Reconfigurable Antennas and Optimized Multi-channel MIMO Designs for DSA Systems with a Broad Frequency Coverage

(supported by NSF under Grant # CNS-1513649)

Principal Investigators: Marwan M. Krunz (PI) and Hao Xin (co-PI)

Summary - Over the last two decades, dynamic and opportunistic spectrum access (DSA/OSA) has been advocated as a new paradigm for improving the utilization of the licensed spectrum below 6 GHz. Spectrum regulators (e.g., FCC, NTIA, etc.) embarked on numerous initiatives that aim at identifying underutilized portions of the licensed spectrum and exploring new models for spectrum sharing among different types of users. These initiatives include the FCC's ruling on TV broadcast channels in the 54 to 698 MHz range (so-called TV whitespaces or TVWS), the FCC's Notice of Proposed Rule Making (NPRM) on the 3.55-3.65 GHz radar band (which lays the groundwork for coexistence between small-cell LTE systems, military radar, and other incumbent systems), and others. Similar initiatives are taking place in other regions of the world, such as the European Union (EU)'s efforts to explore the 2.2-2.3 GHz band for spectrum sharing between aeronautical telemetry radar and small-cell LTE systems. The role of radio spectrum as a critical economic growth engine was highlighted in the 2012 President's Council of Advisors on Science and Technology (PCAST) report, which recommended creating "the first shared-use spectrum superhighways."

Yet, despite this strong push, commercial DSA wireless services have not proliferated. This is in part due to the limited availability of TVWS in urban areas and, more critically, their spatial non-uniformity across the Continental US. Broadcast TV stations in the US are licensed to operate over 6 MHz wide (NTSC) channels that fall into four noncontiguous segments of the spectrum (52-72 MHz, 76-88 MHz, 174-216 MHz, and 470-698 MHz). In a given urban location, the number of TV channels available for opportunistic access can be as low as 2 to 4, after accounting for FCC protection rules (e.g., power masks, adjacent-channel interference, etc.) and "TV pollution" zones, i.e., areas where TV signals are not decodable but are strong enough to disrupt secondary (opportunistic) transmissions. Not only that these channels are too few, but they often have to be shared by several secondary users (SUs), raising the prospects of SU-SU interference. The non-contiguity of available TV channels further complicates matters, as complex carrier/channel aggregation techniques must now be used over a given link to achieve WiFi-comparable channel widths (e.g., 20 MHz and higher).

The overarching goal of the underlying project is to enable DSA operation over a large swath of the opportunistic spectrum below 6 GHz, including the UHF portion of TVWS (470-698 MHz segment), the 3.5 GHz radar band, as well as other bands in the 1 to 4.4 GHz range that may later become candidates for DSA. By aggregating different (not necessarily contiguous) portions of the RF spectrum at the same wireless device, we anticipate that variations in white/grey spaces can be significantly reduced, allowing for sustained DSA operation over a large geographical area. Enabling such operation while maintaining high link throughput requires advances in the following areas:

• Electrically small tunable antennas that allow for dynamic access to narrowband (e.g., 6 MHz) channels, but yet support a broad frequency range from 470 MHz to 4.4 GHz.
• Channel/carrier aggregation techniques for noncontiguous narrowband channels.
• Multi-channel MIMO functionality that allows a given secondary link to boost its throughput (via spatial multiplexing gain) and, simultaneously, minimize interference onto other coexisting systems (via MIMO precoding techniques).

Research Thrusts

1. Reconfigurable Antenna Designs

Figure 1: (a) Proposed antenna design for DSA with a 10:1 frequency-coverage ratio. The antenna switches between high-band operation, which is based on an UWB monopole antenna, and a low-band operation, which is based on a continuously tuned (i.e., via semiconductor varactors) matching network, (b) frequency operation of the proposed antenna. Narrowband channel aggregation in the lower band together with broadband operation in the higher band allow for a compact antenna footprint.

In this thrust, we are designing and demonstrating a novel reconfigurable antenna with high tunability and a wide frequency coverage (a ratio of 10:1 or more between the high and low frequencies). Simultaneously, the antenna will have a small footprint to facilitate MIMO operation on mobile devices. The proposed antenna concept is shown in Figure 1. It combines an ultra-wide-band (UWB) monopole for the higher frequency band (e.g., 1-4 GHz with a 4:1 frequency coverage ratio) with a reconfigurable matching network for the lower frequency range (e.g., 470-1000 MHz). The matching network will not influence the antenna properties because its size is negligible compared with the antenna. Furthermore, since the antenna size is mainly determined by the higher frequency band, it will be much smaller than a conventional broadband antenna without a matching circuit. By switching to a reconfigurable matching network, the 4:1 frequency coverage ratio of the UWB monopole can be further increased by another 2:1 to 3:1. The switching time can be very fast (less than 100 ns). Using the matching network method, the instantaneous bandwidth is narrower but still sufficient for operation over 6-MHz TVWS channels. Therefore, the proposed antenna operates as a broadband antenna at the higher frequency segment and an adaptively tunable narrowband antenna at the lower frequency segment. More importantly, its footprint is determined only by the higher frequency part, which is expected to be in the order of a few centimeters.

In order to extend the lower frequency operation of the antenna to approximately 400 MHz, a continuously tunable matching network, shown in Figure 2, was designed. A semiconductor varactor was used for capacitance tuning. By changing the bias voltage of the varactor, the operating frequency of the antenna varies continuously from 400 MHz to 1.2 GHz. MEMS switches were used in the design for discrete switching between the two operation modes, i.e., 400 MHz to 1 GHz and 1 GHz to 4 GHz. We also plan to augment our antenna design with advanced circuit configurations so as to achieve dynamically tunable channel aggregation of two or more TVWS channels.

Figure 2: (a) Simulation model of the proposed UWB antenna, (b) top view of fabricated prototype, (c) bottom view of fabricated prototype.

2. MIMO Precoding Designs
Our second thrust focuses on exploiting the highly reconfigurable antennas of the previous thrust for real-time adaptation of the MIMO precoding parameters in a dynamic and multi-channel DSA system that operates over a broad frequency range. As a represntative system architecture, we consider a set of opportunistic MIMO-capable WLANs, each controlled by its own access point (AP). Within a given WLAN, three types of MIMO links may be established: downlinks (AP-to-MT), uplinks (MT-to-AP), and peer links (MT-to-MT). Two levels of resource contention exist in the underlying architecture: intra-cell (contention among links of the same WLAN) and inter-cell (contention among APs of different WLANs). To tackle the challenges presented by such an architecture, we follow a hierarchical approach, whereby intra-cell MIMO adaptations of a given WLAN are conducted first by the controlling AP (centralized approach). These adaptations are then used as input for inter-cell resource management, which is conducted in a distributed fashion following a price-based game theoretic approach (and while taking into consideration its implication on intra-cell CMIMO communications).

Because of antenna limitations, the study of MIMO precoding has largely been confined to single-channel systems. More recently, MIMO precoding was investigated in the context of multi-carrier MIMO-OFDM, but the focus was on narrowband channels (i.e., OFDM subcarriers over the same channel). Extending this treatment to the multi-band framework of this project is far from trivial, for a number of reasons. First, because of the drastically different propagation behaviors and fading conditions across bands, different encoders are needed for different channels. More importantly, it is not efficient to optimize the various precoders of a given link separately. Other challenges relate to incorporating the behavior of the reconfigurable antenna into precoder optimization. In particular, the variations in the antenna return loss across frequencies must be accounted for in the precoder design. Furthermore, while our antenna design supports channel aggregation (e.g., 2 to 4 TV channels) in the UHF TVWS segment, there is a tradeoff between the number of aggregated channels and the antenna efficiency. Such a tradeoff must also be accounted for in the optimization of the various precoders. The tasks that are being investigated in this thrust include:

1. Optimal Precoders for Shared-Spectrum Intra-cell Cognitive MIMO Transmissions.
2. Noncooperative Game Theoretic Precoder Designs for Inter-cell Communications.
3. Optimal Precoder Designs for Cognitive MIMO Networks with Exclusive Channel Occupancy.

For Task 1, we consider a single WLAN, and focus on the best performance that this WLAN can achieve. Note that links within the WLAN can interfere with each other and may also have scheduling conflicts (e.g., several transmitters attempting to communicate with the same receiver). Besides power/spectrum adaptation of a typical DSA system, the cognitive MIMO (CMIMO) WLAN involves two additional controls: power allocation over antennas (a.k.a. stream control) and beamforming-based interference management; see Figure 3. The latter control allows a CMIMO link to configure its precoders so as to reduce interference on other links, i.e., facilitate SU-SU coexistence.

Figure 3: Control dimensions in a CMIMO WLAN: (a) Frequency allocation among multiple links, (b) power allocation over frequencies and antennas, and (c) beamforming-based interference suppression. The example shows a WLAN of 4 links, 2 antennas/node, and 3 channels.

To exploit the difference in channel quality among different links (so-called "multi-user diversity"), we augment the feedback from the spectrum database with a cooperative sensing and probing (CSP) mechanism, whose purpose is to allow different links in the same WLAN estimate the CSI of various channels. In this task, we allow various links to access the same spectrum, which leads to to mutual interference. Several scenarios and formulations are being addressed, depending on the target objective function and the optimization window (single or multiple rounds). Some of these formulations are non-convex, and hence quite challenging to solve in exact form. To address these challenges, we are investigating cooperative game theoretic designs, whereby iterative techniques (instead of a single-shot optimization) are used to obtain a near-optimal solution. The global optimization function is replaced by several (node-dependent) local optimization functions with appropriate constraints. Individual nodes perform localized computations and report the results to the AP, which then determines the final outcome. This approach is being applied to various objective functions. We are also exploring cooperative sensing and probing (S&P) strategies that are intended to supplement the coarse-grain database-acquired channel availability information. The proposed cooperative S&P protocol allows multiple links to concurrently sense and probe selected channels while minimizing the total time needed to acquire CSI for all channels over all links. It uses an adaptive control-frame structure whereby the sensing of certain channel/link combinations may often be skipped, depending on the likelihood of a change in the channel status (which is a function of the channel's coherence time and user dynamics). In contrast to classic S&P approaches in which periodic probing is performed over various channels indiscriminantly, in our scheme links are scheduled for sensing/probing processes so as to maximize the chances that the probed channels will meet the total rate demands of various SU links within a given sensing-time constraint.

Related Publications

1. Diep Nguyen, Marwan Krunz, and Stephen Hanly, “Distributed bargaining mechanisms for MIMO dynamic spectrum access systems,” IEEE Transactions on Cognitive Communications and Networking, vol. 1, no. 1, pp. 113-127, Jan. 2016.
2. S. Ershadi, A. Abdelrahman, M. Liang, X. Yu, and H. Xin, “A novel reconfigurable broadband antenna for cognitive radio systems,” Proceedings of the IEEE Antennas and Propagation Symposium, Puerto Rico, July 2016.
3. Jocelyne Elias, Fabio Martignon, Lin Chen, and Marwan Krunz, “Distributed spectrum management in TV white space networks,” accepted for publication in the IEEE Transactions on Vehicular Technology.
4. Mohammad Abdel Rahman, Harish Kumar, and Marwan Krunz, “QoS-aware parallel sensing/probing architecture and adaptive cross-layer protocol design for opportunistic networks,” IEEE Transactions on Vehicular Technology, vol. 65, issue 4, pp. 2231-2242, April 2016.
5. Wessam Afifi and Marwan Krunz, “TSRA: An adaptive mechanism for switching between communication modes in full-duplex opportunistic spectrum access systems,” accepted for publication in the IEEE Transactions on Mobile Computing.
6. Mahmoud Ashour, M. Majid Butt, Amr Mohamed, Tamer ElBatt, and Marwan Krunz, “Energy-aware cooperative wireless networks with multiple cognitive users,” accepted for publication in the IEEE Transactions on Communications.