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- Kasra Alishahi, Shayan Dashmiz, Pedram Pad, Farrokh Marvasti
- IEEE Transactions on Information Theory
- 2012

In this paper, we explore some of the fundamentals of synchronous Code Division Multiple Access (CDMA) as applied to wireless and optical communication systems under very general settings (of any size) for the user symbols and the signature matrix entries. The channel is modeled by real/complex additive noise of arbitrary distribution. Two problems are… (More)

- Shayan Dashmiz, Mohammad Reza Takapoui, Pedram Pad, Farrokh Marvasti
- 2010 IEEE International Symposium on Information…
- 2010

Lower and upper bounds are derived for the sum capacity of synchronous CDMA where the signature matrix and input alphabets are binary or (2p + 1)-ary, in two cases of noiseless and noisy channels. The bounds are very tight in some regions. Interestingly, simulations show that the formulas for noisy systems tend to the ones for noiseless system as noise… (More)

- Shayan Dashmiz, Mohammad Reza Takapoui, Sajjad Moazeni, Mehrdad Moharrami, Melika Abolhasani, Farrokh Marvasti
- IET Communications
- 2014

- Shayan Dashmiz, Pedram Pad, Farrokh Marvasti
- ArXiv
- 2009

In this paper, we study binary and ternary matrices that are used for CDMA applications that are injective on binary or ternary user vectors. In other words, in the absence of additive noise, the interference of overloaded CDMA can be removed completely. Some new algorithms are proposed for constructing such matrices. Also, using an information theoretic… (More)

In this paper, we explore the mystery of synchronous CDMA as applied to wireless and optical communication systems under very general settings for the user symbols and the signature matrix entries. The channel is modeled with real/complex additive noise of arbitrary distribution. Two problems are addressed. The first problem concerns whether overloaded… (More)

- Mitra Fatemi, Shayan Dashmiz, Mohammad Hossein Shafinia, Volkan Cevher
- 2012 IEEE Statistical Signal Processing Workshop…
- 2012

Recovery of sparse signals from linear, dimensionality reducing measurements broadly falls under two well-known formulations, named the synthesis and the analysis formulations. Recently, Chandrasekaran et al. introduced a new algorithmic sparse recovery framework based on the convex geometry of linear inverse problems, called the atomic norm formulation. In… (More)

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