Onur Kaya

Power Control for Fading Cooperative Multiple Access Channels

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.

Cooperative Multiple Access under Energy Harvesting Constraints

We consider a cooperative multiple access channel (MAC) with two energy harvesting transmitters. The transmitters perform delay constrained transmission, i.e., every information block is encoded, transmitted and decoded between two consecutive energy harvests. We aim to maximize the achievable departure region over a finite transmission duration. We formulate the departure region maximization as a convex optimization problem. We propose an iterative algorithm which uses a directional waterfilling strategy to calculate the optimal power components. The departure region obtained by cooperation is shown to be significantly larger than that of a MAC without cooperation under the same energy arrival patterns. As a special case, we also analyze an energy harvesting relay channel with full duplex cooperation.

Achievable rates for the three user cooperative multiple access channel

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.

Power control for fading multiple access channels with user cooperation

For a fading Gaussian multiple access channel with user cooperation, we obtain the optimal power allocation policies that maximize the rates achievable by block Markov superposition coding. 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 channel state information at the transmitters to adapt the powers, we demonstrate significant gains over the achievable rates for existing cooperative systems.

Optimum power control for CDMA with deterministic sequences in fading channels

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.

Ergodic sum capacity maximization for CDMA:Optimum resource allocation

We solve for the optimum signature sequence and power allocation policies that maximize the information-theoretic ergodic sum capacity of a code-division multiple-access (CDMA) system subject to fading. We show that at most N users may transmit at any given channel state, where N is the processing gain; and those users who are transmitting should be assigned orthogonal signature sequences. We also show that the power allocation policy that maximizes the capacity together with the choice of these signature sequences is single-user water-filling over sets of channel states that are favorable to each user. That is, the capacity maximizing signaling scheme is shown to dictate that the users allocate their powers and signature sequences in such a way that they always avoid interference from each other.

Jointly optimal power and signature sequence allocation for fading CDMA

We solve for the optimum signature sequence and power allocation policies that maximize the information theoretic ergodic sum capacity of a code division multiple access (CDMA) system subject to fading. We show that at most N users may transmit at any given channel state, where N is the processing gain, and that those users who are transmitting should be assigned orthogonal signature sequences. We also show that the power allocation policy that maximizes the capacity together with the choice of these signature sequences is single user waterfilling over sets of channel states that are favorable to each user. That is, the capacity maximizing signalling scheme is shown to dictate that the users allocate their powers and signature sequences in such a way that they always avoid interference from each other.

Cooperative Strategies and Achievable Rates for Two User OFDMA Channels

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.

Jointly optimal chunk and power allocation in uplink SC-FDMA

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.

Power control in the cognitive cooperative multiple access channel

We extend several encoding and decoding techniques from cooperative communications framework, to a cognitive radio system consisting of a primary user (PU) and a secondary user (SU), sending their messages to a common receiver. Assuming that the transmitters and the receiver have full channel state information (CSI) collected and distributed by the common receiver, and that the SU knows the PUs codebook, the cooperation is obtained by block Markov superposition coding, and backwards decoding, which yield a causal overlay scenario. We formulate two rate optimization problems with the aim of, (i) maximizing the sum rate of the system, and (ii) maximizing the rate of the secondary user. We obtain the optimal power allocations for both cases, and the resulting rate regions. The power controlled cooperation turns out to be especially useful when maximizing the sum rate of the system, as it gives the PU significant rate rewards for allowing the cognitive transmitter to access its resources.