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.

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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.

Abstract-We propose three encoding strategies for a two user cooperative Orthogonal Frequency Division Multiple Access (OFDMA) system, based on block Markov superposition encoding (BMSE). We obtain the expressions for the resulting achievable rate regions for all three encoding strategies. We show that, by allowing for re-partitioning and re-encoding of the cooperative messages across subchannels, it is possible to better exploit the diversity created by OFDMA, and higher rates can be achieved. We demonstrate potential rate gains attained by cooperative OFDMA, through simulations.

For a two user cooperative orthogonal frequency division multiple access (OFDMA) system with full channel state information (CSI), we obtain the optimal power allocation (PA) policies which maximize the rate region achievable by a channel adaptive implementation of inter-subchannel block Markov superposition encoding (BMSE), used in conjunction with backwards decoding. We provide the optimality conditions that need to be satisfied by the powers associated with the users' codewords and derive the closed form expressions for the optimal powers. We propose two algorithms that can be used to optimize the powers to achieve any desired rate pair on the rate region boundary: a projected subgradient algorithm, and an iterative waterfilling-like algorithm based on Karush-Kuhn-Tucker (KKT) conditions for optimality, which operates one user at a time and converges much faster. We observe that, utilization of power control to take advantage of the diversity offered by the cooperative OFDMA system, not only leads to a remarkable improvement in achievable rates, but also may help determine how the subchannels have to be instantaneously allocated to various tasks in cooperation.

Abstract-We characterize the optimum power control policies that achieve arbitrary rate tuples on the boundary of the capacity region of a power controlled, code division multiple access (CDMA) system in a fading channel with perfect channel state information (CSI). We propose a "generalized" waterfilling approach, and provide an iterative algorithm that solves for the optimum power allocation policy, for a given arbitrary rate tuple on the boundary of the capacity region. We then investigate the effects of limited feedback on the capacity region, and demonstrate that a good power control policy may require only a very low rate feedback.Index Terms-Capacity region, CDMA, fading channels, generalized iterative waterfilling, limited feedback, power control.