The design of application-specific integrated circuits (ASIC) is at the core of modern ultra-high-speed transponders employing advanced digital signal processing (DSP) algorithms. This manuscript discusses the motivations for jointly utilizing transmission techniques such as probabilistic shaping and digital sub-carrier multiplexing in digital coherent optical transmissions systems. First, we describe the key-building blocks of modern high-speed DSP-based transponders working at up to 800G per wave. Second, we show the benefits of these transmission methods in terms of system level performance. Finally, we report, to the best of our knowledge, the first long-haul experimental transmission - e.g., over 1000 km - with a real-time 7 nm DSP ASIC and digital coherent optics (DCO) capable of data rates up to 1.6 Tb/s using two waves (2 x 800G).

Probabilistically-shaped constellations are found to have larger than expected Kerr nonlinearity induced penalty in long-haul transmission. In this paper, a novel nonlinear tolerant super-Gaussian distribution has been proposed which outperforms the Maxwell-Boltzmann distribution. The simulation and experimental results both show a significant improvement.

In a conventional cellular system, devices are not allowed to directly communicate with each other in the licensed cellular bandwidth and all communications take place through the base stations. In this article, we envision a two-tier cellular network that involves a macrocell tier (i.e., BS-to-device communications) and a device tier (i.e., device-to-device communications). Device terminal relaying makes it possible for devices in a network to function as transmission relays for each other and realize a massive ad hoc mesh network. This is obviously a dramatic departure from the conventional cellular architecture and brings unique technical challenges. In such a two-tier cellular system, since the user data is routed through other users' devices, security must be maintained for privacy. To ensure minimal impact on the performance of existing macrocell BSs, the two-tier network needs to be designed with smart interference management strategies and appropriate resource allocation schemes. Furthermore, novel pricing models should be designed to tempt devices to participate in this type of communication. Our article provides an overview of these major challenges in two-tier networks and proposes some pricing schemes for different types of device relaying.

In this letter, we consider the shared used model in cognitive radio networks and design a spectrum trading method to maximize the total satisfaction of the Secondary Users (SUs) and revenue of the Wireless Service Provider (WSP). In our design, we consider the risk of imperfect spectrum sensing which causes the SUs miss the presence of licensed users and interfere with them. Taking into account this risk, we first propose a multi-unit sequential sealed-bid first-price auction to optimize the payoff of each SU. Then, we derive an expression for the total revenue of WSP and maximize it by optimizing the sensing time. Our results demonstrate that the proposed auction-based spectrum trading method brings better revenue than its counterparts.

In this paper, we address the pricing problem in open-access femtocell networks. We use economic and game theoretic approaches such as market equilibrium and noncooperative game to propose novel pricing schemes. In our proposed solutions, the per unit price of spectrum can be determined dynamically and mobile service providers can gain more revenue than the fixed pricing scheme. Furthermore, in our solutions, femtocell owners have more incentives and satisfaction to justify their participation in open-access use.

In the current literature on cognitive radio, it is commonly assumed that fixed time durations are assigned for spectrum sensing and data transmission. It is however possible to improve the performance by finding the best tradeoff between sensing time and network throughput. In this paper, we formulate the sensing-throughput problem to dynamically assign a number of SUs for cooperatively sensing each channel and calculate the optimal sensing time such as to maximize the total average throughput of SUs in the presence of interference with PUs. We propose a two-step optimization algorithm to optimize sensing time and the number of assigned SUs to each channel. Simulation results demonstrate that significant improvement in the throughput of SUs is achieved when the sensing time and the number of assigned SUs is jointly optimized.

In this paper, we investigate spectrum trading via auction approach for cognitive radio networks. We consider a realistic valuation function in terms of different parameters for secondary users (SUs), and propose an efficient concurrent Vickrey-Clarke-Grove mechanism for non-identical channel allocation in two different scenarios. In the first scenario, SUs can bid for a single channel while in the other one, SUs can bid for a bundle of two channels. Our numerical results demonstrate significant revenue increase for the auctioneer and bidders in comparison with the conventional auction mechanisms.