Uplink massive multiple-input multiple-output (MIMO) improves network spectral efficiency by enabling simultaneous transmission from multiple users through spatial multiplexing. Although the centralized radio access network (C-RAN) architecture can meet the increased signal processing requirements, the large number of used antenna elements creates challenges for the fronthaul (FH) links required to transport a large amount of traffic from remote radio units (RRUs) to the centralized baseband unit (BBU). To reduce the FH link load, different baseband splitting options between RRUs and BBU are considered in practical C-RAN networks. More specifically, low complexity maximum ratio combining (MRC) beamforming at the RRU can be used to reduce the number of spatial dimensions of the received signals before transporting them to the BBU for further baseband processing. Despite the high compression efficiency of the MRC-based approach, we find that its performance is not sufficiently robust under channel varying conditions due to rapid user mobility. In this paper, we propose a functional split based on an extension of MRC compression at the RRU which provides better uplink performance for scenarios with high mobility, while guaranteeing moderate FH link throughput and low signal processing complexity.

3GPP 5G New Radio (NR) wireless access technology will support communication at bands ranging from sub GHz to millimeter wave. For communication at millimeter wave, e.g., at 60 GHz, the transmitted signal experiences severe attenuation, due to outdoor-to-indoor penetration, oxygen absorption, etc., significantly degrading the link budget performance of the NR system. In order to achieve good coverage for NR systems, operating at all bands, it is important to ensure the support of power efficient waveforms for physical channels carrying data and reference signals. Demodulation reference signals (DM-RS) are used in 5G NR systems to assist receivers in estimation of the wireless channel for subsequent coherent processing of the corresponding received data on the physical channel. In this paper, we propose a novel design of DM-RS that achieves channel estimation performance similar to NR Release 15 DM-RS, while providing higher power efficiency. The proposed DM-RS design in conjunction with power efficient waveforms for physical channel can thus be used to enhance coverage of NR systems operating at higher carrier frequency ranges of millimeter wave bands, e.g. 60 GHz. We corroborate our claims via computer simulations.

5G-NR (New Radio) specifications have enabled broadband mmWave deployments that can leverage analog beamforming to overcome propagation losses at bands such as 30GHz. We describe how analog beamforming at the BS and at the UE side has significantly impacted the 5G-NR specifications, system design and system performance. We describe the newly introduced set of beam management procedures in 5G-NR that allows such a UE to access the network and maintain connectivity. We observe from simulation results that (in a SU-MIMO system) given a fixed array size, increasing the spatial resolution of the analog beams bring little benefit. However, increasing the array size without increasing the number baseband antenna ports (transceivers) brings significant system gains. We also provide results that show analog beamforming in elevation dimension (3D) is particularly beneficial in dense deployments with above rooftop BS height.

Fog radio access network (F-RAN) architectures can leverage both cloud processing and edge caching for content delivery to the users. To this end, F-RAN utilizes caches at the edge nodes (ENs) and fronthaul links connecting a cloud processor to ENs. Assuming time-invariant content popularity, existing information-theoretic analyses of content delivery in F-RANs rely on offline caching with separate content placement and delivery phases. In contrast, this paper focuses on the scenario in which the set of popular content is time-varying, hence necessitating the online replenishment of the ENs' caches along with the delivery of the requested files. The analysis is centered on the characterization of the long-term normalized delivery time (NDT), which captures the temporal dependence of the coding latencies accrued across multiple time slots in the high signal-to-noise ratio regime. Online edge caching and delivery schemes are investigated for both serial and pipelined transmission modes across fronthaul and edge segments. Analytical results demonstrate that, in the presence of a time-varying content popularity, the rate of fronthaul links sets a fundamental limit on the long-term NDT of F-RAN system. Analytical results are further verified by numerical simulation, yielding important design insights.

In a Fog Radio Access Network (F-RAN) architecture, edge nodes (ENs), such as base stations, are equipped with limited-capacity caches, as well as with fronthaul links that can support given transmission rates from a cloud processor. Existing information-theoretic analyses of content delivery in F-RANs have focused on offline caching with separate content placement and delivery phases. In contrast, this work considers an online caching set-up, in which the set of popular files is time-varying and both cache replenishment and content delivery can take place in each time slot. The analysis is centered on the characterization of the long-term Normalized Delivery Time (NDT), which captures the temporal dependence of the coding latencies accrued across multiple time slots in the high signal-to-noise ratio regime. Online caching and delivery schemes based on reactive and proactive caching are investigated, and their performance is compared to optimal offline caching schemes both analytically and via numerical results.

Caching at the network edge has emerged as a viable solution for alleviating the severe capacity crunch in modern content centric wireless networks by leveraging network load-balancing in the form of localized content storage and delivery. In this paper, we consider a cache-aided network, where the cache storage phase is assisted by a central server and users can demand multiple files at each transmission interval. To service these demands, we consider two delivery models: (1) centralized content delivery, where user demands at each transmission interval are serviced by the central server via multicast transmissions; and (2) device-to-device assisted distributed delivery, where users multicast to each other in order to service file demands. For such cache-aided networks, we present new results on the fundamental cache storage versus transmission rate tradeoff. Specifically, we develop a new technique for characterizing information theoretic lower bounds on the storage-rate tradeoff and show that the new lower bounds are strictly tighter than cut-set bounds from literature. Furthermore, using the new lower bounds, we improve the constant factor approximation of the optimal storage-rate tradeoff for cache-aided systems under both delivery models.

A fog-aided wireless network architecture is studied in which edge nodes (ENs), such as base stations, are connected to a cloud processor via dedicated fronthaul links while also being endowed with caches. Cloud processing enables the centralized implementation of cooperative transmission strategies at the ENs, albeit at the cost of an increased latency due to fronthaul transfer. In contrast, the proactive caching of popular content at the ENs allows for the low-latency delivery of the cached files, but with generally limited opportunities for cooperative transmission among the ENs. The interplay between cloud processing and edge caching is addressed from an information-theoretic viewpoint by investigating the fundamental limits of a high signal-to-noise-ratio metric, termed normalized delivery time (NDT), which captures the worst case coding latency for delivering any requested content to the users. The NDT is defined under the assumptions of either serial or pipelined fronthaul-edge transmission, and is studied as a function of fronthaul and cache capacity constraints. Placement and delivery strategies across both fronthaul and wireless, or edge, segments are proposed with the aim of minimizing the NDT. Information-theoretic lower bounds on the NDT are also derived. Achievability arguments and lower bounds are leveraged to characterize the minimal NDT in a number of important special cases, including systems with no caching capabilities, as well as to prove that the proposed schemes achieve optimality within a constant multiplicative factor of 2 for all values of the problem parameters.

Caching is a viable solution for alleviating the severe capacity crunch in modern content centric wireless networks. Parts of popular files are pre-stored in users' cache memories such that at times of heavy demand, users can be served locally from their cache content thereby reducing the peak network load. In this work, we consider a central server assisted caching network where files are jointly delivered to users through multicast transmissions. For such a network, we develop a new information theoretic lower bound on the fundamental cache storage vs. transmission rate tradeoff, which strictly improves upon the best known existing bounds. The new bounds are used to establish the approximate storage vs. rate tradeoff of centralized caching to within a constant multiplicative factor of 8.

Caching is emerging as a vital tool for alleviating the severe capacity crunch in modern content-centric wireless networks. The main idea behind caching is to store parts of the popular content in end-users' memory and leverage the locally stored content to reduce peak data rates. By jointly designing content placement and delivery mechanisms, recent works have shown order-wise reduction in transmission rates in contrast to traditional methods. In this paper, we consider the secure caching problem with the additional goal of minimizing information leakage to an external wiretapper. The fundamental cache memory versus transmission rate tradeoff for the secure caching problem is characterized. Rather surprisingly, these results show that security can be introduced at a negligible cost, particularly for large number of files and users. It is also shown that the rate achieved by the proposed caching scheme with secure delivery is within a constant multiplicative factor from the information-theoretic optimal rate for almost all parameter values of practical interest.

Caching has emerged as a vital tool in modern communication systems for reducing peak data rates by allowing popular fles to be pre-fetched and stored locally at end users' devices. In this paper, the concept of information theoretic security for content delivery with decentralized caching is introduced. The proposed secure caching scheme allows users to cache content in a decentralized manner and reduces the peak rate by leveraging local and global caching gains, while securely delivering requested content to the users. The analysis of the secure decentralized caching problem is presented which shows that the proposed scheme introduces security at a negligible cost in terms of achievable rate when compared to insecure decentralized caching schemes, particularly for large number of fles and users. It is also shown that the rate of the proposed secure scheme is within a constant multiplicative factor from the information theoretic optimal rate for feasible values of problem parameters.

In this paper, we propose a novel design of concatenated Space-Time Block Codes (STBCs) using Systematic Redundant Residue Number System (RRNS) codes. The link between residues and complex signal constellations is optimized by incorporating the "Direct Mapping", "Prior probability based Distance Aware Mapping" and "Indirect Mapping" schemes. We analytically quantify the upper bounds on the codeword and bit error probabilities of Systematic RRNS-STBC and characterize the achievable coding and diversity gains assuming maximum likelihood decoding (MLD). We propose an Adaptive M-ary Demapping scheme for ML decoding, which exploits the RRNS code structure to decrease complexity and provide further performance improvement over the Distance Aware Mapping scheme. It is shown that Indirect Mapping, when used for RRNS coding schemes can offer more efficient transmission and performance than naive M-ary mapping. It is also seen that Systematic RRNS-STBC codes provide superior performance compared to Non-systematic RRNS-STBC, for the same code parameters, owing to more efficient binary to residue mapping.