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There is an emerging need for high-rate underwater acoustic (UW-A) communication platforms to enable a new generation of underwater monitoring applications including video streaming. At the same time, modern UW-A communication architectures need to be flexible to adapt and optimize their communication parameters in real time based on the environmental conditions. Existing UW-A modems are limited in terms of achievable data rates and ability to adapt the protocol stack in real time. To overcome this limitation, we present the design, implementation, and experimental evaluation of a new high-rate software-defined acoustic modem (SDAM) with real-time adaptation capabilities for UW-A communications. We introduce new physical-layer adaptation mechanisms that enable either joint adaptation of communication parameters such as modulation constellation and channel coding rate or seamless switching between different communication technologies such as orthogonal-frequency-division-multiplexing and direct-sequence-spread-spectrum. The performance of the proposed SDAM has been evaluated in both indoor (water tank) and outdoor (lake) environments. We demonstrated that the SDAM achieves 104 kbit/s with bit-error-rate (BER) of 2 × 10-5, 208 kbit/s with BER of 10-3, and 260 kbit/s with BER of 10-2 in real time over a 200 m horizontal link at a very-shallow lake environment.

We design, develop, and experimentally validate a complete integrated software/hardware platform for airborne cognitive networking in both indoor and outdoor environments. We first present the concept of all-spectrum cognitive networking and describe a distributed algorithm for maximizing network spectral efficiency by jointly optimizing channel access code-waveforms and routes in a multi-hop network. We then discuss system design parameters and implementation details for setting up a software-defined radio (SDR) testbed that enables reconfigurability at the physical (PHY), medium-access control (MAC), and network (NET) layers of the network protocol stack, either by a user or by means of autonomous decisions. Our algorithmic developments toward spectrally-efficient cognitive networking are software optimized on heterogeneous multi-core general-purpose processor-based SDR architectures by leveraging the design of a novel software-radio framework that offers self-optimization and real-time adaptation capabilities at the PHY, MAC, and NET layers of the network protocol stack. We verify our system design approach in a large-scale testbed deployment of ten terrestrial and one airborne SDR platforms at the Stockbridge Controllable Contested Environment at the Air Force Research Laboratory, Rome, NY, USA. Proof-ofconcept experimental results from both indoor and outdoor testbed deployments show that the proposed system can be used to build all-spectrum cognitive networks that withstand intentional interference at PHY and NET layers and can cognitively coexist with non-cross-layer optimized networks.

We consider the problem of joint resource allocation and admission control in a secondary code-division network coexisting with a narrowband primary system. Our objective is to find the maximum number of admitted secondary links and then find the optimal transmitting powers and code sequences of those secondary links such that the total energy consumption of the secondary network is minimized subject to the conditions that primary interference temperature constraints, secondary signal-to-interference-plus-noise ratio (SINR) constraints and secondary peak power constraints are all satisfied. This is an NP-hard optimization problem which motivates the development of suboptimal algorithms. We propose a novel iterative algorithm to solve this problem in a computationally efficient manner. Numerical results demonstrate that the proposed algorithm provides excellent solutions that result in high energy efficiency and large admitted percentage of secondary links.