Linear prediction and entropy coding are widely used in speech, audio, video, and other coding systems. Rate-distortion optimization (RDO) is another relevant coding technique, which is especially useful when the encoder performance depends on tunable parameters from distinct coding subsystems. This work presents a RDO strategy for variable-rate encoders that use linear prediction and entropy coding. The method is suitable when the signal to be compressed is short-term stationary and the prediction order varies over signal segments. The second contribution of this paper is to customize the method to the compression of time-domain OFDM-based cellular radio signals. The method enables a 4G / 5G packet-based fronthaul to flexibly trade-off rate and distortion depending on the amount of information to be transmitted and, consequently, benefit from multiplexing gain. Simulation results with LTE signals show that the proposed method achieves improved performance with a relatively low computational cost, while operating with time-domain signals under different traffic scenarios.

Massive Beamforniing systems in next-generation Centralized Radio Access Network architectures can substantially increase the requirements on fronthaul interfaces. This paper proposes a novel and efficient model to reduce the overhead generated by the transfer of beamforming coefficients between base station elements. This approach creates a compressed version for said coefficients, in the beamspace domain, using a clustering strategy over sets (windows) of most powerful beams. The method can be extended for any antenna configuration and also parameterized to adjust the trade-off between radio performance and the fronthaul load reduction. Simulations in typical mobile outdoor scenarios show that the proposed method can present Signal-to-Interference-plus-Noise-Ratio performance comparable to the usual dimensionality reduction approach, i.e., beam selection, while generating lower fronthaul overhead.

In centralized radio access network (C-RAN) architecture, the baseband unit (BBU) is connected to the remote radio unit (RRU) via a fronthaul (FH) interface. For massive MIMO systems in the 5G era, the traditional FH interface (e.g. CPRI) becomes a network bottleneck since the required FH capacity increases proportional to the number of antennas. New functional split between RRU and BBU is thereby considered where RRU carries out more processing than RF-related operation to make the FH traffic only scale based on the number of MIMO layers. This paper provides one alternative of such functional split in the uplink direction implementing interference rejection combining (IRC). The proposed approach reformulates IRC into a zero-forcing (ZF) process and decomposes the latter into two parts. The first part performs maximum ratio combining (MRC) which is much simpler than the full IRC and is therefore implemented in RRU. The second part handles the remaining calculations (such as matrix inversion) with high complexity and is implemented in BBU. The results show that the proposed functional split can deliver performances with both intra- and inter-cell interferences effectively mitigated, while guaranteeing low-complexity RRU implementation and moderate FH-traffic demands, which is proportional to the number of MIMO layers plus interferers.

Provisioning of cost-effective Ethernet-based fronthaul by reusing the LAN infrastructure available in most commercial buildings is challenging predominantly in terms of the required bandwidth and synchronization. In contrast to a synchronous fronthaul, a PTP-based Ethernet network must cope with estimation noise introduced by packet delay variation (PDV) for synchronization recovery. The SYNC packet used for PTP on such networks is expected to suffer from significant PDV due to the fronthaul traffic and other background traffic. Further challenges are met when the switches adopted in the network do not support PTP and therefore synchronization can only be done by end-devices. Focusing on this scenario, this paper analyzes the problems that may affect the time offset estimation accuracy and presents schemes to mitigate these problems. The performance is evaluated through a self-developed FPGA-based testbed and the results suggest that the end-to-end PTP approach can fulfill the less strict time alignment requirements of 3GPP standards if PDV is handled properly.

G.fast is a new standard from the International Telecommunication Union, which targets 1 Gb/s over short copper loops using frequencies up to 212 MHz. This new technology requires accurate parametric cable models for simulation, design, and performance evaluation tests. Some existing copper cable models were designed for the very high speed digital subscriber line spectra, i.e., frequencies up to 30 MHz, and adopt assumptions that are violated when the frequency range is extended to G.fast frequencies. This paper introduces a simple and causal cable model that is able to accurately characterize copper loops composed by single or multiple segments, in both frequency and time domains. Results using G.fast topologies show that, apart from being accurate, the new model is attractive due to its low computational cost and closed-form expressions for fitting its parameters to measurement data.

The use of a hybrid copper and fiber architecture is attractive in both fixed access and mobile backhauling scenarios. This trend led the industry and academia to start developing the fourth generation broadband system, which aims at achieving bit-rates of 1 Gb/s over short copper loops. In this context, accurate models of short twisted-pair cables operating at relatively high frequencies are key elements. This work describes new parametric cable models that incorporate four important characteristics: support of frequencies up to 200 MHz, few parameters, causal impulse responses and require relatively easy fitting procedures. The results show that the models achieve good accuracy for single segments, which are the expected topology for G.fast deployments.

Radio resource management (RRM) across multiple, potentially competing, wireless networks has emerged as a salient feature for future generation system. Besides increased overhead, it will incur more complicated architectures and the question then becomes whether the gains of cooperative RRM (increased throughput, reliability, etc.) can justify these disadvantages. Herein we study potential gains that can be achieved by utilizing sophisticated algorithms in a scenario with two cooperating IEEE 802.11a networks, limited by either the wireless or wired link. Both best-effort (BE) and minimum bit-rate (MBR) are treated and throughout the paper we use the rudimentary minimum path-loss (MPL) allocation as reference. Our results indicate that sophisticated access selection methods that besides path-loss, also account for AP load and potential constraints in the wired connection, can increase performance significantly. The maximum gain varies between 30-60% and 100-150% for BE and MBR traffic respectively and is typically obtained when there, on average, is one user per AP. We also studied the case where APs with constrained wired capacity connected (using the MPL criteria) to high-capacity APs in order to reroute traffic. Contrary to the approach in which advanced allocation principles is used, "loose" network integration is sufficient and even though it gave lower gains for BE data, the achievable rates for MBR data could be improved substantially

This paper presents initial findings on how ambient networks technology will enable new ways to establish and manage access and service provisioning from a business perspective. The concepts of network composition and multi-radio multi-operator wireless access provide the framework for network advertising and discovery, which are essential first steps for allowing "any" user to be able to connect to "any" network. Technology support for different options of advertising are described followed by a discussion of the business related aspects including: i) payment schemes, ii) dynamic pricing, iii) use of identifiers for "frequent users", iv) use of public or "private" directories of offers and v) possibilities with alliances between providers. Finally, results of a case study on dynamic pricing are presented. The conclusion is that the proposed concepts of advertising and discovery indicate a very large potential for enabling a competitive market for both access and service provisioning including support for establishment of agreements on the fly

An important question for future wireless networks is whether the prioritization between different accesses should be controlled by the networks or terminals. Herein we evaluate the performance of distributed access-selection algorithms where terminals are responsible for both AP selection and the necessary measurements. In particular, we focus on determining whether selfish distributed algorithms can perform as well as centralized ones (for comparison we include max-sum, max-min, proportional fair and minimum delay allocations). The study is conducted by time-dynamic simulations in a IEEE 802.11a network and as performance measures we use file transfer delay and supportable load at a maximum tolerable delay. Our results show that selfish algorithms can offer similar performance, both in terms of throughput and fairness, as the centralized schemes as long as they account for both path- loss and access point load. This is an important result and it suggests that terminal-controlled algorithms are just as efficient as centralized schemes, which besides extensive measurements also require that AP exchange information, for improving the efficiency in WLAN networks. Compared with a minimum path- loss selection criteria, which is standard in the IEEE 802.11 family today, our distributed load-aware algorithm increases the maximum supportable load with more than 200 percent even after accounting for measurement time and estimation errors. With fast reselection during ongoing sessions the gains can be further increased with, typically, 20 percent.

Integration of heterogeneous access technologies to provide multi-radio access allows for dynamic access selection. The "always best connected" paradigm can increase system capacity and end user throughput, as well as, reduce the network deployment costs for multi-radio wireless networks. In this paper we present the functional entities generic link layer and multi-radio resource management, and describe their interactions for access selection. A focus of the paper is to show - with an example given for 3G and WLAN - how existing wireless networks can be migrated to provide multi-radio access functionality. This will be explained for a single operator integrating different radio access standards, as well as, for multiple cooperating network operators.

Third generation mobile communication systems will allow many different services with varying demands on data rate and delay. For those systems, the fixed radio resource management (RRM) techniques used in today's low rate systems will not be appropriate to ensure efficient utilization of the radio spectrum. Dynamic RRM is necessary in order to cope with the large variations in data rate. We study the bunch concept which is a hybrid between random and dynamic RRM. Within a small synchronized cluster (bunch) we use dynamic radio resource allocation combined with SIR-based power control and between the bunches we use time/frequency hopping to average the interference. We propose an improved RRM algorithm and evaluate the performance of the bunch concept for a Manhattan scenario with mixed traffic. The performance is improved while the computational complexity is reduced compared to our previously published results for the bunch concept. We also show that the performance of a single bunch system is close to the theoretical upper bound.