Abstract-For a fading Gaussian multiple access channel with user cooperation, we obtain the power allocation policies that maximize the average rates achievable by block Markov superposition coding, subject to average power constraints. The optimal policies result in a coding scheme that is simpler than the one for a general multiple access channel with generalized feedback. This simpler coding scheme also leads to the possibility of formulating an otherwise non-concave optimization problem as a concave one. Using the perfect channel state information available at the transmitters to adapt the powers, we demonstrate gains over the achievable rates for existing cooperative systems.

We present our vision for a departure from the established way of architecting and assessing communication networks, by incorporating the semantics of information, defined, not necessarily as the meaning of the messages, but as their significance, possibly within a real-time constraint, relative to the purpose of the data exchange. We argue that research efforts must focus on laying the theoretical foundations of a redesign of the entire process of information generation, transmission and usage for networked systems in unison by developing (1) advanced semantic metrics for communications and control systems; (2) an optimal sampling theory combining signal sparsity and timeliness, for real-time prediction/reconstruction/control under communication constraints and delays; (3) temporally effective compressed sensing techniques for decision making and inference directly in the compressed domain; (4) semantic-aware data generation, channel coding, packetization, feedback, multiple and random access schemes that reduce the volume of data and the energy consumption, increasing the number of supportable devices. This paradigm shift targets jointly optimal information gathering, information dissemination, and decision-making policies in networked systems.

Abstract-We specify the capacity region for a power-controlled, fading code-division multiple-access (CDMA) channel. We investigate the properties of the optimum power allocation policy that maximizes the information-theoretic ergodic sum capacity of a CDMA system where the users are assigned arbitrary signature sequences in a frequency flat-fading environment. We provide an iterative waterfilling algorithm to obtain the powers of all users at all channel fade levels, and prove its convergence. Under certain mild conditions on the signature sequences, the optimum power allocation dictates that more than one user transmit simultaneously in some nonzero probability region of the space of all channel states. We identify these conditions, and provide an upper bound on the maximum number of users that can transmit simultaneously at any given time. Using these properties of the sum capacity maximizing power control policy, we also show that the capacity region of the fading CDMA channel is not in general strictly convex.Index Terms-Capacity region, code-division multiple access (CDMA), fading channels, iterative waterfilling, power control, sum capacity.

Abstract-For a single carrier frequency division multiple access (SC-FDMA) system, we obtain the jointly optimal power and chunk allocation policies which maximize the sum rate. Our solution is applicable to both localized and interleaved subcarrier mapping schemes. We solve the joint optimization problem by sequentially solving two sub-problems: power allocation and chunk allocation. Primarily, we use an optimal power allocation algorithm, which we derive from Karush-Kuhn-Tucker (KKT) conditions; and then we convert the optimum chunk assignment problem into a maximum weighted matching problem on a bipartite graph, and hence solve it in polynomial time. We also propose two greedy chunk allocation algorithms with lower complexity, and demonstrate that these algorithms produce near optimal results, especially for interleaved subcarrier mapping, when used in conjunction with optimal power control.

For a three user Gaussian multiple access channel (MAC), we propose a new superposition block Markov encoding based cooperation scheme. Our scheme allows the three users to simultaneously cooperate both in pairs, and collectively, by dividing the transmitted messages into sub-messages intended for each cooperating partner. The proposed encoding and decoding at the transmitters take into account the relative qualities of the cooperation links between the transmitters. We obtain and evaluate the achievable rate region based on our encoding strategy, and compare it with the achievable rates for the two user cooperative MAC. We demonstrate that the added diversity by the presence of the third user improves the region of achievable rates, and this improvement is especially significant as far as the sum rate of the system is concerned.