Analog MIMO Radio-over-Copper: Prototype and Preliminary Experimental Results

Analog Multiple-Input Multiple-Output Radio-over-Copper (A-MIMO-RoC) is an effective all-analog FrontHaul (FH) architecture that exploits any pre-existing Local Area Network (LAN) cabling infrastructure of buildings to distribute Radio-Frequency (RF) signals indoors. A-MIMO-RoC, by leveraging a fully analog implementation, completely avoids any dedicated digital interface by using a transparent end-to-end system, with consequent latency, bandwidth and cost benefits. Usually, LAN cables are exploited mainly in the low-frequency spectrum portion, mostly due to the moderate cable attenuation and crosstalk among twisted-pairs. Unlike current systems based on LAN cables, the key feature of the proposed platform is to exploit more efficiently the huge bandwidth capability offered by LAN cables, that contain 4 twisted-pairs reaching up to 500 MHz bandwidth/pair when the length is below 100 m. Several works proposed numerical simulations that assert the feasibility of employing LAN cables for indoor FH applications up to several hundreds of MHz, but an A-MIMO-RoC experimental evaluation is still missing. Here, we present some preliminary results obtained with an A-MIMO-RoC prototype made by low-cost all-analog/all-passive devices along the signal path. This setup demonstrates experimentally the feasibility of the proposed analog relaying of MIMO RF signals over LAN cables up to 400 MHz, thus enabling an efficient exploitation of the LAN cables transport capabilities for 5G indoor applications.Comment: Part of this work has been accepted as a conference publication to ISWCS 201

Business Innovation Strategies to Reduce the Revenue Gap for Wireless Broadband Services

Mobile broadband is increasing rapidly both when it comes to traffic and number of subscriptions. The swift growth of the demand will require substantial capacity expansions. Operators are challenged by the fact that revenues from mobile broadband are limited, just a few per cent of APRU, and thus not compensating for declining voice revenues, creating a so called "revenue gap". Concurrently, mobile broadband dominates the traffic, set to grow strongly. In this paper we analyze the potential of different strategies for operators to reduce or bridge the revenue gap. The main options are to reduce network costs, to increase access prices and to exploit new revenue streams. The focus in the paper is on cost & capacity challenges and solutions in the network domain. Operators can cooperate and share sites and spectrum, which could be combined with off-loading heavy traffic to less costly local networks. In the network analysis we illustrate the cost impacts of different levels of demand, re-use of existing base station sites, sharing of base stations and spectrum and deployment of a denser network. A sensitivity analysis illustrates the impact on total revenues if access prices are increased, whether new types of services generate additional revenues, and if it fills the revenue gap. Our conclusion is that the different technical options to reduce the revenue gap can be linked to business strategies that include cooperation with both other operators as well as with non-telecom actors. Hence, innovations in the business domain enable technical solutions to be better or fully exploited.Wireless Internet access, data traffic, revenues, network costs, spectrum, deployment strategies, HSPA, LTE, operator cooperation, value added services, NFC, B2B2C.

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

Mobile Communications Industry Scenarios and Strategic Implications for Network Equipment Vendors

Mobile infrastructure markets have changed dramatically during the past years. The industry is experiencing a shift from traditional large-scale, hardware-driven system roll-outs to software and services -driven business models. Also, the telecommunications and internet worlds are colliding in both mobile infrastructure and services domains requiring established network equipment vendors and mobile operators to transform and adapt to the new business environment. This paper utilizes Schoemaker's scenario planning process to reveal critical uncertain elements shaping the future of the industry. Four possible scenarios representing different value systems between industry's key stakeholders are created. After this, five strategic options with differing risk and cost factors for established network equipment vendors are discussed in order to aid firm's strategic planning process. --

Advanced Technologies Enabling Unlicensed Spectrum Utilization in Cellular Networks

As the rapid progress and pleasant experience of Internet-based services, there is an increasing demand for high data rate in wireless communications systems. Unlicensed spectrum utilization in Long Term Evolution (LTE) networks is a promising technique to meet the massive traffic demand. There are two effective methods to use unlicensed bands for delivering LTE traffic. One is offloading LTE traffic toWi-Fi. An alternative method is LTE-unlicensed (LTE-U), which aims to directly use LTE protocols and infrastructures over the unlicensed spectrum. It has also been pointed out that addressing the above two methods simultaneously could further improve the system performance. However, how to avoid severe performance degradation of the Wi-Fi network is a challenging issue of utilizing unlicensed spectrum in LTE networks. Specifically, first, the inter-system spectrum sharing, or, more specifically, the coexistence of LTE andWi-Fi in the same unlicensed spectrum is the major challenge of implementing LTE-U. Second, to use the LTE and Wi-Fi integration approach, mobile operators have to manage two disparate networks in licensed and unlicensed spectrum. Third, optimization for joint data offloading to Wi-Fi and LTE-U in multi- cell scenarios poses more challenges because inter-cell interference must be addressed. This thesis focuses on solving problems related to these challenges. First, the effect of bursty traffic in an LTE and Wi-Fi aggregation (LWA)-enabled network has been investigated. To enhance resource efficiency, the Wi-Fi access point (AP) is designed to operate in both the native mode and the LWA mode simultaneously. Specifically, the LWA-modeWi-Fi AP cooperates with the LTE base station (BS) to transmit bearers to the LWA user, which aggregates packets from both LTE and Wi-Fi. The native-mode Wi-Fi AP transmits Wi-Fi packets to those native Wi-Fi users that are not with LWA capability. This thesis proposes a priority-based Wi-Fi transmission scheme with congestion control and studied the throughput of the native Wi-Fi network, as well as the LWA user delay when the native Wi-Fi user is under heavy traffic conditions. The results provide fundamental insights in the throughput and delay behavior of the considered network. Second, the above work has been extended to larger topologies. A stochastic geometry model has been used to model and analyze the performance of an MPTCP Proxy-based LWA network with intra-tier and cross-tier dependence. Under the considered network model and the activation conditions of LWA-mode Wi-Fi, this thesis has obtained three approximations for the density of active LWA-mode Wi-Fi APs through different approaches. Tractable analysis is provided for the downlink (DL) performance evaluation of large-scale LWA networks. The impact of different parameters on the network performance have been analyzed, validating the significant gain of using LWA in terms of boosted data rate and improved spectrum reuse. Third, this thesis also takes a significant step of analyzing joint multi-cell LTE-U and Wi-Fi network, while taking into account different LTE-U and Wi-Fi inter-working schemes. In particular, two technologies enabling data offloading from LTE to Wi-Fi are considered, including LWA and Wi-Fi offloading in the context of the power gain-based user offloading scheme. The LTE cells in this work are subject to load-coupling due to inter-cell interference. New system frameworks for maximizing the demand scaling factor for all users in both Wi-Fi and multi-cell LTE networks have been proposed. The potential of networks is explored in achieving optimal capacity with arbitrary topologies, accounting for both resource limits and inter-cell interference. Theoretical analyses have been proposed for the proposed optimization problems, resulting in algorithms that achieve global optimality. Numerical results show the algorithms’ effectiveness and benefits of joint use of data offloading and the direct use of LTE over the unlicensed band. All the derived results in this thesis have been validated by Monte Carlo simulations in Matlab, and the conclusions observed from the results can provide guidelines for the future unlicensed spectrum utilization in LTE networks

Exposure optimization in indoor wireless networks by heuristic network planning

Due to the increased use of indoor wireless networks and the concern about human exposure to radio-frequency sources, exposure awareness has increased during recent years. However, current-day network planners rarely take into account electric-field strengths when designing networks. Therefore, in this paper, a heuristic indoor network planner for exposure calculation and optimization of wireless networks is developed, jointly optimizing coverage and exposure, for homogeneous or heterogeneous networks. The implemented exposure models are validated by simulations and measurements. As a first novel optimization feature, networks are designed that do not exceed a user-defined electric-field strength value in the building. The influence of the maximally allowed field strength, based on norms in different countries, and the assumed minimal separation between the access point and the human are investigated for a typical office building. As a second feature, a novel heuristic exposure minimization algorithm is presented and applied to a wireless homogeneous WiFi and a heterogeneous WiFi-LTE femtocell network, using a new metric that is simple but accurate. Field strength reductions of a factor 3 to 6 compared to traditional network deployments are achieved and a more homogeneous distribution of the observed field values on the building floor is obtained. Also, the influence of the throughput requirement on the field strength distribution on the building floor is assessed. Moreover, it is shown that exposure minimization is more effective for high than for low throughput requirements and that high field values are more reduced than low field values