Coordination Strategies for Interference Management in MIMO Dense Cellular Networks

The envisioned rapid and exponential increase of wireless data traffic demand in the next years imposes rethinking current wireless cellular networks due to the scarcity of the available spectrum. In this regard, three main drivers are considered to increase the capacity of today’s most advanced (4G systems) and future (5G systems and beyond) cellular networks: i) use more bandwidth (more Hz) through spectral aggregation, ii) enhance the spectral efficiency per base station (BS) (more bits/s/Hz/BS) by using multiple antennas at BSs and users (i.e. MIMO systems and iii) increase the density of BSs (more BSs/km2) through a dense and heterogeneous deployment (known as dense heterogeneous cellular networks). We focus on the last two drivers. First, the use of multi-antenna systems allows exploiting the spatial dimension for several purposes: improving the capacity of a conventional point-to-point wireless link, increasing the number of served users, and reducing unwanted emissions (interference). Second, dense heterogeneous networks are a simple and cost-effective way to boost the area spectral efficiency by densifying the network with BSs that dispose of different coverage areas and by improving the spatial re-use of the spectrum. However, increasing the density of BSs entails two main technical challenges: i) the interference in the network increases because neighboring BSs/users are nearer, and ii) the amount of data traffic, as well as the downlink (DL) and uplink (UL) traffic asymmetry, varies over space and time more drastically since the number of users per BS is reduced. The increase of interference in the network makes the development of efficient interference management techniques a key enabler for MIMO dense heterogeneous networks. But, as we move towards denser networks, interference management is becoming increasingly challenging. On the other hand, the variability of the per-BS data traffic amount and of the DL/UL traffic asymmetry convert flexible duplexing (i.e. flexible and dynamic allocation of DL/UL resources per BS, either in time or frequency domain) into a necessity for an efficient radio resource usage that meets the non-uniform and time-varying DL/UL per-BS traffic loads. Therefore, the development of traffic-aware resource management schemes capable of adapting to the varying traffic load, as well as interference management, becomes crucial. Accordingly, this doctoral thesis focuses on: 1) the development of advanced interference management techniques to deal with inter-cell interference in MIMO dense cellular networks, and 2) the design of traffic-aware and interference-aware resource management schemes for flexible duplexing systems in asymmetric traffic conditions. To these goals, the wide deployment of MIMO systems is capitalized to develop advanced multi-antenna signal processing techniques when full reuse of time and frequency resources among densely deployed BSs is adopted. In the first part of this work, different statistical characterizations of the transmitted signals are analyzed so as to improve the capacity of wireless interference channels. In this regard, advanced signaling schemes are developed and the use of improper Gaussian signaling (IGS) is investigated, which allows taking advantage of the real and imaginary dimensions of the MIMO channels by splitting one spatial dimension into two halves. Majorization theory is exploited to demonstrate the strict superiority of IGS. Then, the benefits of IGS are applied to different MIMO interference-limited scenarios. Another way to manage interference under full frequency reuse is through the coordination and/or cooperation of BSs. Coordination among BSs allows adjusting in a coordinated manner the transmit strategies at different BSs so as to reduce the impact of interference in the network. In contrast, cooperation among BSs allows BSs to act as a single multi-antenna transmitter and has the great advantage of converting interference into useful signal through the joint transmission of cooperative BSs towards the same user. However, cooperation comes at the cost of a tight synchronization and high backhaul capacity to share user data among cooperative BSs. For that reason, in practical implementations, it can only be achieved between a limited number of BSs (which form a cluster) and coordination among clusters is still needed to deal with interference. Both coordination and cooperation, either implemented in a centralized or decentralized fashion, require knowledge of all channel matrices in the network, which imposes stringent channel estimation requirements for interference management in dense networks. In the second part of the Ph.D. dissertation, transmit coordination strategies are proposed to manage interference in extremely dense cellular networks. The focus is on the DL data transmission. The design of the BSs transmit strategies (involving design of the spatial transmit and receive filters, transmit power control, and scheduling of users) is coordinated with the objective of optimizing different network functions (as, for instance, the weighted sum of the user throughputs) while reducing the stringent requirements needed for channel estimation in dense networks. Coordination strategies for the case in which different signaling schemes (proper and improper) coexist in the network are also derived. Further, the thesis develops coordination strategies for cluster-based joint transmissions, where BSs are grouped into clusters formed by a low number of cooperative BSs and different clusters interfere to each other. In this case, the transmit strategy is jointly optimized together with the user-centric cluster formation. Finally, we address traffic-aware and interference-aware resource management in flexible duplexing systems, where resources have to be properly distributed between DL and UL according to the traffic load and traffic asymmetries of each BSs. Under reuse of resources among densely deployed BSs, the use of flexible duplexing entails changes to the interference generated between neighbor BSs/users. As a consequence, new kinds of interference (like BS to BS) arise. The third part of this thesis focuses on the design of traffic-aware duplexing techniques for resource management and interference management. In contrast to the previous parts, DL and UL data transmissions are considered for each BS. The main objective is to make a better use of the available time/frequency resources by taking into account the asymmetric traffic conditions that arise in dense networks as well as managing the new kinds of interference that come up under flexible duplexing. Short-term and long-term optimizations are investigated, being therefore the interference managed instantaneously and statistically, respectively.