Fair resource allocation in the citizens broadband radio service band

In the Citizens Broadband Radio Service (CBRS) band, the Federal Communications Commission (FCC) has set stringent timing constraints for the lower tier users to vacate the channel on which an incumbent shipborne radar appears. The standards body formulating various specifications for the CBRS operation has taken these timing constraints into consideration in the Spectrum Access System (SAS) - CBRS Device (CBSD) protocol. A transmitting CBSD continually heartbeats with its SAS. When required, the SAS sends commands to vacate a channel through these heartbeat messages. In this paper, we study the impact of the heartbeat interval on the CBRS system in terms of meeting the FCC timing constraints. We also study how the heartbeat interval can overload a SAS and how it can be used to determine the number of CBSDs a SAS can serve without causing unnecessary suspension of CBSD transmissions. We show the tradeoff between using a short heartbeat interval to meet the timing constraint early and the number of CBSDs that can be served by a SAS without causing unnecessary suspension of CBSD transmissions.

The General Authorized Access (GAA) users in the Citizens Broadband Radio Service (CBRS) band are the lowest priority users who not only have to make sure that they do not cause harmful interference to the higher tier users but also must cooperate with each other to minimize potential interference among themselves. Thus, efficient GAA coexistence scheme is essential for operation of GAA users and to obtain high spectrum utilization. Towards this goal, the Wireless Innovation Forum (WInnForum) has recommended three schemes to facilitate coexistence among the GAA users. To the best of our knowledge, there is no performance study on any of these schemes available in the public domain. In this paper, we study performance of one of these schemes (called Approach 1). We choose two actual locations in the USA around which our study is conducted using actual terrain and land cover data of the continental USA. We evaluate performance of the scheme at different deployment densities, using different propagation models and with different mix of CBRS devices (CBSDs) at those two locations. We provide some interesting insights into the bandwidth allocation process and performance of Approach 1 in terms of mutual interference.

The General Authorized Access (GAA) users in the Citizens Broadband Radio Service (CBRS) band are the lowest priority users. They must make sure that they do not cause harmful interference to the higher tier users while cooperating with each other to minimize potential interference among themselves. Thus, efficient GAA coexistence scheme is essential for the operation of GAA users and to obtain high spectrum utilization. Towards this goal, the Wireless Innovation Forum (WInnForum) has recommended three schemes to facilitate GAA-GAA coexistence. We had reported a performance study of one of these schemes (called Approach 1), but that study did not have any Coexistence Group (CxG). A CxG is responsible for managing interference among its CBRS devices (CBSDs). In this paper, we study the performance of Approach 1 without CxGs as well as with different number of CxGs, in various configurations. We conduct our study around two locations in the USA using actual terrain and land cover data of the continental USA. We evaluate performance of the scheme at different deployment densities, using different propagation models at those two locations with different number of CxGs. We provide some interesting insights into the costs and benefits of having CxGs in the deployment.

The General Authorized Access (GAA) users operate at the lowest priority in the Citizens Broadband Radio Service (CBRS) band. So, they must not cause harmful interference to the higher priority users and must cooperate with each other to minimize mutual interference and increase spectrum utilization. Towards this goal, the Wireless Innovation Forum (WInnForum), a standards body, has recommended three schemes. We study performance of one of the schemes, called Approach 3. To the best of our knowledge, there is no performance study available for Approach 3. WInnForum does not specify any performance metrics to evaluate the schemes. We define few performance metrics for Approach 3 that will be useful for the operators in deciding their operating parameters. We choose two actual locations and use real terrain and land cover data of continental USA in our simulation study. Hence, we expect our results to be similar to practical implementations.

Opening the Citizen Broadband Radio Service (CBRS) band in the US to secondary users offers unprecedented opportunities to LTE and 5G networks, as long as incumbent radar signals are protected from interference. Towards this aim, the US Federal Communications Commission (FCC) requires Environmental Sensing Capabilities (ESCs) to be installed along the coastal regions. Furthermore, FCC mandates that the secondary users transmit with low power levels, such that the aggregated interference and noise power in the vicinity of ESC sensors remains below −109 dBm/MHz. At this interference level, the ESC must detect 99 % of radar pulses with peak power of at least −89 dBm/MHz. In this paper, we design an enhanced ESC sensor, called ESC+, that leverages the deep learning framework called 'you only look once’ (YOLO) for signal detection using spectrograms. We propose a two-stage spectrogram-based coarse and fine signal analysis method for: (i) detecting, and characterizing radar pulses in environments where the aggregated noise and interference level goes beyond FCC restrictions, and (ii) detecting and characterizing other signal types (e.g., 5G and LTE) in the CBRS band, with a goal of determining unauthorized users. We generate a realistic spectrogram dataset in MATLAB consisting of three signal types of radar, 5G, and LTE where the aggregated interference and noise power occurring concurrently with the radar pulse is varied upto −104 dBm/MHz. We show 100% radar pulse detection in interference and noise levels of up to 3 dB higher than what is required today.

Open RAN (O-RAN) has the potential for revolutionizing not only cellular communication but also spectrum sensing by carefully controlling uplink/downlink traffic in shared spectrum bands. In this paper, we present the design of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SenseORAN</i> , which detects the presence of radar pulses within the Citizens Broadband Radio Service (CBRS) band. SenseORAN is especially useful for scenarios where these pulses (highest priority) are fully overlapping with interfering LTE signals (secondary priority licensee), requiring immediate detection of such an occurrence. This design paradigm of re-using existing cellular infrastructure with ORAN-compliant sensing and communication slices can potentially eliminate the need for dedicated spectrum sensors along the coastline as well as severe restrictions on the transmit power for the LTE operators that are enforced today. Our approach involves a machine learning module deployed as a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Radar Detection xApp</i> at the near-Real-Time (near-RT) Radio Access Network (RAN) Intelligent Controller, i.e., near-RT RIC. The base station or gNB (i) uses the you-only-look-once (YOLO)-based machine learning framework that is modified to detect radar signals present within spectrograms generated from I/Q samples collected during the regular uplink cellular operation, and (ii) maintains a list of ‘occupied’ channels in the 3.5 GHz CBRS band that indicate radar presence. Our design is validated with (i) an over the air collected dataset composed of Type 1 radar and standard-compliant LTE waveforms, and (ii) an experimental testbed of SDRs running a complete Open RAN stack with a near-RT RIC implementation integrated with our YOLO-based xApp. We show radar detection accuracy of 100% under SINR conditions ≥ 12 dB after combining 7 spectrograms into a single decision. Furthermore, using testbed results, we demonstrate that the gNB can be reconfigured to avoid radar interference within 866 ms, which represents a reduction of 85.5% over the 60 s response time mandated for pausing cellular operation in detecting radar presence in the CBRS band today.

By implementing reinforcement learning-aided listen-before-talk (LBT) schemes over a citizens broadband radio service (CBRS) network, we increase the spatial reuse at secondary nodes while minimizing the interference footprint on higher-tier nodes. The federal communications commission encourages “use-or-share” policies in the CBRS band across the priority access license (PAL)–general authorized access (GAA) priority tiers by opportunistically allowing the lower-priority GAA nodes to access unused higher-priority PAL spectrum. However, there is currently no mechanism to enable this cross-tier spectrum sharing. In this paper, we propose and evaluate LBT schemes that allow opportunistic access to PAL spectrum. We find that by allowing LBT in a two carrier, two eNB scenario, we see upward of 50% user perceived throughput (UPT) gains for both eNBs. Furthermore, we examine the use of ${Q}$ -learning to adapt the energy-detection threshold (EDT), combating problematic topologies, such as hidden and exposed nodes. With merely a 4% reduction in primary node UPT, we see up to 350% gains in average secondary node UPT when adapting the EDT of opportunistically transmitting nodes.

The opening up of the 3550-3700 MHz band in the US for Citizen's Broadband Radio Service (CBRS) represents a new opportunity for deploying spectrum-sharing cellular networks. The three-tier structure of the CBRS sharing regime with different interference protection constraints per tier imposes a coexistence challenge for networks based on Long-Term Evolution (LTE). As a result, contention-based channel access mechanisms can be incorporated into LTE networks as a method of sharing frequency channels assigned by the Spectrum Access System (SAS). In this work, we examine the design and implications of contention- based channel access for the lowest CBRS tier that comprises opportunistic users known as General Authorized Access (GAA) devices. In particular, we assess the suitability of Listen-Before-Talk (LBT) for GAA channel access. Performance evaluations for an outdoor deployment scenario show that LBT- based coexistence is effective for low-power GAA users or symmetric power situations, while a combination of LBT and channel allocation is preferred for asymmetric power situations with a mix of low and high-power GAA transmitters.

The 3.5 GHz citizens broadband radio service (CBRS) band in the U.S. is a key portion of mid-band spectrum shared between commercial operators and existing federal and non-federal incumbents. To protect the federal incumbents from harmful interference, a spectrum access system (SAS) is required to use a common, standardized algorithm, called the move list algorithm, to suspend transmissions of some CBRS devices (CBSDs) on channels in which the incumbent becomes active. However, the current reference move list implementation used for SAS testing is non-deterministic in that it uses a Monte Carlo estimate of the 95th percentile of the aggregate interference from CBSDs to the incumbent. This leads to uncertainty in move list results and in the aggregate interference check of the test. This paper uses upper and lower bounds on the aggregate interference distribution to compute deterministic move lists. These include the reference move list used by the testing system and an operational move list used by the SAS itself. We evaluate the performance of the proposed deterministic move lists using reference implementations of the standards and simulated CBSD deployments in the vicinity of federal incumbent dynamic protection areas.

As a frontier in dynamic spectrum sharing, the citizens broadband radio service (CBRS) system has been proposed by FCC, where three-tiered users are allowed to share the same spectrum. To manage the interference among different layered users, a centralized spectrum access system (SAS) combined with a central database is utilized to coordinate the spectrum access of lower-tiered users. Therefore, the centralized management architecture of the CBRS system cannot efficiently manage very large scale and large quantity of users, and may also suffer severe security and privacy issues. To address these problems, in this paper, we propose a new blockchain-assisted dynamic spectrum management model based on existing CBRS model, where the blockchain technology is leveraged to improve the spectrum management efficiency and quality-of-service of the GAA users. Furthermore, we design a detailed flow of the spectrum management of GAA users, where a dedicated graph coloring algorithm is proposed to obtain the optimal channel assignment strategy. Simulation results have increased the ratio of GAA users licensed and improved spectrum utilization under the proposed algorithm.

Spectrum Access System (SAS) is a three-tier spectrum sharing framework proposed for 3.5 GHz by Federal Communication Commission (FCC) in the United States. General Authorized Access (GAA) users in SAS do not have an assigned channel and can opportunistically access the Priority Access Licensee (PAL) channel satisfying the interference constraint proposed by FCC. Coexistence among GAA users in SAS is a key problem to be solved to enhance the system capacity to meet the increasing traffic demand. In this work, we propose a method for fair and efficient spectrum utilisation for GAA users. To achieve the fairness among GAA users equal interference budget allocation scheme is proposed for each set of GAA users that can hear each other. Our proposed method decide the optimal channel switching schedule that maximises the average capacity of GAA users while satisfying the interference constraint at PAL protection area. This work jointly considers the fairness between GAA users and the average capacity maximisation of GAA network. Simulation result justifies the performance of our proposed method for average capacity maximisation of GAA users and fairness between GAA users by comparing with existing works.

Dynamic spectrum sharing (DSS) has recently attracted keen interest from regulatory bodies around the world as a key strategy to overcome spectrum scarcity in beyond 5G networks. In the United States, the Federal Communications Commission has adopted a three-tier DSS model for the Citizens Broadband Radio Service (CBRS) band managed by a spectrum access system (SAS) to share incumbents' spectrum with commercial cellular broadband applications. In this article, we first present a survey of current DSS approaches and their limitations and then discuss the benefits of using in-band full-duplex (IBFD) techniques in DSS networks. To illustrate the improvement in the performance of priority access license (PAL) and general authorized access (GAA) users in an IBFD-assisted CBRS, we consider a CBRS mobile broadband network (MBN) architecture comprising an incumbent in the form of a MIMO radar system and an IBFD MIMO MBN, consisting of PAL and GAA users. In particular, we design joint beamformers at the MBN, with constraints on transmit power at the MBN and detection probability of the radar system, and beamformers at the radar system to mitigate the interference from the radar system toward the cellular system. It is shown that the IBFD CBRS network architecture not only leads to improved performance of PAL and GAA users, but does so while producing less interference toward the radar than state-of-the-art half-duplex solutions. Finally, we present some open research challenges to invigorate research on beyond 5G IBFD DSS networks.

The optimal use of spectrum is a key focus for all regulatory bodies. Federal Communications Commission has introduced Spectrum Access System (SAS) to maximise the spectrum utilisation in the US 3.5 GHz band. SAS is a three-tier spectrum sharing framework where Citizen Broadband Radio Service (CBRS) devices can access the channel when it is not used by Incumbent Access users. CBRS consists of Priority Access Licensee (PAL) and General Authorized Access (GAA). In this paper, we consider the problem of optimum transmit power allocation for GAA users using a carrier sensing range i.e. maximum distance a user can be sensed while guaranteeing the interference to PAL from GAA users is below the threshold. We use carrier sensing range to find the sets of GAA users that cannot transmit at the same time and adjust the interference budget of transmitting GAA users. We present an algorithm for transmit power allocation for GAA users in the SAS. The proposed algorithm uses the transmission characteristics and location information provided by Citizen Broadband Radio Service Devices to SAS to maximise the peak capacity of GAA users ensuring the interference constraint to PAL. Simulation results show that the proposed algorithm significantly increases the peak capacity of GAA users by considering the carrier sensing range and adjusted interference budget.

Spectrum access system (SAS) is a three-tier layered spectrum sharing architecture proposed by the Federal Communications Commission (FCC) for Citizen broadband radio service (CBRS) 3.5 GHz band. The available 150 MHz spectrum is dynamically shared among Incumbent Access (IA), Primary Access Licensees (PAL) and General Authorized Access (GAA) users. IA users are the highest priority federal military users, PAL users are the licensed users and the GAA users are the least priority unlicensed users. In this scenario, PAL operators are willing to give access to their idle spectrum to GAA users to generate extra revenue. SAS will ensure to protect IA users and PAL users from interference caused by lower-tier users. It is the responsibility of SAS to allocate resources to GAA users but the method to do so is left open. In this article, a novel auction algorithm based on Q-learning for dynamic spectrum access (SAS-QLA) is proposed. In SAS-QLA, multiple GAA users dynamically and intelligently bid using Q-learning to access PAL reserved idle channels. SAS will decide to allocate the channels to GAA users with maximum bidding offers. GAA users have their own quality of service (QoS) demands i.e., transmission rate, packet loss, bidding efficiency, and maintain the preference of available PAL reserved idle channels based on Q-learning considering the available QoS. The proposed scenario is also modeled as a knapsack NP-hard problem and solved using dynamic programming and distributed relaxation method. Numerical results demonstrate the effectiveness of the SAS-QLA algorithm in improving the bidding efficiency, maximizing the data rate per unit cost and spectrum utilization.

The citizen broadband radio service (CBRS) is a newly re-purposed spectrum band in 3550-3700 MHz, reclaiming spectrum occasionally used by radars and other incumbents for mobile data communication. It is also a poster child for future LTE-based dynamic spectrum access systems. At present, CBRS does not manage interference from unlicensed LTE users, which we show can be detrimental for its performance. In this paper we develop F-CBRS, a decentralized spectrum interference management system for unlicensed LTE users in the CBRS band. We first look at how much information can each operator be allowed to conceal and how much it has to be mandated (by a regulator) to disclose, and formally prove that the network can achieve fairness only if all operators share fully verifiable information about Access point (AP) locations and user activity. Using this insight we design a channel allocation scheme to efficiently utilize spectrum and incentivise collaboration. This also includes a simple, non-disruptive channel change scheme to frequently and efficiently change channels to accommodate dynamic traffic and environments. Through simulation and testbed evaluation, we show that we increase throughput of more than 90% of the flow by 80%-100% compared to the current CBRS protocol.