73 research outputs found
The Behavior of Unbounded Path-loss Models and the Effect of Singularity on Computed Network Interference
No full text
Optimality of binary power-control in a single cell via majorization
No full text10.1109/ISIT.2011.6034104IEEE International Symposium on Information Theory - Proceedings2891-2895PIST
On the rates of convergence of the wireless multi-access interference distribution to the normal distribution
No full textWiOpt 2010 - 8th Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks453-45
Throughput Scaling in Cognitive Multiple Access With Average Power and Interference Constraints
No full textThis paper derives tight ergodic sum-rate capacity scaling limits for cognitive radio secondary networks under five different communication environments (CoE) for two different network types when secondary users' (SUs) transmission powers are optimally allocated. The network types studied are power-interference limited (PIL) networks and interference limited (IL) networks. In PIL networks, SUs' transmissions are limited by both an average total power constraint and a constraint on the average interference that they cause to primary users (PUs). In IL networks, SUs' transmissions are only limited by an average interference constraint. The capacity scaling results in PIL networks are derived for three different CoEs in which secondary transmitter to secondary base station (STSB) channel gains are Rayleigh distributed while secondary transmitter to primary base station (STPB) channel gains are Rayleigh, Rician or Nakagami distributed. It is shown that secondary network capacity scales according to log log(N) in these three CoEs, where N is the number of SUs. In addition to these three CoEs, two more CoEs are also studied for IL networks: Rician or Nakagami distributed STSB channel gains and Rayleigh distributed STPB channel gains. It is shown that the secondary network capacity scales according to log(N) for all live CoEs in IL networks. This result implies exponential capacity gains in IL networks over PIL networks. The same capacity scaling results are shown to hold even for heterogeneous cognitive radio networks in which different SUs experience statistically different channel conditions. In some cases, our analysis leads to a new notion called effective number of users, which signifies the effective number of users contributing to multiuser diversity in cognitive radio networks. For example, effective number of users is given by K+1/e K N when STSB channel gains are Rayleigh distributed and STPB channel gains are Rician distributed with a Rician factor K
Power Control and Asymptotic Throughput Analysis for the Distributed Cognitive Uplink
No full textThis paper studies optimum power control and sum-rate scaling laws for the distributed cognitive uplink. It is first shown that the optimum distributed power control policy is in the form of a threshold based water-filling power control. Each secondary user executes the derived power control policy in a distributed fashion by using local knowledge of its direct and interference channel gains such that the resulting aggregate (average) interference does not disrupt primary's communication. Then, the tight sum-rate scaling laws are derived as a function of the number of secondary users N under the optimum distributed power control policy. The fading models considered to derive sum-rate scaling laws are general enough to include Rayleigh, Rician and Nakagami fading models as special cases. When transmissions of secondary users are limited by both transmission and interference power constraints, it is shown that the secondary network sum-rate scales according to 1/en h log log (N), where n_h is a parameter obtained from the distribution of direct channel power gains. For the case of transmissions limited only by interference constraints, on the other hand, the secondary network sum-rate scales according to 1/eγ g log (N), where γ g is a parameter obtained from the distribution of interference channel power gains. These results indicate that the distributed cognitive uplink is able to achieve throughput scaling behavior similar to that of the centralized cognitive uplink up to a pre-log multiplier 1/e, whilst primary's quality-of-service requirements are met. The factor 1/e can be interpreted as the cost of distributed implementation of the cognitive uplink
Power control for two-tier multi-carrier MAC under interference constraints
No full textIn this work, a two-tier heterogeneous network architecture is investigated for a channel with multiple carriers. The studied system structure qualifies as a general framework that covers both heterogeneous network (HetNet) structures and cognitive radio (CR) structures. The first and second tiers can be thought as a macro-cell and a femto-cell in a HetNet, respectively. Similarly, the first and second tier users coincide with the primary and secondary users in a CR network, respectively. Unlike our previous works, the data rate maximization problem is investigated for multi-carrier scenarios. It is intended to maximize the total data rate of the second tier users under transmit power constraints per user and per frequency band and a total interference power constraint at the first tier. The performance enhancement of using multiple carriers is investigated by forming a near-optimum, analytically found upper bound for the sum data rate
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