closer look reveals two severe bottlenecks; the well-known exponential subpacketization bottleneck that dramatically reduces performance when the communicated file sizes are finite, and the considerable optimization complexity of beamforming multicast messages when the SNR is finite. We here present an entirely novel caching scheme, termedcyclic multi-antennacoded caching, whose unique structure allows for the resolution of the above bottlenecks in the crucial regime of many transmit antennas. For this regime, where the multiplexing gain can exceed the coding gain, our new algorithm is the first to achieve the exact one-shot linear optimal DoF with a subpacketization complexity that scales only linearly with the number of users, and the first to benefit from a multicasting structure that allows for exploiting uplink-downlink duality in order to yield optimized beamformers ultra-fast. In the end, our novel solution provides excellent performance for networks with finite SNR, finite file sizes, and many users.

In this paper, assuming multi-antenna transmitter and receivers, we consider a multicast beamformer design for the weighted max-min-fairness (WMMF) problem in a multi-stream multi-group communication setup. Unlike the single-stream scenario, the WMMF objective in this setup is not equivalent to maximizing the minimum weighted SINR due to the summation over the rates of multiple streams. Therefore, the non-convex problem at hand is first approximated with a convex one and then solved using Karush-Kuhn-Tucker (KKT) conditions. Then, a practically appealing closed-form solution is derived for both transmit and receive beamformers as a function of dual variables. Finally, we use an iterative solution based on the sub-gradient method to solve for the mutually coupled and interdependent dual variables. The proposed solution does not rely on generic solvers and does not require any bisection loop for finding the achievable rate of various streams. As a result, it significantly outperforms the state-of-art in terms of computational cost and convergence speed.

Immersive viewing is emerging as the next interface evolution for human-computer interaction. A truly wireless immersive application necessitates immense data delivery with ultra-low latency, raising stringent requirements for next-generation wireless networks. A potential solution for addressing these requirements is through the efficient usage of in-device storage and computation capabilities. This paper proposes a novel location-based coded cache placement and delivery scheme, which leverages the nested code modulation (NCM) to enable multi-rate multicasting transmission. To provide a uniform quality of experience in different network locations, we formulate a linear programming cache allocation problem. Next, based on the users' spatial realizations, we adopt an NCM based coded delivery algorithm to efficiently serve a distinct group of users during each transmission. Numerical results demonstrate that the proposed location-based delivery method significantly increases transmission efficiency compared to state of the art.

Large subpacketization requirement is known to be a significant issue in the practical implementation of multiantenna coded caching schemes. In this paper, we introduce a new class of schemes applicable to any network in which the spatial degrees of freedom a is larger than or equal to the coded caching gain. This class of schemes, called diagonal coded caching (DCC), is based on a tabular representation of transmitted codewords and includes consecutive diagonal shifting of such representations over a well-defined placement table. We find the lower-bound for the required subpacketization for any DCC scheme and show that it is achievable using simple, novel algorithms. This not only enables smaller subpacketization compared to state of the art but also makes it possible to control the subpacketization by carefully adjusting the a parameter.

Exponentially growing subpacketization is known to be a major issue for practical implementation of coded caching, specially in networks with multi-antenna communication setups. We provide a new coded caching scheme for such networks, which requires linear subpacketization and is applicable to any set of network parameters, as long as the multi-antenna gain L is larger than or equal to the global caching gain t. Our scheme includes carefully designed cache placement and delivery algorithms; which are based on circular shift of two generator arrays in perpendicular directions. It also achieves the maximum possible degrees of freedom of t+L, during any transmission interval.

Coded caching can be applied in wireless multi- antenna communications by multicast beamforming coded data chunks to carefully selected user groups and using the existing file fragments in user caches to decode the desired files at each user. However, the number of packets a file should be split into, known as subpacketization, grows exponentially with the network size. We provide a new scheme, which enables the level of subpacketization to be selected freely among a set of predefined values depending on basic network parameters such as antenna and user count. A simple efficiency index is also proposed as a performance indicator at various subpacketization levels. The numerical examples demonstrate that larger subpacketization generally results in better efficiency index and higher symmetric rate, while smaller subpacketization incurs significant loss in the achievable rate. This enables more efficient caching schemes, tailored to the available computational and power resources.

Considering cache enabled networks, optimal content placement minimizing the total cost of communication in such networks is studied, leading to a surprising fundamental 0-1 law for non-redundant cache placement strategies, where the total cache sizes associated with each file does not exceed the file size. In other words, for such strategies, we prove that any non-redundant cache placement strategy can be transformed, with no additional cost, to a strategy in which at every node, each file is either cached completely or not cached at all. Moreover, we obtain a sufficient condition under which the optimal cache placement strategy is in fact non-redundant. This result together with the 0-1 law reveals that situations exist, where optimal content placement is achieved just by uncoded placement of whole files in caches.

Smartphones can be viewed as resource pools capable of communicating with their outside world. Such communication capabilities provide unique opportunity for sharing resources, which would result in new possibilities for end users. In this paper, we present a new framework designed for managing mobile local networks, also referred to as Mobile Clouds. In this framework, mobility of nodes is managed by selecting one leader for each cloud, which is responsible for all cloud-level decisions, as well as processing all incoming data from other users. We also evaluate and discuss our proposed framework under different scenarios.