Coordination and Bargaining over the Gaussian Interference Channel

This work considers coordination and bargaining between two selfish users over a Gaussian interference channel using game theory. The usual information theoretic approach assumes full cooperation among users for codebook and rate selection. In the scenario investigated here, each selfish user is willing to coordinate its actions only when an incentive exists and benefits of cooperation are fairly allocated. To improve communication rates, the two users are allowed to negotiate for the use of a simple Han-Kobayashi type scheme with fixed power split and conditions for which users have incentives to cooperate are identified. The Nash bargaining solution (NBS) is used as a tool to get fair information rates. The operating point is obtained as a result of an optimization problem and compared with a TDM-based one in the literature.Comment: 5 pages, 4 figures, to appear in Proceedings of IEEE ISIT201

Optimal Signaling of MISO Full-Duplex Two-Way Wireless Channel

We model the self-interference in a multiple input single output (MISO) full-duplex two-way channel and evaluate the achievable rate region. We formulate the boundary of the achievable rate region termed as the Pareto boundary by a family of coupled, non-convex optimization problems. Our main contribution is decoupling and reformulating the original non-convex optimization problems to a family of convex semidefinite programming problems. For a MISO full-duplex two-way channel, we prove that beamforming is an optimal transmission strategy which can achieve any point on the Pareto boundary. Furthermore, we present a closed-form expression for the optimal beamforming weights. In our numerical examples we quantify gains in the achievable rates of the proposed beamforming over the zero-forcing beamforming.Comment: To appear in IEEE ICC 2015, London, U

Distributed downlink multi-cell processing requiring reduced-rate back-haul data exchange

Different-complexity Multi-Cell Processing (MCP) schemes employing Distributed Signal-to-Interference-Leakage-plus-Noise-Ratio (SILNR) precoding techniques are proposed, which require reduced back-haul data exchange in comparison to the conventional MCP structure. Our results demonstrate that the proposed structures are capable of increasing the achievable cell-edge throughput and offering different geographic rate profile distributions as well as meeting different delay requirements

Cooperative Downlink Multicell Preprocessing Relying on Reduced-Rate Back-Haul Data Exchange

Different-complexity multicell preprocessing (MCP) schemes employing distributed signal-to-interference leakageplus-noise ratio (SILNR) precoding techniques are proposed, which require reduced back-haul data exchange in comparison with the conventional MCP structure. Our results demonstrate that the proposed structures are capable of increasing the throughput achievable in the cell-edge area while offering different geographic rate profile distributions, as well as meeting different delay requirements

Alternating-Offer Bargaining Games over the Gaussian Interference Channel

This paper tackles the problem of how two selfish users jointly determine the operating point in the achievable rate region of a two-user Gaussian interference channel through bargaining. In previous work, incentive conditions for two users to cooperate using a simple version of Han-Kobayashi scheme was studied and the Nash bargaining solution (NBS) was used to obtain a fair operating point. Here a noncooperative bargaining game of alternating offers is adopted to model the bargaining process and rates resulting from the equilibrium outcome are analyzed. In particular, it is shown that the operating point resulting from the formulated bargaining game depends on the cost of delay in bargaining and how bargaining proceeds. If the associated bargaining problem is regular, a unique perfect equilibrium exists and lies on the individual rational efficient frontier of the achievable rate region. Besides, the equilibrium outcome approaches the NBS if the bargaining costs of both users are negligible.Comment: 8 pages, 6 figures, to appear in Proceedings of Forty-Eighth Annual Allerton Conference on Communication, Control, and Computin

Cross-layer distributed power control: A repeated games formulation to improve the sum energy-efficiency

The main objective of this work is to improve the energy-efficiency (EE) of a multiple access channel (MAC) system, through power control, in a distributed manner. In contrast with many existing works on energy-efficient power control, which ignore the possible presence of a queue at the transmitter, we consider a new generalized cross-layer EE metric. This approach is relevant when the transmitters have a non-zero energy cost even when the radiated power is zero and takes into account the presence of a finite packet buffer and packet arrival at the transmitter. As the Nash equilibrium (NE) is an energy-inefficient solution, the present work aims at overcoming this deficit by improving the global energy-efficiency. Indeed, as the considered system has multiple agencies each with their own interest, the performance metric reflecting the individual interest of each decision maker is the global energy-efficiency defined then as the sum over individual energy-efficiencies. Repeated games (RG) are investigated through the study of two dynamic games (finite RG and discounted RG), whose equilibrium is defined when introducing a new operating point (OP), Pareto-dominating the NE and relying only on individual channel state information (CSI). Accordingly, closed-form expressions of the minimum number of stages of the game for finite RG (FRG) and the maximum discount factor of the discounted RG (DRG) were established. The cross-layer model in the RG formulation leads to achieving a shorter minimum number of stages in the FRG even for higher number of users. In addition, the social welfare (sum of utilities) in the DRG decreases slightly with the cross-layer model when the number of users increases while it is reduced considerably with the Goodman model. Finally, we show that in real systems with random packet arrivals, the cross-layer power control algorithm outperforms the Goodman algorithm.Comment: 36 pages, single column draft forma

Downlink Noncoherent Cooperation without Transmitter Phase Alignment

Multicell joint processing can mitigate inter-cell interference and thereby increase the spectral efficiency of cellular systems. Most previous work has assumed phase-aligned (coherent) transmissions from different base transceiver stations (BTSs), which is difficult to achieve in practice. In this work, a noncoherent cooperative transmission scheme for the downlink is studied, which does not require phase alignment. The focus is on jointly serving two users in adjacent cells sharing the same resource block. The two BTSs partially share their messages through a backhaul link, and each BTS transmits a superposition of two codewords, one for each receiver. Each receiver decodes its own message, and treats the signals for the other receiver as background noise. With narrowband transmissions the achievable rate region and maximum achievable weighted sum rate are characterized by optimizing the power allocation (and the beamforming vectors in the case of multiple transmit antennas) at each BTS between its two codewords. For a wideband (multicarrier) system, a dual formulation of the optimal power allocation problem across sub-carriers is presented, which can be efficiently solved by numerical methods. Results show that the proposed cooperation scheme can improve the sum rate substantially in the low to moderate signal-to-noise ratio (SNR) range.Comment: 30 pages, 6 figures, submitted to IEEE Transactions on Wireless Communication